U.S. patent application number 13/452492 was filed with the patent office on 2012-08-09 for advertising futures marketplace methods and systems.
This patent application is currently assigned to MetaMarkets Group Inc.. Invention is credited to David SOLOFF.
Application Number | 20120203625 13/452492 |
Document ID | / |
Family ID | 40589149 |
Filed Date | 2012-08-09 |
United States Patent
Application |
20120203625 |
Kind Code |
A1 |
SOLOFF; David |
August 9, 2012 |
ADVERTISING FUTURES MARKETPLACE METHODS AND SYSTEMS
Abstract
Methods and systems provide information products relating to
past, present and future advertising transactions (i.e., contracts
to place advertisements in various media) to enable a marketplace
in advertising products. Information regarding a plurality of
advertising transactions are gathered. Data is analyzed to
determine its attributes. Some attribute values are transformed and
the attribute values are stored in a database. Attributes are
organized or indexed according to a taxonomy of attributes to
provide indexes to advertising transaction records. Indexes and
benchmarks for various selected types of advertising transactions
can be generated by selecting certain records from the database and
aggregating the data or otherwise synthesizing information
products, such as benchmarks and market entities for the selected
types of advertising transactions. Information products may be
published and syndicated as market indexes and benchmarks.
Inventors: |
SOLOFF; David; (Berkeley,
CA) |
Assignee: |
MetaMarkets Group Inc.
San Francisco
CA
|
Family ID: |
40589149 |
Appl. No.: |
13/452492 |
Filed: |
April 20, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12263437 |
Oct 31, 2008 |
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13452492 |
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61045724 |
Apr 17, 2008 |
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60985118 |
Nov 2, 2007 |
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Current U.S.
Class: |
705/14.44 |
Current CPC
Class: |
G06Q 30/02 20130101;
G06Q 30/0283 20130101; G06Q 30/0251 20130101; G06Q 30/0201
20130101 |
Class at
Publication: |
705/14.44 |
International
Class: |
G06Q 30/02 20120101
G06Q030/02 |
Claims
1. A computer system, comprising: a programmable processor; a
network interface coupled to the programmable processor and
configured to enable the programmable processor to communicate via
a network; and a memory coupled to the programmable processor,
wherein the programmable processor is configured with executable
instructions to perform steps comprising: receiving answers to
survey questions from market participants in advertising markets
wherein the survey questions are configured to solicit information
about advertising activity levels in the advertising markets;
transforming the received survey answers into at least one
advertising activity level score; and indexing the advertising
activity level score to establish an advertising activity level
benchmark for a type of advertising activity, wherein the
advertising activity levels are selected from the group consisting
of purchasing activity levels, selling activity levels, viewing
activity levels, marketing activity levels, inquiry activity
levels, hiring activity levels, account visit activity levels, and
request for proposal activity levels.
2. The computer system of claim 1, wherein the programmable
processor is further configured with executable instructions to
perform further steps comprising: publishing the indexed
advertising activity level score as an advertising activity index;
syndicating the indexed advertising activity level score; and
archiving the indexed advertising activity level score.
3. A computer system, comprising: a programmable processor; a
network interface coupled to the programmable processor and
configured to enable the programmable processor to communicate via
a network; and a memory coupled to the programmable processor,
wherein the programmable processor is configured with executable
instructions to perform steps comprising: receiving answers to
survey questions from market participants in advertising markets
wherein the survey questions are configured to solicit information
about future or proposed advertising activity levels in the
advertising markets for a predetermined future time period;
transforming survey answers into at least one future advertising
activity level score; and indexing the future advertising activity
level score to establish a future advertising activity level
benchmark for a type of advertising activity, wherein the
advertising activity levels are selected from the group consisting
of purchasing activity levels, selling activity levels, viewing
activity levels, marketing activity levels, inquiry activity
levels, hiring activity levels, account visit activity levels, and
request for proposal activity levels.
4. The computer system of claim 3, wherein the programmable
processor is further configured with executable instructions to
perform further steps comprising: publishing the indexed future
advertising activity level score as a future advertising activity
index; syndicating the indexed future advertising activity level
score; and archiving the indexed future advertising activity level
score.
5. A non-transitory computer-readable storage medium having stored
thereon computer-executable instructions configured to cause a
computer to perform operations comprising: receiving answers to
survey questions from market participants in advertising markets
wherein the survey questions are configured to solicit information
about future or proposed advertising activity levels in the
advertising markets for a predetermined future time period;
transforming survey answers into at least one future advertising
activity level score; and indexing the future advertising activity
level score to establish a future advertising activity level
benchmark for a type of advertising activity, wherein the
advertising activity levels are selected from the group consisting
of purchasing activity levels, selling activity levels, viewing
activity levels, marketing activity levels, inquiry activity
levels, hiring activity levels, account visit activity levels, and
request for proposal activity levels.
6. The non-transitory computer-readable storage medium of claim 5,
wherein the stored programmable computer-executable instructions
are configured to cause a computer to perform operations further
comprising: publishing the indexed advertising activity level score
as an advertising activity index; syndicating the indexed
advertising activity level score; and archiving the indexed
advertising activity level score.
Description
RELATED APPLICATIONS
[0001] The present application is a divisional of and claims
priority to U.S. patent application Ser. No. 12/263,437, filed Oct.
31, 2008, which claims the benefit of priority to U.S. Provisional
Patent Applications Nos. 60/985,118 filed Nov. 2, 2007 and
61/045,724 filed Apr. 17, 2008, the entire contents of both of
which are hereby incorporated by reference.
FIELD OF THE INVENTION
[0002] The present invention relates generally to computer based
tools for analyzing business transactions and more particularly to
methods and systems for providing an advertising futures
marketplace.
BACKGROUND
[0003] While advertising continues to have a place in a variety of
markets, such as print, broadcast, and electronic, advertising
spend may be trending toward a greater percent of future
advertising dollars being spent in various electronic forms. Large
companies have made public statements regarding requiring marketing
partners to allocate specific, and growing, amounts of advertising
budgets to on-line, electronic advertisements. As this trend
continues, it is perceived that ad agency media buys are going away
and that quantifiable data will form the basis for media buy
decisions.
[0004] While traditionally financial or commodity market maturity
has supported movement toward speed, efficiency, transparency and
away from opacity, inefficiency, and wide value spreads,
advertising market, such as the electronic advertising world has no
such basis for risk mitigation or leveraged speculation.
SUMMARY
[0005] Various embodiments provide methods and systems for support
an advertising transaction marketplace. Data from a plurality of
advertising placement transactions may be captured and analyzed to
extract values of standard advertising attributes that characterize
the captured advertising transaction data. The attribute data may
be extracted and organized according to a taxonomy of attributes
with the values of the standard attributes stored in a database
according to the taxonomy. Selected attributes of the advertising
transactions may be aggregated to provide a common market index of
advertising transactions. Stored advertising transaction records
may be sampled based on the extracted attribute values and used to
determine a benchmark based on the sampled set of advertising
transactions.
[0006] In another embodiment, methods and systems capture
advertising transaction data from a stream of advertising
transaction records received from a source of advertising
transaction data, determine values of standard attributes within
extracted advertising transactions, organize the extracted
advertising transactions into tiers according to a taxonomy of
advertising transaction attributes, identify targeted advertising
attribute values that represent a selected plurality of
transactions, sample a set of advertising transactions based upon
the identified attribute values, and synthesize an advertising
reference entity based upon and representative of the sampled set
of advertising transactions. The results may be used to define a
synthesized advertising reference entity that can be published and
syndicated.
[0007] In another embodiment, methods and systems capture
advertising transaction data from a stream of advertising
transaction records received from a source of advertising
transaction data, determine values of standard attributes within
extracted advertising transactions, sample a set of advertising
transactions based upon the identified attribute values, determine
an advertising product composite price based on the transaction
sample set for sampled advertising products of the identified
parameters conducted within the identified transaction timeframe,
publish the advertising product composite price to a marketplace on
a timely and consistent basis, syndicate the publication of the
advertising product composite price, and establish the advertising
product composite price as an advertising composite price benchmark
for subsequent transactions.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The accompanying drawings, which are incorporated herein and
constitute part of this specification, illustrate exemplary
embodiments of the invention. Together with the general description
given above and the detailed description given below, the drawings
serve to explain features of the invention.
[0009] FIG. 1 is a diagram of example participants in an
advertising futures market place according to the various
embodiments.
[0010] FIGS. 2A and 2B is a process flow diagram of an embodiment
method for generating information products useful in establishing
an advertising futures marketplace.
[0011] FIGS. 3A and 3B is a process flow diagram of an embodiment
method for processing advertising transactions to identify and
process advertising attributes.
[0012] FIG. 4 is a process flow diagram of a method for organizing
and storing advertising transaction data according to a
taxonomy.
[0013] FIG. 5 is a process flow diagram of a method for
establishing a common market index for advertising
transactions.
[0014] FIG. 6 is a process flow diagram of a method for
establishing a benchmark based on a sample set of advertising
transactions.
[0015] FIG. 7 is up process flow diagram of a method for
establishing a reference entity based on a sample set of
advertising transactions.
[0016] FIG. 8 is a process flow diagram for a method of aggregating
sampled advertising transactions to establish an advertising
reference entity.
[0017] FIGS. 9-17 are process flow diagrams of methods for
establishing an advertising benchmark, reference entity and
composite price syndication for a selected type of advertising
product or marketplace.
[0018] FIG. 18 is a process flow diagram of a method for
originating a financial instrument from an advertising
benchmark.
[0019] FIG. 19 is a process flow diagram of a method for the
origination, trading and capture of advertising financial
instruments.
[0020] FIG. 20 is a process flow diagram of a method for generating
and trading financial instruments.
[0021] FIG. 21 illustrates components and interrelationships of an
advertising financial instrument market built around an advertising
financial instrument electronic communications network.
[0022] FIG. 22 illustrates market participants, components and
process flow for syndication of the historic and current market
data regarding advertising financial instruments.
[0023] FIG. 23 is a process flow diagram of a method for generating
a user interface for viewing bid and asking prices and transaction
data for advertising financial instruments.
[0024] FIGS. 24-29 are example screenshots of a user interface
presenting bid and ask prices for advertising transaction
securities.
[0025] FIG. 30 shows three example displays of advertising market
information presented in an embodiment.
[0026] FIGS. 31-38 are process flow diagrams of methods for
establishing a electronic display advertising benchmark, reference
entity and composite price syndication.
[0027] FIGS. 39-46 are process flow diagrams of methods for
establishing a mobile advertising benchmark, reference entity and
composite price syndication.
[0028] FIGS. 47-54 are process flow diagrams of methods for
establishing a search advertising benchmark, reference entity and
composite price syndication.
[0029] FIGS. 55-62 are process flow diagrams of methods for
establishing a video advertising benchmark, reference entity and
composite price syndication.
[0030] FIGS. 63-70 are process flow diagrams of methods for
establishing a game advertising benchmark, reference entity and
composite price syndication.
[0031] FIGS. 71-78 are process flow diagrams of methods for
establishing a public display advertising benchmark, reference
entity and composite price syndication.
[0032] FIGS. 79-86 are process flow diagrams of methods for
establishing a outdoor advertising benchmark, reference entity and
composite price syndication.
[0033] FIGS. 87-94 are process flow diagrams of methods for
establishing a print advertising benchmark, reference entity and
composite price syndication.
[0034] FIGS. 95-102 are process flow diagrams of methods for
establishing a radio advertising benchmark, reference entity and
composite price syndication.
[0035] FIGS. 103-110 are process flow diagrams of methods for
establishing a television advertising benchmark, reference entity
and composite price syndication.
[0036] FIGS. 111-118 are process flow diagrams of methods for
establishing a direct marketing advertising benchmark, reference
entity and composite price syndication.
[0037] FIGS. 119-126 are process flow diagrams of methods for
establishing a telemarketing advertising benchmark, reference
entity and composite price syndication.
[0038] FIGS. 127-134 are process flow diagrams of methods for
establishing a product placement advertising benchmark, reference
entity and composite price syndication.
[0039] FIGS. 135-137 are process flow diagrams of methods for
establishing an advertiser activity index and benchmark.
[0040] FIGS. 138-140 are process flow diagrams of methods for
establishing an advertiser sentiment index and sentiment
benchmark.
[0041] FIG. 141 is a component block diagram of a computer suitable
for implementing the various embodiments.
DETAILED DESCRIPTION
[0042] Various embodiments will be described in detail with
reference to the accompanying drawings. Wherever possible, the same
reference numbers will be used throughout the drawings to refer to
the same or like parts. References made to particular examples and
implementations are for illustrative purposes and are not intended
to limit the scope of the invention or the claims.
[0043] As used herein, the terms "computer," "computing device" or
"mobile device" refer to any one or all of personal computers,
notebook computers, cellular telephones, personal data assistants
(PDA's), palm-top computers, wireless electronic mail receivers and
cellular telephone receivers (e.g., the Blackberry.RTM. and
Treo.RTM. devices), multimedia Internet enabled cellular telephones
(e.g., the iPhone.RTM.), and similar personal electronic devices
which include a programmable processor, memory.
[0044] As used herein, the terms "advertising," "advertisement" and
"ad" refer broadly to any form of product or service promotional
message that is purchased by an advertiser. Beyond the traditional
forms of billboard, print, radio and television advertisements the
embodiments also encompass newer forms of advertising, such as
Internet advertising, product placement (i.e., transactions to have
products displayed in television programs and movies), and
promotional ads or messages appearing in video games, as well as
advertising products that may be developed in the future.
[0045] As used herein, an "advertising transaction" refers to any
order, contract, purchase order or similar agreement by an
advertiser to have an advertisement presented in any media.
[0046] To simplify the description of the various embodiments, the
term "attribute" is used herein to refer to certain details or
aspects within an advertising transaction that together
characterize the nature of the advertisement (e.g., size, context,
etc.), the nature of the transaction (e.g., cost, revenue model,
time of placement, duration, sales channel, buy channel, etc.), the
nature of the media in which the advertisement will appear (e.g.,
print, video, television, electronic display, etc.), the subject
matter content of the media in which the advertisement will appear
(e.g., sports, entertainment, etc.), and other aspects of the
advertisement as described herein. As this brief list suggests, the
term "attribute" is used to refer to a wide variety of features,
specifications, aspects and transaction details. Several examples
of different advertising transaction attributes are listed herein
in order to illustrate the breadth of this term rather than to
limit the embodiments to the specifically mentioned transaction
details.
[0047] Also to simplify the description of the various embodiments,
the term "attribute value" and "value" is used to refer to the
textual, numeric, date or other parameter associated with a given
attribute in a given advertising transaction. For example, an
advertisement may be characterized by a revenue model attribute,
and a value of the revenue model attribute may be "cost per click"
or "cost per impression." As another example, an advertisement may
be characterized by a media subject matter attribute, and the value
of a media subject matter attribute may be "sports" or
"entertainment." As another example, an advertisement may be
characterized by a date attribute, the value of which may be the
date in MM-DD-YYYY format. As explained herein, in some embodiments
an attribute value may be transformed from one format/value, such
as text, to another format/value, such as ordinal numbers, to
facilitate the various processing methods. Thus, the term "value"
should not be construed to be limited to numerical values, and
instead should be construed to encompass any information that is
associated with a particular attribute.
[0048] In this description, the terms "example" and "exemplary" are
used herein to mean "serving as an example, instance, or
illustration." Any implementation described herein as "exemplary"
or as an "example" should not be construed as required, necessarily
preferred or advantageous over other implementations.
[0049] The various embodiments provide information products
relating to past, present and future advertising transactions
(i.e., contracts to place advertisements in various media)
sufficient to enable a marketplace in advertising products.
Information regarding a plurality of advertising transactions are
gathered. The data is processed and analyzed to determine its
attributes. Some attribute values are transformed and the attribute
values are stored in a database. Attributes are organized or
indexed according to a taxonomy of attributes to provide indexes to
advertising transaction records. Indexes and benchmarks for various
selected types of advertising transactions can be generated by
selecting certain records from the database and aggregating the
data or otherwise synthesizing information products, such as
benchmarks and market entities for the selected types of
advertising transactions. Information products may be published and
syndicated as market indexes and benchmarks. Such information
products and the networks that enable capture, storage and
processing of the information may support the generation and
trading of advertising-related security instruments, such as
futures contracts, tradable advertising securities and
advertising-related asset backed securities.
[0050] While an advertising index may be an imperfect reflection of
what a market is doing, and price trending may reflect that market
participants are paying/bidding whatever their budgets will allow,
dips in an advertising index may be due to channel competition and
reduced ad spend, and thus may not be due to changes ad advertising
`value.` An advertising index may characterize the advertising
market better than an industry association forecast in that the
index is reflective of what real people are paying for advertising
products. However, indexing payments alone may be far from
reflective of true market forces; rather it may simply reflect an
established structure of delivery and inventory. A futures market
may reflect all information in an advertising marketplace. While
advertising futures may start trading in parallel with index
values, the futures market may maintain some relationship to the
index and industry that the index seeks to capture. A futures
market may also capture much more of opinion, fact, rumor,
speculation, and the like in ways that may be similar to existing
futures, securities, and options markets. An advertising futures
market may serve to smooth and stabilize advertising by making
possible more rational spot/cash pricing of advertising assets, for
example. Combining this with transparent transaction printing (e.g.
a composite `tape` of all trades of similar or identical
advertising assets) may form a basis for a rational and efficient
advertising market.
[0051] Advertising futures, such as electronic advertising futures,
may open advertising as a tradable, alternative asset class.
Advertising futures may support opening various aspects of
advertising, such as advertising inventory, (e.g. page or web
browser banner ad space), delivery (broadcast, internet, print, and
the like), services (promotions, markup, targeting, and the like),
generation, associated products and services, branding, product
placement, and the like.
[0052] Referring to FIG. 1 which illustrates a representation of an
advertising futures marketplace, an advertising futures market
platform 102 may be associated with advertising future vehicles
104, such as futures and exchange traded notes (ETN), advertising
products 108, delivery mechanisms 110, advertising attributes 112,
participants 114, non-participants 118, indexes 120, and the
like.
[0053] An advertising futures market may enabled by establishing
and providing information products and platforms to enable risk
management and price hedging among advertising market principals,
such as those with inventory or budgetary exposure to advertising
assets. An advertising futures market and platform may facilitate
establishing products and services to enable speculation in this
asset class among non-principal participants, or non-participants.
Advertising futures markets, methods, systems, and platforms may
also facilitate establishing a price discovery and feedback
mechanism that can incorporate various advertising information
related data (pricing, demographics, spend, demand, and the like)
into futures and perhaps spot price movements.
[0054] Advertising futures may be based on one or more indexes
associated with advertising such as aggregate revenue, price trends
(e.g. per unit quantity), yield metrics (e.g. realized .vs. quoted
revenue or utilization), advertiser and/or publisher sentiment,
industry metrics (e.g. Revenue Per Available Impression), Avails
(unfilled capacity across online advertising), delivery volume,
other sentiment measures, Internet traffic volume, and the
like.
[0055] Advertising futures markets may include macro futures that
may be market and market sector focused. Macro futures may be
derivatives of an index and, therefore, may include contracts that
are priced based at least in part on an index value multiplied by
factors such as a US dollar (USD) factor. Macro futures may
facilitate participation by non-advertising industry professionals,
such as individual investors, traders, and the like. Macro futures
may constitute contracts for large classes of advertising assets.
Macro futures products may be derivatives of deliverables.
Settlement prices on macro contracts scheduled for delivery in the
months to come can give investors and consumers a reading on how
the market is anticipating movements in advertising prices and thus
may give order and some rationality to spot advertising
pricing.
[0056] An advertising futures marketplace may include micro futures
markets that may be asset-focused. Micro futures may be established
through bidding on assets individually. The assets and bidding may
be based on a specific purpose/retail customer, market demographic
and the like. Bidding may be granular and may be cash, future
focused, swappable, and the like. A micro future market may benefit
from a real-time exchange in which asset-focused futures may be
purchased, sold, traded, exchanged, guarantee, offered, swapped,
and the like. A micro futures market may also benefit secondary
markets, such as spot markets for similar assets, trading a
delivery date associated with a future for comparable products, and
the like.
[0057] An advertising futures marketplace may be supported by a
variety of trading and exchange platforms and associations such as
an endorsement by the advertising industry, platform affiliation
with CBE/CBOT/ICE/NYMEX/NYX, one or more advertising futures
proprietary trading desks, a buy-side trading desk for advertising
hedging, retail outlets for individual investors, and the like.
[0058] Advertising futures may be based on one or more indexes that
may provide analysis, tracking, and fundamental measures of a wide
variety of aspects of advertising. Any of these aspects of
advertising may be individually represented by an index or may be
aggregated into a combined index. Although various indexes may
exist or be developed to support advertising industry indexing, an
advertising futures market may or may not rely on any specific
index for determining valuation, marketability, and the like. While
indexes may provide a trackable measure of various aspects of the
advertising industry, advertising futures pricing and valuation may
be based on combinations of indexes, data that may be used to
generate advertising indexes, third party data, advertising futures
market historical data, and the like, as well as market demand.
Some examples of indexes that may facilitate establishing an
advertising futures market include indexes based on search, social
media, demographics, and advertising product types.
[0059] Advertising futures markets may include markets associated
with advertising spend migration. As advertising spending migrates
from one vehicle, such as print, to another, such as electronic,
future values in the respective vehicles may respond so that, for
example, electronic futures increase in value and print futures
decrease in value. Individuals, principals, participants, and
others may benefit from market forces that drive this migration so
that risks may be mitigated. In an example, a print advertising
publisher with advertising `space` may choose to purchase
electronic advertising futures as a hedge against future reductions
in print advertising revenue. In another example, an advertiser may
purchase electronic advertising futures today as a hedge against
future cost increases in electronic advertising placements.
[0060] Seasonal changes in advertising spending may also be
leveraged in an advertising futures market. For example, an
investor may purchase advertising futures or options for November
advertising inventory in anticipation of their value increasing due
to an increase in seasonal advertising associated with the
holidays. Similarly particular market segments, such as
advertisements targeted toward men to purchase gifts for women, may
be traded on an advertising futures market. For the example of the
advertising market segment targeting men purchasing gifts for
women, the futures for such advertising in the weeks leading up to
Valentines Day may be highly valued.
[0061] An advertising futures marketplace may be associated with
analytic and trading products, such as screen based trading systems
or an electronic communications network (ECN). An ECN may be
configured to consolidate sell-side offers, buy-side analytics and
algorithmic trading tools (e.g. ROI, relative strength, sector to
sector spend optimization, and the like) to provide market
participants and traders with the information necessary to enable a
market in advertising futures.
[0062] Advertising futures may be derived for aggregate online
advertising, for sector specific advertising such as electronic
premium, tier 2 display ads, CPA, search, exchanged purchased
electronic advertising, print, broadcast, Podcast, direct mail,
streaming video, product placement, and the like.
[0063] An advertising futures market future price may be construed
via an industry standard method such as a simple cash multiplier
that results in a monetization of an index via a futures
market.
[0064] Advertising futures may be available as structures such as
futures, options, swaps, exchange-traded notes (ETNs), and the
like. Exchange-traded notes may include an investment vehicle for
direct institutional and retail investment in advertising assets,
and may be based on market-recognized indexes of price and activity
levels in the advertising industry. An ETN structure may take
principal and invest it in Treasury Securities, not directly in the
assets that the ETN structure tracks. However, a Note-issuing
institution (e.g. Barclay's or Merrill Lynch) may guarantee the
return to the investor of an amount equal to: Principal or Note
Face Value*(1+((Index Value at Redemption Date-Index Value at
Investment Date))/100). Similar ETN structures have been developed
and successfully launched to open new and previously inaccessible
asset classes to retail and institutional investors, and may
provide a viable vehicle for advertising futures retail investing.
Such a structure can be extended to track multiple indexes across
the advertising universe, including print, broadcast, spend
migration, yield metrics, price metrics and revenue.
[0065] The methods and systems of the various embodiments may
include characterizing, summarizing and indexing advertising
transactions according to a standard set of attributes of
advertising transactions. A process of indexing may include
determining values of standard attributes of a plurality of
transactions for the placement of advertisements in media;
selecting a subset of advertising transactions based on selected
attribute values of a plurality of transactions for placement of
advertisements; and providing an index based on the selected set of
transactions whose attributes match the selected attribute values.
The advertising medium may be of a variety of types including:
electronic medium, internet-enabled online medium, electronic game,
mobile, search, print, newspaper, magazine, broadcast, television,
radio, satellite-based, outdoor advertising, and the like.
[0066] Standardized attributes characterizing advertising
transactions may include a product attribute, a media platform
attribute (e.g. an internet-enabled online display), a media
channel attribute, an advertising tier attribute, a duration
attribute, a time to launch attribute, a geographic attribute, a
location attribute, a proximity attribute, a placement attribute, a
dimension attribute, a size attribute, a relative placement
attribute, a font attribute, font size attribute, an industry
attribute, a channel attribute, a time period attribute, a seasonal
attribute, a keyword attribute, a target customer attribute, a
demographic attribute, a psychographic attribute, a medium
attribute, an animation attribute, a motion attribute, an estimated
viewer attribute, an estimated click through attribute, an
estimated purchase attribute, an estimated listener attribute, and
the like.
[0067] Standard attributes characterizing advertising transactions
may further include a pricing model attribute which is the pricing
model associated with the advertisement. Examples of pricing models
include, for example, price per display, price per placement, price
per view, price per click, cost per thousand impressions (CPM),
cost per action (CPA), price per action and affiliate revenue.
[0068] Standard attributes characterizing advertising transactions
may also include a media segmentation attribute, such as an
up-front display segment, a premium display segment, an
exchange-traded display segment, a targeted display segment, a
remnant display segment, a social advertising display segment, a
broadband video segment, an in-line advertising segment, an overlay
segment, a border segment, a search segment, a keyword-indexed
segment, and an in-gaming segment.
[0069] Standardized attributes characterizing advertising
transactions may further include an advertising product, a media
platform in which the advertisement appears (e.g., an
internet-enabled online display), a media channel in which the
advertisement appears, an advertising tier, a duration of the
advertisement, a time to launch the advertisement, a geographic
target of the advertisement, a location target of the
advertisement, a proximity aspect of the advertisement (e.g.,
proximity to a particular subject matter, element of the
publication or other advertisement), a placement of the
advertisement, a dimension of the advertisement, a size of the
advertisement, a relative placement of the advertisement, a font
used in the advertisement, font size used in the advertisement, an
industry addressed in the advertisement, a channel for the sale or
purchase of the advertisement, a time period in which the
advertisement may appear, a seasonal period in which the
advertisement may appear, a keyword within the advertisement, a
target customer to whom the advertisement is addressed, a
demographic target of the advertisement, a psychographic target of
the advertisement, a medium used in the advertisement, an animation
used in the advertisement, a motion used in the advertisement, an
estimated viewer level expected to view the advertisement, an
estimated click-through value, an estimated purchase value, an
estimated listener value, and the like.
[0070] A variety of benchmarks of advertising transactions may be
generated including, for example, an index, an advertising
sentiment benchmark, an activity level benchmark, a benchmark based
on a survey of activity level, an advertising reference entity
related to a type of market, and the like. The methods and systems
of the various embodiments may generate an advertising market
benchmark for use as a basis of a transaction by identifying
attribute parameters of a plurality of advertising transactions,
sampling a set of advertising transactions based on the identified
parameters, and establishing a benchmark based on the transaction
sample set. The systems of the various embodiments may include a
user interface for generating and viewing benchmarks by taking an
advertising market benchmark based on a set of advertising
transactions having a standardized set of attributes; and providing
a user interface whereby a party may view changes in the
benchmark.
[0071] The methods and systems of the various embodiments may
include syndication of advertising security and derivative
transactions. Syndication may include tracking the attributes of a
plurality of transactions for placement of advertisements in media;
providing an advertising market benchmark based on a set of
transactions having a standardized set of attributes; and
syndicating the benchmark. Syndicating the index may include
providing a data feed that may include a value for the index
associated with a time period. The feed may be a live or real time
data feed accessible by a network. The network may include a
computer network, a telecommunications network, a local area
network, a wireless network, the Internet and a mobile
telecommunications network. Syndication may pertain to the index or
to granular transactions across a multiplicity of attribute-centric
transaction nodes, which could be aggregated along various axes to
compose an index.
[0072] The methods and systems of the various embodiments may
include syndication of all historic and current market data
regarding advertising security and derivative transactions. This
syndication may include tracking the attributes of a plurality of
transactions for placement of advertisements in media; providing a
real-time data stream of all advertising financial market
instrument transactions having a standardized set of attributes to
form a composite advertising benchmark tape indicator to the market
of the current status of the advertising market financial
instruments with particular attributes or combinations of
attributes; and syndicating the real-time data stream. Syndicating
may include providing historic advertising security and derivative
transaction data having a standardized set of attributes.
Syndicating may further include providing a set of data tools to
analyze the historic data along multiple dimensions. Syndication
may further include composing custom views, providing standard
views, providing an index based on a set of transactions having a
standardized set of attributes, and the like. In an example, all
like transactions are synthesized into a single, composite
transaction for purposes of accurately gauging market levels.
[0073] The syndication information may include a value of the index
at a point in time, a rate of change of the index, an individual
transaction vs. history of itself, an individual transaction vs.
index composed of like transactions, and an individual transaction
vs. composite of the market, of the media type, of the platform
type, of the content type, of the demographic type, of the
geographic type, of the psychographic type, and the like.
[0074] The syndication information may include a value of an index
for a type of media including: internet-enabled online medium,
electronic game, mobile, search, print, newspaper, magazine,
broadcast, television, radio, satellite-based, outdoor advertising,
and the like.
[0075] The syndication information may include a value of the index
for a transaction having particular standardized attribute values.
The standardized attributes used for syndication may be the same as
those listed above and used for characterizing, summarizing and
indexing a plurality of advertising transactions. Syndication
information may further include volume information for advertising
transactions.
[0076] Syndication may be based on a subscription. Syndication may
provide information products and services to a terminal on a closed
network. Syndication may be associated with a user interface, and
the user interface may include analysis tools for analyzing the
syndicated information.
[0077] The methods and systems may include determining and
publishing a sentiment index by periodically posing a standard set
of queries associated with attributes of advertising transactions
to a plurality of parties to advertising transactions and
aggregating the responses to generate an index of sentiment about
the market for advertising transactions. The set of queries may
relate to the price of advertising, a type of advertising medium, a
preference among advertising media, effectiveness of advertising,
perceived ad spend migration, perceived or derived value from ad
spend, spend allocation forecasts, and the like.
[0078] The methods and systems of the various embodiments may
include aggregation of various advertising transaction data.
Aggregation may include transaction attribute aggregation, such as
obtaining data for a plurality of advertising transactions for a
type of media; and aggregating selected attributes of the
advertising transactions to provide a common market index of
advertising transactions. Methods of aggregation may include
averaging prices of the advertising transactions for the medium for
a selected time period (e.g. the present time period, a future time
period, a custom-defined time period, and the like). Aggregating
may be based on a standardized set of advertising transaction
attributes. Aggregation may be accomplished over any one or
combination of the standardized attributes listed above for
characterizing, summarizing and indexing advertising transaction.
Aggregation may include normalizing data, cleansing data prior to
aggregation, preprocessing, de-duplicating, triangulating and
archiving transaction data, segmenting data based on the type of
media, segmenting data by time period and the like. Aggregation may
be based on various pricing and revenue models, such as cost per
click, cost per action, cost per impression, price per page, price
per viewer, targeted segment, keyword, transaction date, content
type, distribution platform, product dimension, product motion
attribute, product standard advertising unit identifier,
transaction lead/lag time, time to launch, and other revenue model
related attributes.
[0079] The methods and systems of the various embodiments may
provide an analytic workbench for analyzing data from advertising
transactions. The workbench may include obtaining data for a
plurality of advertising transactions for a type of media;
aggregating data associated with selected attributes of the
advertising transactions; and providing a set of tools whereby a
user may perform analysis on the aggregated data. The workbench may
include analytic tools such as tools that allow for calculation of
an index for a subset of transactions along user-defined groups of
attributes, analysis of the index based on information for canned
and user-defined periods of time, analysis of subsets of
transactions, analysis of transactions for specific types of media,
historic archiving of select analytic views and the on-demand
recall of such views, reproduction, transmission and publication of
select analytic views, graphical representation of select analytic
views, calculation of different statistics and technical analyses
associated with the transactions (e.g. weighted average statistics,
simple and exponential moving averages), transaction volume,
convergence divergence, Bollinger bands, performance versus
composite peer group, performance versus market in toto or by
segment/platform, and the like.
[0080] The methods and systems of the various embodiments may
include establishing a reference entity, such as by identifying
attribute parameters of a plurality of advertising transactions;
sampling a set of advertising transactions based on the identified
parameters; and establishing a reference entity based on the
transaction sample set. A reference entity may be established by
aggregating transactions such as through bottom up aggregation.
This may include extracting, transforming and loading a stream of
advertising transaction records from a plurality of data sources;
tiering the transaction records according to a taxonomy of
advertising attribute values; identifying targeted attribute values
that represent a selected plurality of advertising transactions;
sampling a set of advertising transactions based on the identified
parameters; and establishing a reference entity based on the
transaction sample set. Data sources may include advertising
servers, advertising billing transaction systems, advertising
networks, advertising exchanges, publisher networks, media buyer
networks, and the like. In an example of a reference entity for net
revenue activity for all sample transactions, the reference entity
value may be a composite revenue value for all sample transactions.
Aggregating transactions may include extracting, transforming and
loading a stream of advertising transaction records from a
plurality of data sources; tiering the transaction records
according to a taxonomy of advertising attribute values;
identifying targeted attribute values that represent a selected
plurality of advertising transactions; sampling a set of
advertising transactions based on the identified values; and
establishing and/or synthesizing a reference entity based on the
transaction sample set.
[0081] Aggregating of advertising transaction data may be
accomplished to define a reference entity for a variety of types of
advertising transactions. For example, an advertising reference
entity can be defined for electronic display advertising by
selecting electronic display advertising transaction records or
loading a stream of electronic display advertising transaction
records from a plurality of data sources, and aggregating the
records to synthesize an electronic display reference entity.
Similarly, an advertising reference entity can be defined for
mobile advertising by selecting mobile advertising transactions or
loading a stream of mobile advertising transaction records from a
plurality of data sources and aggregating the records to synthesize
a mobile display reference entity. Similarly, an advertising
reference entity can be defined for video advertising by selecting
video advertising transaction records or loading a stream of video
advertising transaction records from a plurality of data sources
and aggregating the records to synthesize a video advertising
reference entity. Similarly, an advertising reference entity can be
defined for game advertising by selecting game advertising
transactions or loading a stream of game advertising transaction
records from a plurality of data sources and aggregating the
records to synthesize a game advertising reference entity.
Similarly, an advertising reference entity can be defined for
search advertising by selecting search advertising transactions or
loading a stream of search advertising transaction records from a
plurality of data sources and aggregating the records to synthesize
a search advertising reference entity. Similarly, an advertising
reference entity can be defined for public display advertising by
selecting public display advertising transactions or loading a
stream of advertising transaction records from a plurality of data
sources associated with public display advertising transactions and
aggregating the records to synthesize a public display reference
entity. Similarly, an advertising reference entity can be defined
for outdoor advertising by selecting outdoor advertising
transactions or loading a stream of advertising transaction records
from a plurality of data sources associated with outdoor
advertising transactions and aggregating the records to synthesize
an outdoor display reference entity. Similarly, an advertising
reference entity can be defined for offline advertising by
selecting offline advertising transactions or loading a stream of
advertising transaction records from a plurality of data sources
associated with offline advertising and aggregating the records to
synthesize an offline advertising reference entity. Similarly, an
advertising reference entity can be defined for print advertising
by selecting print advertising transactions or loading a stream of
advertising transaction records from a plurality of data sources
associated with print advertising transactions and aggregating the
records to synthesize a print advertising reference entity.
Similarly, an advertising reference entity can be defined for radio
advertising by selecting radio advertising transactions or loading
a stream of advertising transaction records from a plurality of
data sources associated with radio advertising transactions and
aggregating the records to synthesize a radio advertising reference
entity. Similarly, an advertising reference entity can be defined
for television advertising by selecting television advertising
transactions or loading a stream of advertising transaction records
from a plurality of data sources associated with television
advertising transactions and aggregating the records to synthesize
a television advertising reference entity. Similarly, an
advertising reference entity can be defined for direct marketing
advertising by selecting direct marketing advertising transactions
or loading a stream of advertising transaction records from a
plurality of data sources associated with direct marketing
advertising transactions and aggregating the records to synthesize
a direct marketing advertising reference entity. Similarly, an
advertising reference entity can be defined for telemarketing
advertising by selecting telemarketing advertising transactions or
loading a stream of telemarketing transaction records from a
plurality of data sources associated with telemarketing advertising
transactions and aggregating the records to synthesize a
telemarketing advertising reference entity. Similarly, an
advertising reference entity can be defined for product placement
by selecting product placement advertising transactions or loading
a stream of advertising transaction records from a plurality of
data sources associated with product placement advertising
transactions and aggregating the records to synthesize a product
placement reference entity.
[0082] The methods and systems of the various embodiments may
include using data for a single advertising product-type as a
reference entity by identifying attribute parameters of a selected
type of advertising product; sampling the identified parameters for
a set of advertising transactions for the type of advertising
product over time; and establishing a benchmark entity based on the
transaction sample set. The product may be a high-demand
advertising product. The benchmark entity consists of a
volume-weighted composite price for a series of transactions in the
advertising product.
[0083] The methods and systems of the various embodiments may
include surveying market participants to establish a sentiment
benchmark, such as by surveying participants in advertising markets
with a predefined set of questions intended to solicit information
about forward-looking sentiment about the advertising markets;
transforming the survey answers into a sentiment score; and
indexing the score to establish a sentiment benchmark for at least
one type of advertising. The survey data may be taxonomized based
on attributes of advertising transactions. The advertising markets
may include any one or more of the various types of advertising
markets The surveyed participants may include advertisers,
advertising brokers, publishers, and the like. The questions may
relate to a type of information that may include expected spending
by platform, expected spending by product, expected ROl by
platform, expected ROl by product, expected allocation shift among
products, expected overall spending levels, perceived value of
products, perceived value of platforms, expected pricing, and the
like.
[0084] The methods and systems of the various embodiments may
include surveying market participants to establish an activity
level benchmark, such as by surveying participants in advertising
markets with a predefined set of questions intended to solicit
information about activity levels in the advertising markets;
transforming the survey answers into at least one activity level
score; and indexing the score to establish an activity level
benchmark for a type of advertising activity. The activity levels
may be any one or more of: purchasing activity; selling activity;
and viewing activity. The survey data may be organized according to
the taxonomy described above based on attributes of the advertising
transactions. The advertising markets may include any one or more
of the various types of advertising markets. Survey participants
may include advertisers, advertising brokers, publishers, and the
like. The survey questions may relate to or include spending by
product, spending by platform, viewing by product, viewing by
platform, allocation among products, allocation across platforms,
migration among products, migration among platforms, revenue by
product, revenue by platform, and the like.
[0085] Results from the benchmarking process may an index, an
advertising sentiment benchmark, an activity level benchmark, based
on a survey of activity level, an advertising reference entity
related to a type of market, and the like.
[0086] The methods and systems of the various embodiments may
include providing a standardized advertising instrument, such as an
advertising security. A process for creating a standardized
advertising instrument may include taking an index based on a set
of advertising transactions having a standardized and/or normalized
set of attributes and creating at least one of an attribute
standardization processing framework, a revenue rights assignment
mechanism, and a securitization mechanism via cash multiplier or
the like so that a party may enter into a transaction, the terms of
which are based on the index.
[0087] An advertising security transaction may be a primary market
security transaction based on the underlying market value of
physical advertising assets. The transaction may be based on an
index value derived from an aggregation of advertising transactions
involving like attributes, such as media platform, channel, tier,
product size, motion attribute, demography, content context,
pyschography, geography, and the like, including various product
taxonomies.
[0088] The methods and systems of the various embodiments may
include creation of an advertising security whereby the instrument
which is based on standardized attributes provides the ability for
principal and non-principal parties to purchase or sell the revenue
rights associated with underlying real physical advertising assets
without taking possession or delivery of the physical assets
themselves. In effect, pre-sale/pre-purchase of select advertising
assets may be made available to all market participants, outside
any traditional advertising industry mechanisms or calendars,
enabling much more nuanced and liquid price discovery.
[0089] Such advertising securities or instruments can be based on
the most popular/in-demand/liquid combination of standardized
advertising attributes as delineated in the standardized taxonomy
of advertising attributes, or on an OTC basis according to such
attributes, or as market-makers or counterparties demand. Such
advertising securities or instruments can be multi-use contracts
enabling: insurance; total return style commodity investment;
portfolio diversification, and the like. Advertising instruments
may represent any one or combination of the variety of advertising
medium types including: internet-enabled online medium, electronic
game, mobile, search, print, newspaper, magazine, broadcast,
television, radio, satellite-based, outdoor advertising, and the
like.
[0090] The methods and systems of the various embodiments may
include creation of a generic advertising market financial
instrument that may involve taking an advertising market benchmark
based on information about at least one of an activity and a
sentiment in an advertising market; and providing an advertising
market financial instrument whereby a party may enter into a
transaction the terms of which are based on the advertising market
benchmark. The benchmark may be an index, an advertising sentiment
benchmark, an activity level benchmark, based on a survey of
activity level, an advertising reference entity related to a type
of market, and the like. The generic advertising market financial
instrument may be a derivative financial instrument, an exchange
traded note, an option, a futures contract, an exchanged traded
fund, a principal-protected note, a securitization, a security, a
single advertising product future, an advertising sentiment future,
a basis for a swap, and the like. An advertising market associated
with a generic advertising market financial instrument may include
any one or more of the various types of advertising markets e. The
generic advertising financial instrument may represent a variety of
advertising medium types including: internet-enabled online medium,
electronic game, mobile, search, print, newspaper, magazine,
broadcast, television, radio, satellite-based, outdoor advertising,
and the like. The generic advertising financial instrument may
include any of the standardized attributes described herein.
[0091] The transaction based on a generic advertising market
financial instrument may be a futures transaction, with the futures
contracts derived from indexes based on individual or combined
standardized advertising attributes. The indexes may represent an
aggregation of a set of advertising transactions for a type of
media. Futures contracts may be priced according to market BID and
ASK entry. Futures contracts may be priced according to a
market-making computer-generated optimal selling price based on
existing market conditions. Futures contracts may be bespoke or
over the counter (OTC) contracts and may not be listed on an
exchange but rather entirely negotiated between party and
counterparty.
[0092] The transaction based on a generic advertising market
financial instrument may be an option on a listed futures contract
that may have been otherwise derived and transacted. The
transaction may also be a principal protected note whose return may
be linked to an index value and whose principal may be protected
for the note's duration. The transaction may also be an exchange
traded fund whose value may be linked to an index value based on
transaction values for advertising assets of specific and
standardized attributes.
[0093] The methods and systems of the various embodiments may
include creating a primary advertising market financial instrument
by taking an advertising market benchmark based on information
about at least one of an activity level and a sentiment relating to
an advertising market; and providing a primary instrument whereby a
party may enter into a transaction the terms of which are based on
the advertising market benchmark. The primary instrument may enable
a party to access a spot or cash market in advertising without
taking possession or providing delivery of physical advertising
assets. The primary instrument may also be an exchange traded fund,
an exchange traded note, a principal-protected note, a
securitization and the like. The benchmark may be an index, an
advertising sentiment benchmark, an activity level benchmark, based
on a survey of activity level, an advertising reference entity
related to a type of market, and the like. The advertising
financial instrument may be a derivative instrument, an exchange
traded note, an option, a futures contract, an exchanged traded
fund, a principal-protected note, a securitization, a security, a
single advertising product future, an advertising sentiment future,
a basis for a swap, and the like. An advertising market associated
with a generic advertising market financial instrument may include
any one or more of the various types of advertising markets.
[0094] The methods and systems of the various embodiments may
include creating a derivative advertising market financial
instrument by taking an advertising market benchmark based on
information about at least one of an activity level and a sentiment
relating to an advertising market; and providing a derivative
instrument whereby a party may enter into a transaction the terms
of which are based on the benchmark. The derivative instrument may
be a standardized exchange-traded futures contract that enables
parties to speculate on levels of an advertising benchmark at a
future date. The derivative instrument may be an option on the
benchmark or an option on a future based on the benchmark. The
benchmark may be an index, an advertising sentiment benchmark, an
activity level benchmark, based on a survey of activity level, an
advertising reference entity related to a type of market, and the
like. The derivative instrument may have terms that may include
cash settlement, trading unit, settlement method, point size,
strike date, strike price interval, limits, price banding, minimum
fluctuation, trading hours, listed platforms, minimum block size,
product calendar, issuance, mark-to-market policies, convergence
with physical underlying entity, exchange rules, distribution,
leverage on money, and the like. The exchange of the instrument may
be made possible by the fielding of bids and asks for these
instruments. The exchange platform may automatically list, sort,
filter, match and confirm best bids and offers for standardized
advertising instruments and derivatives therefrom. The platform may
use proprietary listing and matching algorithms to match best bids
and offers. An automated market making entity may generate optimal
price for these bids and offers. The derivative advertising market
financial instrument may include standardized attributes which may
include any of the advertising attributes identified herein.
[0095] The instrument may be a derivative instrument, an exchange
traded note, an option, a futures contract, an exchange traded
fund, a principal-protected note, a securitization, a security, a
single advertising product future, an advertising sentiment future,
a basis for a swap, and the like. An advertising market associated
with the derivative advertising market financial instrument may
include any one or more of the various types of advertising
markets.
[0096] The methods and systems of the various embodiments may
include facilitating the exchange of advertising financial
instruments. The exchange of advertising financial instruments may
include taking an advertising market benchmark based on a set of
advertising transactions having a standardized set of attributes;
and facilitating the exchange of advertising market financial
instruments whereby a party to an instrument may enter into a
transaction the terms of which are based on the benchmark. A
mechanism for facilitating the exchange of advertising assets may
be an electronic communications network (ECN), open only to
qualified members, providing secure data communications between
qualified principal, non-principal and other market participants.
The ECN may provide communications mechanisms between parties via
secure instant messenger running on the trader desktop suite,
secure web portal, secure electronic mail, and other secure
communication means, such that parties to the exchange may
simultaneously and in real time view securities and derivative
price and volume information while communicating with an
advertising trade counterparty, broker or market-maker. The ECN
operator may be the sole owner and provider of price, volume and
transaction data for physical and derivative advertising assets.
The methods and systems of the various embodiments relating to
exchange of instruments may further include providing a facility
for clearing an exchange transaction, such as a central
counterparty (CCP) mechanism whereby all contracts and trades are
matched with the necessary financial counterparty.
[The methods and systems of the various embodiments relating to
exchange of instruments may further include providing a facility
for the optimized pricing of advertising financial instruments
based on real-time and historic advertising market conditions. Such
a facility may be a computer programmed with algorithmic software
so that market conditions are monitored by the computer and used to
adjust its pricing models and re-price bids and offers for
advertising financial instruments to reflect market conditions.
[0097] The methods and systems of the various embodiments relating
to exchange of instruments may further include providing a facility
for settling exchange transactions such as an advertising
instruments and securities registry whereby all data generated
concerning trading parties, counterparties, instruments,
transactions, expiration dates, revenue assignment rights, physical
delivery obligations, and the like are recorded, archived, indexed,
made searchable, sortable and syndicated. The methods and systems
of the various embodiments relating to exchange of instruments may
further include providing a facility for trade capture, whereby all
data for all listed and OTC physical underlying and derivative
advertising transactions are captured, archived and
provisioned.
[0098] The systems of the various embodiments may include a user
interface for facilitating instrument exchanges. The user interface
may obtain or generate an advertising market benchmark based on a
set of advertising transactions having a standardized set of
attributes, and provide a user interface for exchanging advertising
market financial instruments whereby a party to an advertising
market financial instrument may enter into a transaction the terms
of which are based on the benchmark.
[0099] The systems of the various embodiments may include a user
interface for entering into standardized transactions by obtaining
or generating an advertising market benchmark based on a set of
advertising transactions having a standardized set of attributes,
and providing a user interface entering into transactions whereby a
party may enter into a transaction the terms of which are based on
the benchmark. The user may enter a bid or an ask quantity for an
instrument the pricing terms of which are based on the index.
[0100] The systems of the various embodiments may include a user
interface for viewing benchmarks by obtaining or generating an
advertising market benchmark based on a set of advertising
transactions having a standardized set of attributes, and providing
an information display by which a party may view changes in the
benchmark.
[0101] The systems of the various embodiments may include a user
interface for viewing bids/asks/transaction data for advertising
securities that may be based on indexes whose values are derived
from a standardized set of attributes obtained or generated by
taking an advertising market benchmark based on a set of
advertising transactions having a standardized set of attributes,
and providing an information display by which a party may view bid
and ask transactions for advertising financial market instruments.
Alternatively, the user interface present an information display
for viewing bids/asks/transaction data for derivative advertising
securities based on indexes whose values are derived from a
standardized set of attributes.
[0102] The systems of the various embodiments may include a user
interface for viewing registry data for all standardized
advertising and derivative transactions by obtaining or generating
an advertising market benchmark based on a set of advertising
transactions having a standardized set of attributes, and providing
an information display by which a party may view registry data for
advertising market financial instruments.
[0103] The methods and systems of the various embodiments may
include syndication of advertising security and derivative
transactions. Syndication may include tracking the attributes of a
plurality of transactions for placement of advertisements in media;
providing an advertising market benchmark based on a set of
transactions having a standardized set of attributes; and
syndicating the benchmark. Syndicating the index may include
providing a data feed that may include a value for the index
associated with a time period. The feed may be a live/real time
data feed accessible by a network. The network may include a
computer network, a telecommunications network, a local area
network, a wireless network, the Internet and a mobile
telecommunications network. Syndication may pertain to the index or
to granular transactions across a multiplicity of attribute-centric
transaction nodes, which could be aggregated along various axes to
compose an index.
[0104] The methods and systems of the various embodiments may
include syndication of historic and current market data regarding
advertising security and derivative transactions. This syndication
may include tracking the attributes of a plurality of transactions
for placement of advertisements in media; providing a real-time
data stream of all advertising financial market instrument
transactions having a standardized set of attributes to form a
composite advertising benchmark tape indicator to the market of the
current status of the advertising market financial instruments with
particular attributes or combinations of attributes; and
syndicating the real-time data stream. Syndicating may comprise
providing historic advertising security and derivative transaction
data having a standardized set of attributes; Syndicating may
further comprise providing a set of data tools to analyze the
historic data along multiple dimensions. Syndication may further
comprise composing custom views, providing standard views,
providing an index based on a set of transactions having a
standardized set of attributes, and the like. In an example all
like transactions can be synthesized into a single, composite
transaction for purposes of accurately gauging market levels.
[0105] The syndication information may be a value of the index at a
point in time. The syndication information may be rate of change of
the index, individual transaction vs. history of itself, individual
transaction vs. index composed of like transactions, individual
transaction vs. composite of the market, of the media, of the
platform, of the content type, of the demographic, geographic,
psychographic, and the like.
[0106] The syndication information may be a value of an index for a
type of media including: internet-enabled online medium, electronic
game, mobile, search, print, newspaper, magazine, broadcast,
television, radio, satellite-based, outdoor advertising, and the
like. The syndication information may be a value of the index for a
transaction having particular standardized attributes, including
any one or more of the standard attributes described herein.
[0107] Syndication may be based on a subscription. The syndication
may include a terminal on a closed network. Syndication may be
associated with a user interface that includes analysis tools for
analyzing the syndicated information. Syndication information may
include volume information for advertising transactions.
[0108] The methods and systems of the various embodiments may
include creating macro advertising securities. Creation of macro
advertising securities may include obtaining survey results on
advertising spend and channel allocation for a type of media;
multiplying the indexed value of responses by a consistent
numerical value to obtain an index level; and multiplying the index
by a cash multiplier to create a macro advertising security based
on advertiser sentiment or ad spend migration or other macro level
advertising industry trends and forecasts. The methods and systems
of the various embodiments may include facilitating the trade and
exchange of macro advertising securities. Macro securities may be
associated with micro securities and derivatives described herein
in that the method of derivation may be different but the
securitization, market making, and trading may be on a single,
shared platform.
[0109] The methods and systems of the various embodiments include
facilitating an advertising super exchange including an interface
for managing a unified advertising order book across a plurality of
advertising networks.
[0110] The methods and systems of the various embodiments may also
include creating a trading hub for standardized advertising
securities and derivative instruments. Such a trading hub may list
advertising attributes and the prices of the corresponding
advertising assets transacted featuring these attributes. The
trading hub may be uniquely positioned to demonstrate the prices
achieved by advertising assets with certain attribute
combinations.
[0111] The methods and systems of the various embodiments may
include facilitating a meta ad exchange and managing multiple ad
network relationships and/or pan-network ad exchange. This may
include brokering bids and asks across multiple product categories
as well as brokering within electronic advertising medium or other
advertising media.
[0112] The methods and systems of the various embodiments may
include creating an advertising bank to facilitate securitization.
The creation of such an advertising bank may include obtaining
information about advertising transactions across at least one
advertising network; obtaining advertising rights to a plurality of
advertising opportunities; and using the advertising rights to
facilitate cash settlement of futures transactions for advertising
transactions. Futures transactions may be based on an index and the
index may be based on standard attributes of advertising
transactions including those identified herein. The index may be
based on a plurality of standard attributes of advertising
transactions. The advertising bank may include obtaining
information about advertising transactions across at least one
advertising network; obtaining advertising rights to a plurality of
advertising opportunities; and using the rights to hedge a position
in a market for advertising transactions. The market may be a
futures market based on an index of advertising transactions. The
advertising bank may serve as a structural intermediary, offering a
number of services and offsetting the market making function that
would work as a natural complement to ad banking services. The
advertising bank may offer an array of products and services
including: short, middle and long term service packages
provisioning/brokering sale and purchase of advertising assets on
behalf of clients; long-term advertising index sales, enabling
clients to lock in sale or purchase terms; `underwriting` whereby
the bank funds a client's advertising budget in part or in whole
for a fee which may be a percentage of the overall ad spend amount;
fixed price warranted delivery of advertising assets under ad hoc
contract structures customized on behalf of clients; risk
management services such as advertising price and volume risk
management, creation of bespoke price hedging instruments (swaps,
options, insurance, hedges), and the like. The advertising bank may
offer the above services on the basis of a skilled analysis of
market data and trends and a superior ability to use the new family
of advertising securities and derivatives to make any hedge or
insurance profitable as a result of trading acumen.
[0113] The methods and systems of the various embodiments may
include a marketing and trading platform. Also, the methods and
systems may include trade capture and syndication.
[0114] An overview of the system and methods of the various
embodiments is illustrated in FIGS. 2A and 2B. Data on advertising
transactions can be obtained from a variety of data sources, such
as streaming advertising transaction data from an ad server or
advertising data source, step 200. Raw advertising transaction data
may be obtained from parties to advertising transactions as well as
services which monitor and report on advertising transactions. The
parties to advertising transactions from which raw data can be
received may include one or more of: advertisers; publishers; media
buyers; agents; networks; carriers; theaters and theater groups.
Services that may provide raw advertising transaction data may
include one or more of an advertising database service provider; an
advertising exchange; and an advertising market. Advertising
transaction raw data may be received and captured from a variety of
transmission mechanisms including manual and automatic sources.
Examples of advertising transaction data sources include any one or
more of: a data feed; a data scrape; a data syndication; a data
broadcast; a wireless transmission; a satellite transmission; a
printed transmission; an internet-protocol transmission; an
electronic mail transmission; an instant messenger transmission; a
telephone transmission; a fax; a report; a direct sales force; a
network agent; a reseller; a tiered reseller; a remnant exchange; a
primary exchange; a market; a spot market; a publisher; an
advertiser; a broker; an auction mechanism. One source for
receiving digital feeds of raw advertising data is the DART.RTM.
services offered by DoubleClick.com which is owned by Google Inc.
Further information regarding the DART.RTM. services is available
at www.doubleclick.com.
[0115] To capture advertising transaction data the sources of such
raw data may be subscribed to or accessed, such as via a computer
system accessing an appropriate Internet website and downloading
the data, step 200. In a preferred embodiment the sources of raw
advertising transaction data are selected so that the data is
received from multiple sides or parties to an advertising
transaction, including for example but not limited to the
advertiser, publisher, ad network, exchange, media buyer, and
advertising dashboard. In a preferred embodiment the advertising
transaction data sources are tapped consistently with a target of
rolling and refresh data daily and a minimum rate of weekly. In a
preferred embodiment data source will be tapped and the data
processed to provide end of day pricing, such as a calculation at
4:00 PM EST Monday through Friday, with intraday pricing with
dynamic refresh provided at 12:30 PM EST Monday thru Friday.
[0116] Referring to FIG. 2A, streaming advertising transaction data
may be received and processed by a variety of source-specific
preprocessing engines 202, 204, 206. For example, a source-specific
preprocessing engine within or coupled to a publisher or agency
billing and transaction system 202 may receive and process
advertising transaction data received from or stored within that
system. As another example, a source-specific preprocessing engine
within or coupled to a buy side optimization log system 204 may
receive and process advertising transaction data received from buy
side systems. As another example, a source-specific preprocessing
engine within or coupled to an advertiser server 206 may receive
and process advertising transaction data received from the ad
server. The source-specific preprocessing engines 202, 204, 206 may
be implemented in computer systems in a variety locations,
including within the system that are sources of transaction data,
in a cloud computing platform. Additionally or alternatively, a
source-specific preprocessing engine 206 may be implemented in a
stand alone computer configuration. The source-specific
preprocessing engines 202, 204, 206 can perform preliminary
processing of advertising transaction data such as to extract
selected transactions, remove duplicate records, convert file
formats, remove blank or incomplete records, etc. step 208.
Preprocessing may also include formatting transactions for multiple
advertisements into ad server line item records which are a single
entries recording the transaction and delivery circumstances
pertaining to single units of advertising. The overall database
structure may be composed of multiple lines, with a single line
typically dedicated to a single act of the ad server. Preprocessed
advertising transaction records may then be assigned a unique
record identifier (ID), step 210. The processed records may be
recorded in a relational database to provide a record and archive
of original transaction records, step 212.
[0117] Processed records may then be further processed to transform
individual data fields to identify and apply attribute values, step
214. As described more fully below with reference to FIGS. 3A and
3B, the process of transforming data fields may be accomplished by
applying identified attribute values to a series of look-up table
processes, step 218. The attribute values obtained from such
processing and table look-up steps may then be inserted into the
advertising transaction record, step 216. Alternatively, the
processed and transformed attribute values may be assembled into a
data record for the advertising transaction.
[0118] Referring to FIG. 2B, the processing of advertising
transaction records proceeds to provision and stage the transformed
transaction records, step 220. In this context "provisioned" means
that the raw transaction logs have been transformed to their new
state and "staged" means that the transformed records are standing
by, local to processing power, such that they may be recalled and
composed in a reference entity or composite price calculation in an
efficient manner. Such provisioned and staged records may be
recorded in a relational database to provide a record and archive
of processed transaction records, step 222. The provisioned and
staged records may also be aggregated to generate a variety of
information products such as benchmarks, indexes and reference
entities, step 224. Such aggregated information products may be
published to market participants in a variety of print, electronic
and on-line publishing mechanisms, step 226. Also, aggregated
information products may be recorded and archived in a relational
database, step 228.
[0119] In a preferred embodiment advertising transaction data
records are maintained in a relational database to provide a
minimum of six months of retrospective data along with forward
rolling transaction data for a minimum of six months into the
future (i.e., contracts for future advertising placement). Also in
a preferred embodiment the raw and transformed advertising
transaction data set are archived and maintained in a searchable
format for at least seven years from the data of benchmark pricing
in anticipation of meeting stringent financial market regulatory
requirements.
[0120] As advertising transaction records are received or captured
from various data streams, the transactions can be parsed and
analyzed to identify and extract characteristic information
regarding the transaction that can be useful for supporting an
advertising marketplace. Such characteristic information on
advertising transactions are referred to herein as "attributes" and
include such quantities as the advertising medium, the industry,
and the size and placement of the advertisement. In the various
embodiments, the attributes used to characterize, organize,
correlate (e.g., organize into or according to tiers) and otherwise
process advertising transaction data are selected from
characteristics that are common to most advertising deals. By
extracting the values or information associated with such
attributes a large number of advertising transactions can be
summarized into a compact data set. Such compact data sets,
referred to sometimes herein as a "transformed transaction record,"
fully reflects the nature and value of the underlying advertising
purchases and placements. Many of the attributes can be extracted
directly from advertising transaction data streams. In addition to
enabling advertising transactions to be summarized in a relational
database, such attributes can be used to sort and/or correlate the
data into a tiered structure that facilitates analyzing a database
of advertising transaction data. Such a tiered structure of
advertising attributes is referred to herein as a "taxonomy." The
taxonomy provides a tool for relating together large numbers of
advertising transactions that have some characteristic(s) in common
to identify trends, generate benchmarks and indexes, and support a
marketplace in advertising futures and securities.
[0121] The attributes that can be used to characterize and organize
advertising transactions in the taxonomy may include the following:
advertising medium; media platform; revenue model; media sales
channel; advertising product category; advertising product type;
advertising product dimension; advertising product placement;
publisher tier; publisher classification; advertiser transaction
tier; advertiser buy agent; advertiser industry; advertising
product context overlap tier; advertising product behavioral
targeting package; advertising product geographic targeting
package; advertising product demographic targeting package;
advertising product booking date; advertising product launch date;
advertising product gross transaction size; advertising product
transaction gross revenue; advertising product transaction net
revenue; advertising product effective unit revenue; time to
launch; geographic; location; proximity; time period; seasonal;
keyword; target customer; estimated viewer; estimated click
through; estimated purchase; estimated listener; duration; font;
font size; animation; motion; relative placement attribute. Each of
these attributes may be further broken out by values or further
attributes, examples of which are described below.
[0122] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising medium attribute. The
advertising medium attribute is the medium in which a particular
advertisement appears or is delivered. A wide variety of
advertising medium may be considered and included in the taxonomy.
Examples of advertising media include: a digital media; an analog
media; an internet-enabled media; a wireless media; a social media;
a satellite-based media; a print media; a broadcast media; a
networked media; a telephonic media; a telepathic media; a
brainwave media; a recorded media; a live media; an electronic
display media; an internet-enabled display media; an
internet-enabled rich media display media; an internet-enabled text
media; an internet-enabled video media; a social media; an
internet-enabled social media; a mobile display media; a mobile
text media; a mobile location based media; a mobile video media; an
mobile social media; an internet-enabled search media; a mobile
search media; a video search media; a video media; a broadband
video media; an internet protocol enabled broadband video media; a
closed circuit video media; a network served video media; a
satellite-based video media; an electronic game media; an
internet-enabled game media; a console game media; a downloadable
game media; massively-multiplayer game media; a public display
media; an outdoor advertising media; a radio media; an Internet
Protocol radio media; a satellite-broadcast radio media; a
newspaper media; a magazine media; a classified print media; a
television media; a broadcast television media; a spot television
media; a cable television media; a digitally recorded television
media; a Internet Protocol Television (IPTV) broadcast media; a
direct marketing media; a telemarketing media; and a product
placement medium.
[0123] The standard attributes of advertising transactions used in
the taxonomy may also include a media platform attribute. This
attribute describes the platform that supports or presents the
particular advertisement. Examples of media platform attributes
include: an internet-enabled electronic display; an electronic
display; an internet-enabled display; an internet-enabled rich
media display; an internet-enabled text; an internet-enabled video;
a social; an internet-enabled social; a mobile display; a mobile
text; a mobile location-based; a mobile video; a mobile audio; a
mobile social; an internet-enabled search; a mobile search; a video
search; a text search; an image search; an audio search; a video; a
broadband video; an Internet-Protocol enabled broadband video; a
closed-circuit video; a network-served video; a satellite-based
video; an electronic game; an internet-enabled game; a console
game; a downloadable game; a massively-multiplayer game; a public
display; an indoor electronic public display; an outdoor electronic
public display; an in-vehicle network served public display; an
in-building network served public display; an in-flight network
served public display; an outdoor advertising; an outdoor
advertising; an outdoor advertising; a radio; an Internet Protocol
radio; a satellite-broadcast radio; a newspaper; a magazine; is a
classified print; a television; a broadcast television; a spot
television; a cable television; a digitally recorded television; an
Internet Protocol Television (IPTV) broadcast; a direct marketing;
a telemarketing; a media insert product placement; an in-stream
product placement; and an on-product placement platform.
[0124] The standard attributes of advertising transactions used in
the taxonomy may also include a revenue model attribute. The
revenue model attribute defines the method or computation by which
the advertising product is priced. Examples of revenue model
attributes include: a unit-based revenue; and a point-based revenue
model. The revenue model attribute may also may include the type of
revenue per advertisement model involved in the transaction.
Examples of types of revenue per advertisement attributes include:
Cost Per Mille Impression; Cost Per Play Cost Per Spot; Cost Per
Piece; Cost Per Unit Mailed; audience-based revenue; Cost Per
Audience Member; Cost Per Gross Rating Point (GRP);
performance-based revenue; Cost Per Click (CPC); Cost Per Action
(CPA); auction-based revenue; keyword-bid revenue; session-bid
revenue; job-bid revenue; time-based revenue; Cost Per Session
(CPS); Cost Per Period; Cost Per Second; Cost Per Minute; Cost Per
Hour; Cost Per Day Cost Per Week; Cost Per Month; size-based
revenue; Cost Per Column Inch; Cost Per Square Foot; shared
revenue; an affiliate revenue; and hybrid revenue. Revenue model
attributes may be expressed (i.e., the value transformed into) in
terms of correlated values, such as CPM advertising transactions
being assigned a revenue model value of "1" while CPC advertising
transactions being assigned a revenue model value of "2". Further
examples of revenue model value assignments are listed below in
Table 9.
[0125] Additionally, the revenue model attribute may include the
revenue transaction size (i.e., the value of the advertising
transaction). For example, the revenue transaction size attributes
may include: dollar-based revenue; euro-based revenue; yen-based
revenue; rupee-based revenue; renminbi-based revenue; yuan-based
revenue model-based revenue; pound-based revenue-based revenue;
real-based revenue; pound-based revenue-based revenue; franc-based
revenue; ruble-based revenue; peso-based revenue; rupiah-based
revenue; dinar-based revenue; shekel-based revenue; ringgit-based
revenue; rand-based revenue; won-based revenue; shilling-based
revenue; dirham-based revenue; gold-based revenue; platinum-based
revenue; silver-based revenue; and palladium-based revenue.
[0126] The standard attributes of advertising transactions used in
the taxonomy may also include a media sales channel attribute.
Advertisements may be sold through a wide variety of sales
channels. The media sales channel attribute defines the channel by
which the advertising product is sold. Examples of media sales
channel attributes include: a direct sales force; an electronic
display publisher direct sales force; a mobile publisher direct
sales force; a mobile carrier direct sales force; a social
publisher direct sales force; a search publisher direct sales
force; a video publisher direct sales force; a game publisher
direct sales force; a game producer direct sales force; a public
display publisher direct sales force; an outdoor publisher direct
sales force; a print publisher direct sales force; a radio
publisher direct sales force; a television publisher direct sales
force; a direct marketing publisher direct sales force; a
telemarketing publisher direct sales force; a product placement
publisher direct sales force; a contracted network agent; a
contracted electronic display network agent; a contracted mobile
network agent; a contracted social network agent; a contracted
search network agent; a contracted video network agent; a
contracted game network agent; a contracted public display network
agent; a contracted outdoor network agent; a contracted print
network agent; a contracted radio network agent; a contracted
television network agent; a contracted direct marketing network
agent; a contracted telemarketing network agent; a contracted
product placement network agent; a tiered advertising reseller; a
tiered electronic advertising reseller; a tiered mobile advertising
reseller; a tiered social advertising reseller; a tiered search
advertising reseller; a tiered game advertising reseller; a tiered
public display advertising reseller; a tiered outdoor advertising
reseller; a tiered print advertising reseller; a tiered radio
advertising reseller; a tiered television advertising reseller; a
tiered direct marketing advertising reseller; tiered telemarketing
advertising reseller; a tiered product placement advertising
reseller; a remnant market; an electronic display remnant market; a
mobile publisher remnant market; a mobile carrier remnant market; a
social remnant market; a search remnant market; a video remnant
market; a game publisher remnant market; a game producer remnant
market; a public display remnant market; an outdoor remnant market;
a print remnant market; a radio remnant market; a television
remnant market; a direct marketing remnant market; a telemarketing
remnant market; a product placement remnant market; an electronic
market; an electronic display market; an electronic mobile
publisher market; an electronic mobile carrier market; an
electronic social market; an electronic search market; an
electronic video market; an electronic game publisher market; an
electronic game producer publisher; an electronic public display
market; an electronic outdoor market; an electronic print market;
an electronic radio market; an electronic television market; an
electronic direct marketing market; an electronic telemarketing
market; an electronic product placement market; a exchange market;
a exchange electronic display market; a exchange mobile publisher
market; a exchange mobile carrier market; a exchange social market;
a exchange search market; a exchange video market; a exchange game
publisher market; a exchange game producer publisher; a exchange
public display market; a exchange outdoor market; a exchange print
market; a exchange radio market; a exchange television market; a
exchange direct marketing market; a exchange telemarketing market;
a exchange product placement market; a spot market; a spot
electronic display market; a spot mobile publisher market; a spot
mobile carrier market; a spot social market; a spot search market;
a spot video market; a spot game publisher market; a spot game
producer publisher; a spot public display market; a spot outdoor
market; a spot print market; a spot radio market; a spot television
market; a spot direct marketing market; a spot telemarketing
market; a spot product placement market; an auction; an auction
electronic display market; an auction mobile publisher market; an
auction mobile carrier market; an auction social market; an auction
search market; an auction video market; an auction game publisher
market; an auction game producer publisher; an auction public
display market; an auction outdoor market; an auction print market;
an auction radio market; an auction television market; an auction
direct marketing market; an auction telemarketing market; an
auction product placement market; a brokered market; a brokered
electronic display market; a brokered mobile publisher market; a
brokered mobile carrier market; a brokered social market; a
brokered search market; a brokered video market; a brokered game
publisher market; a brokered game producer publisher; a brokered
public display market; a brokered outdoor market; a brokered print
market; a brokered radio market; a brokered television market; a
brokered direct marketing market; a brokered telemarketing market;
a brokered product placement market channel. The sales channel
attribute identified in an advertising transaction record may be
transformed into a tier number for ranking and organizing according
to the taxonomy. For example, an advertising transaction sold by a
direct sales force may be assigned the sales channel attribute
value "1" while an advertising transaction sold by a contracted
network agent may be assigned the sales channel attribute value
"2."
[0127] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product category
attribute. This attribute defines how the advertising product is
delivered, such as within the page content, above/below the page
content or over the page content (e.g., via a pop-up or pop-under
mechanism). This attribute may categorize the advertising product
in a variety of ways. Examples of advertising product categories
include; in-page electronic display product; between-page
electronic display product; over-page electronic display product;
streaming electronic video product; streaming broadband video
product; streaming satellite video product; location-triggered
mobile product; mobile downloadable executable product; immersive
game product; around-game product; in-game product category;
projected; terminal-based; vehicle-based; national broadcast
product; regional broadcast product; local broadcast product; cable
broadcast product; digital video recorded broadcast product; mailed
insert; print product; printed promotion; interactive voice
response (IVR) product; on-product. The product category attribute
identified in an advertising transaction record may be transformed
into a tier number for ranking and organizing according to the
taxonomy. For example, an in-page advertisement may be assigned the
product category attribute value "1" while an off-page
advertisement may be assigned the product category attribute value
"2."
[0128] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product type
attribute. Advertising product types describe the format, form
factor and/or applicable media of the advertisement. Examples of
advertising product types include: HTML rectangle; HTML banner;
HTML skyscraper; HTML button; HTML slide; HTML pop-up; HTML
pop-under; rich media rectangle; rich media banner; rich media
skyscraper; rich media button; rich media slide; rich media pop-up;
rich media pop-under; video rectangle; video banner; video
skyscraper; video button; video slide; video pop-up; video
pop-under; search keyword; search key image; search key audio clip;
search key video clip; mobile graphical display (WAP/HTML) banner;
mobile text; mobile video; multimedia message service (MMS); short
messaging service (SMS); in-stream; pre-stream; post-stream;
overlay; standalone video player; immersive; console; downloadable;
advergame; around-game; game-skinning; dynamic in-game type; static
in-game; game-skinning; inter-level game; post-game; pre-game;
in-game product placement; game sponsorship; 10-second spot;
30-second spot; 45-second spot; 60-second spot; Double Page; Full
Page; Half Page Horizontal; Half Page Vertical; Quarter Page;
Display Bannered; Full Centerspread; Mini Centerspread; 3/5 Page
Vertical; 1/2 Page Horizontal; 9/20 page; 2/5 Page Vertical; 3/10
Page Vertical; 3/10 Page Horizontal; 1/5 page vertical; 1/5 page
horizontal; 3/20 page; 1/10 page vertical; 1/10 page horizontal;
1/20 page; two-page; single page; 2/3 page vertical; 1/3 page
vertical; 1/2 page horizontal; 1/2 page vertical; 1/3 page square;
1/2 page horizontal; 1/6 page horizontal; 1/6 page square; 1/4
page; 1/8 page; public billboard; public sandwichboard; public
placard; vehicle-borne; mailed insert page; product package;
printed decal; product wrapper; and tattoo type products. The
product type attribute identified in an advertising transaction
record may be transformed into a tier number for ranking and
organizing according to the taxonomy. For example, a rectangle
(HTML/Rich Media) Internet advertisement may be assigned the
product type attribute value "1" while a banner (HTML/Rich Media)
Internet advertisement may be assigned the product type attribute
value "2."
[0129] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product dimension
attribute. The advertising product dimension attribute defines the
Interactive Measurement Unit (IMU), standardized pixel dimension,
inch, square footage or other size measurement of the advertising
product. The advertising product dimension attribute may also
reflect the play duration and/or the run duration of the
advertisement. Examples of dimensional attributes that may be
implemented in the taxonomy include: a year; a month; a week; a
day; a hour; a minute; a second; an Interactive Measurement Unit
(IMU); a level; a screen; a column; a pixel; a page; a word; a
mile; a kilometer; an acre; a field; a yard; a foot; a meter; a
square mile; a square kilometer; a square yard; a square foot; a
square meter; a square inch; a square centimeter; a square
millimeter; a cubic mile; a cubic kilometer; a cubic yard; a cubic
foot; a cubic meter; a cubic inch; a cubic centimeter; a cubic
millimeter; a byte; a decibel; a click; a refresh; a load; a
command; an execute dimension. The product dimension attribute
identified in an advertising transaction record may be transformed
into a tier number for ranking and organizing according to the
taxonomy. For example, a leaderboard (Universal Ad Package)
advertisement may be assigned the product dimension attribute value
"1" while a wide skyscraper (UAP) advertisement may be assigned the
product dimension attribute value "2."
[0130] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product placement
attribute. The advertising product placement attribute determines
the level of the site hierarchy to which the advertising product is
slotted to be delivered. Examples of advertising product placement
attributes that may be used in the taxonomy include: network;
run-of-network; site; run-of-site; page group; page; run-of-page;
page area; front page; back page; internal page; op-ed page;
editorial page; scattered; publisher's-choice; margin; quadrant;
segment; above-the-fold; below-the-fold; mid-show; pre-show;
post-show; pre-roll; post-roll; standalone; pre-game; post-game;
inter-game level; overlay level; floating; sponsorship;
share-of-voice; proportional; allocation; blocking; context; genre;
broadcast; carrier; geographic; handset; time of day; day of week;
week of month; week of year; and month of year placement. The
product placement attribute identified in an advertising
transaction record may be transformed into a tier number for
ranking and organizing according to the taxonomy. For example, an
advertisement slotted to be delivered at the network level may be
assigned the product placement attribute value "1" while an
advertisement slotted to be delivered at the page level of a site
may be assigned the product placement attribute value "2." In this
context, the level of site hierarchy indicates how far down (in
"page level") or how high up ("run of network") that an advertising
product will be placed. High in the hierarchy is less specific and
typically less expensive advertising since the computer servers can
find a vacant slot and fill it with available advertising
inventory.
[0131] The standard attributes of advertising transactions used in
the taxonomy may also include a publisher tier attribute. Examples
of publisher tier attributes that may be used in the taxonomy
include: circulation; unique visitors; visitors; log-ins; viewers;
users; players; audience; consumption; pricing leverage; pricing
premium; buyers; subscribers; subscriber tenure; audience tenure;
audience engagement; audience loyalty; reach; signal strength;
network breadth; membership; and affiliate.
[0132] The standard attributes of advertising transactions used in
the taxonomy may also include domain traffic attribute,
particularly for Internet advertising transactions. The domain
traffic attributes indicates via third-party traffic and audience
measurement mechanisms (e.g., Quantcast.com and The Nielsen
Company) the scale and prominence of the domain name (i.e.,
Internet URL) to which the advertising product is slotted to be
served via measurement of monthly unique visitors to that domain
name. Once a particular transaction has been transformed and tiered
via domain traffic and subject matter classifications, the precise
reference domain may not be recorded in the data warehouse. Instead
a reference or tier number may be assigned to the transaction as
the sole mechanism by which the transaction may be traced back to
its source domain. For example, an advertising transaction for an
ad appearing in a website with a domain monthly unique visitor
volume (i.e., number of hits on the domain name) of >20 million
unique visitors per month (mm) may be assigned the attribute value
"1" while an advertising transaction for an ad appearing in a
website with a domain monthly unique visitor value of 10 million to
20 million unique visitors per month (10 mm-20 mm) may be assigned
the sales channel attribute value "2." An extension of this method
can be made to print media based on circulation data, to broadcast
media based on average viewership, and to radio media based on
average number of listeners.
[0133] The standard attributes of advertising transactions used in
the taxonomy may also include a publisher classification attribute
(also referred to herein as the "publisher domain classification"
in which reference "domain" refers to the subject matter addressed
by the publisher rather than a URL). The publisher classification
attribute indicates the subject matter of the content of the media
or publication targeted for the advertising product delivery. For
example, the publisher classification attribute may be a content
type classification, examples of which include: News and
Information; Financial; Entertainment; Sports; Computers &
Technology; Social Media; and Other. Other examples of publisher
classification attributes include: industry type; format; media;
subscription model; sector; subject matter; technology standards;
industry standard; business model; geographic; economic; and
transmission standards. The publisher classification attribute
identified in an advertising transaction record may be transformed
into a tier number for ranking and organizing according to the
taxonomy. For example, an advertisement that will appear in a news
and information content medium may be assigned the publisher
classification attribute value "1" while an advertisement appearing
in a financial content medium may be assigned the publisher
classification attribute value "2."
[0134] The standard attributes of advertising transactions used in
the taxonomy may also include an advertiser transaction tier
attribute. The advertiser transaction tier attribute indicates the
size of the advertiser account measured in terms of a gross
bookings relationship between advertiser and publisher (e.g.,
advertiser gross bookings as a percentage of total bookings for a
given delivery date.) Examples of advertiser tiers include: gross
bookings; percentage share; share of voice; relative strength;
relative bookings; duration of tenure; contract; premium; discount;
exclusive; and non-exclusive. The advertiser transaction tier
attribute identified in an advertising transaction record may be
transformed into a tier number for ranking and organizing according
to the taxonomy. For example, an advertising transaction in which
the advertiser's transaction share exceeds ten percent may be
assigned the advertiser transaction tier attribute value "1" while
an advertising transaction in which the advertiser's transaction
share is between five and ten percent may be assigned the
advertiser transaction tier attribute value "2."
[0135] The standard attributes of advertising transactions used in
the taxonomy may also include an advertiser buy agent attribute.
The advertiser buy agent attribute indicates the purchasing channel
for the advertising product. Examples of advertiser buy agent
attributes include: an advertiser marketing department; an
authorized proxy; an advertiser buy desk; an agency buy desk; an
automated offer matching function; an automated remnant fill
channel; an automatic network; an electronic communications
network; a wireless agent; a prescreened filter agent. The
advertiser buy agent attribute identified in an advertising
transaction record may be transformed into a tier number for
ranking and organizing according to the taxonomy. For example, an
advertising transaction purchased through an advertiser buy desk
may be assigned the advertiser buy agent attribute value "1" while
an advertising transaction purchased through an agency buy desk may
be assigned the advertiser buy agent attribute value "2."
[0136] The standard attributes of advertising transactions used in
the taxonomy may also include an advertiser industry attribute. The
advertiser industry attribute indicates the industry addressed by
the advertising product. Examples of advertiser industry attributes
include: automotive; consumer products; financial services; media
and entertainment; telecommunications; computers and technology;
travel; and other industries. The sales channel attribute
identified in an advertising transaction record may be transformed
into a tier number for ranking and organizing according to the
taxonomy. For example, an advertising transaction for an
advertisement addressing the automotive industry may be assigned
the advertiser industry attribute value "1" while an advertising
transaction for an advertisement addressing the consumer industry
may be assigned the advertiser industry attribute value "2."
[0137] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product context
overlap tier attribute. The product context overlap attribute
reflects a relative measure of the degree to which an advertisement
in a particular media may have cross over application to other
industries. For example, an advertisement placed in a medium
addressed to the auto industry (e.g., an advertisement placement in
Automotive News magazine or website) has a high correlation in
terms of subject matter and targeted audience to the financial and
sports industry tiers, and thus may be rated with an overlap tier
of "1" For those industries In this example, if an advertiser is
aiming to reach consumers interested in financial or sports
matters, many of those targeted consumers may also be reached by
advertising in auto industry media. In contrast, there is low
context overlap between the auto industry and the entertainment and
the computers & technology industries, so an ad placed in an
auto industry medium will reach relatively few consumers who are
interested in or read/watch entertainment or computers &
technology related media. For example, magazines dedicated to cars
and the automotive industry typically include advertisements
related to financial services, while magazines dedicated to
business and financial news typically include advertisements
related to automobiles. This is because advertisers know that the
readership of automotive magazines include target audiences of
financial service advertisers, and the readership of business
magazines include target audiences of automotive advertisers. The
context overlap are defined for the purposes of the various
embodiments to reflect the degree to which different advertising
media and targeted audiences provide relevance to or presentation
to other industry or consumer target groups.
[0138] The degree to which there is overlap may be classified into
tiers, such as "tier one," "tier two," and "tier three" to reflect
relative context overlap, with tier one corresponding to
industry/interest groups with a high degree of context overlap and
tier three corresponding to industry/interest groups with a low
degree of context overlap.
[0139] Examples of "High Context Overlap" or "tier one;" product
context overlap include: an Automotive advertiser industry
contextualized with Finance publisher content; an Automotive
advertiser industry contextualized with a Sports publisher; a
Consumer advertiser industry contextualized with Entertainment
publisher content; a Consumer advertiser industry contextualized
with Social Media publisher content; a Financial advertiser
industry contextualized with News and Information publisher
content; a Financial advertiser industry contextualized with
Financial publisher content; a Financial advertiser industry
contextualized with Computers and Technology publisher content; a
Media and Entertainment advertiser industry contextualized with
Entertainment publisher content; a Media and Entertainment
advertiser industry contextualized with Social Media publisher
content; a Telecommunications advertiser industry contextualized
with Financial publisher content; a Telecommunications advertiser
industry contextualized with a Computers and Technology publisher
content; a Computers and Technology advertiser industry
contextualized with Financial publisher content; a Computers and
Technology advertiser industry contextualized with Computers and
Technology publisher content; a Travel advertiser industry
contextualized with News and Information publisher content; and a
Travel advertiser industry contextualized with Financial
publisher.
[0140] Examples of Moderate Context Overlap, which may be
designated as "Tier Two" within the taxonomy, include: an
Automotive advertiser industry contextualized with News and
Information publisher content; an Automotive advertiser industry
contextualized with Social Media publisher content; a Consumer
advertiser industry contextualized with News and Information
publisher content; a Consumer advertiser industry contextualized
with Sports publisher content; a Consumer advertiser industry
contextualized with Computers and Technology publisher content; a
Financial advertiser industry contextualized with Sports publisher
content; an Media and Entertainment advertiser industry
contextualized with News and Information publisher; a Media and
Entertainment advertiser industry contextualized with Sports
publisher content; a Media and Entertainment advertiser industry
contextualized with Computers and Technology publisher content; a
Telecom advertiser industry contextualized with News and
Information publisher content; a Telecom advertiser industry
contextualized with Social Media publisher content; a Computers and
Technology advertiser industry contextualized with News and
Information publisher content; a Computers and Technology
advertiser industry contextualized with an Entertainment publisher
content; a Computers and Technology advertiser industry
contextualized with Sports publisher content; a Computers and
Technology advertiser industry contextualized with Social Media
publisher content.
[0141] Examples of Low Context Overlap, which may be designated as
"tier three" include: an Automotive advertiser industry
contextualized with Entertainment publisher content; an Automotive
advertiser industry contextualized with Computers and Technology
publisher content; a Consumer advertiser industry contextualized
with Financial publisher content; a Financial advertiser industry
contextualized with Entertainment publisher content; a Financial
advertiser industry contextualized with Social Media publisher
content; a Media and Entertainment advertiser industry
contextualized with Financial publisher content; a Telecom
advertiser industry contextualized with Entertainment publisher
content; a Telecom advertiser industry contextualized with Sports
publisher content; a Travel advertiser industry contextualized with
Entertainment publisher content; a Travel advertiser industry
contextualized with Sports publisher content; a Travel advertiser
industry contextualized with Computers and Technology publisher
content; and a Travel advertiser industry contextualized with
Social Media publisher content.
[0142] Advertising transactions which have very little or Zero
Context Overlap, meaning that the advertisement category has very
little relationship to or target audience overlap with a content
classification, may be categorized as "tier four."
[0143] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product behavioral
targeting package attribute. This attribute reflects the degree to
which the advertising product is packaged or presented so as to
target consumers exhibiting particular behaviors, such as clicking
on a particular Internet advertisement or purchasing a particular
product. This attribute can be useful for tracking advertising
transactions that are targeted to particular consumer purchasing
patterns or media access patterns. Examples of advertising product
behavioral targeting package attributes include: previous site
visit targeting; previous viewer targeting; previous visitor
targeting; previous reader targeting; previous listener targeting;
previous traveler targeting; previous dialer targeting; previous
purchaser targeting; previous diner targeting; previous searcher
targeting; previous respondent targeting; previous non-respondent
targeting; keyword targeting; cookie targeting; device targeting;
network targeting; connection speed targeting; satellite dish
targeting; screen targeting; runtime duration targeting; on-time
duration targeting; off-time duration targeting; referent site
targeting; referent search targeting; referent viewing targeting;
referent visit targeting; referent click targeting; referent action
targeting; referent purchase targeting; referent call targeting;
referent trip targeting; referent location targeting; late payment
targeting; re-payment targeting; non-payment targeting; pre-payment
targeting; under-payment targeting; cancellation targeting; renewal
targeting; expression of interest targeting; filing of paperwork
targeting; raising of flag targeting; self-reported targeting;
user-reported targeting; system-reported targeting; retarget
targeting; multi-attribute targeting; voting record targeting; and
tax filing status targeting. The product behavioral targeting
package attribute identified in an advertising transaction record
may be transformed into a tier number for ranking and organizing
according to the taxonomy. For example, an advertising transaction
that includes no behavior targeting may be assigned the product
behavioral targeting package attribute value "0" while an
advertising transaction that includes a previous site visit product
behavioral targeting package may be assigned the product behavioral
targeting package attribute value "1."
[0144] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product geographic
targeting package attribute. This attribute reflects the particular
geographic region to which an advertisement is targeted or
delivered. For example, an ad in a local newspaper will target the
city of its circulation while an ad in a nationwide publication
will target the entire United States (assuming the ad is not
limited to magazines distributed in particular regions). The Direct
Marketing Association (DMA) trade group has defined world wide
standardized regions that may be used to define the geographic
attribute. In the art of advertising the term DMA is often referred
to as shorthand for the standardized zones themselves. Examples of
advertising product geographic targeting package attribute values
include: DMA (Direct Marketing Associate region) targeting; state
targeting; province targeting; canton targeting; municipality
targeting; county targeting; city targeting; township targeting;
town targeting; postal code or `zip code` targeting; street
targeting; street number targeting; street corner targeting;
roadway targeting; highway targeting; expressway targeting; edifice
targeting; GPS coordinate targeting; longitude/latitude coordinate
targeting; time zone coordinate targeting; sea targeting; airport
targeting; and building floor targeting. The geographic targeting
attribute identified in an advertising transaction record may be
transformed into a tier number for ranking and organizing according
to the taxonomy. For example, an advertising transaction that
includes no geographic targeting may be assigned the geographic
targeting attribute value "0" while an advertising transaction that
includes country level geographic targeting may be assigned the
geographic targeting attribute value "1."
[0145] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product demographic
targeting package attribute. This attribute reflects the degree to
which an advertisement is presented or packaged so as to reach or
be directed to a particular demographic segment. Examples of
advertising product demographic targeting packages include: age
range targeting; exact numerical age targeting; gender targeting;
income targeting; hybrid gender and age targeting; hybrid gender
and income targeting; hybrid age and income targeting; hybrid
gender, age and income targeting. Demographic targeting attributes
may also address combinations of age, gender and income. The
demographic targeting attribute identified in an advertising
transaction record may be transformed into a tier number for
ranking and organizing according to the taxonomy. For example, an
advertising transaction sold with no demographic targeting may be
assigned the demographic targeting attribute value "0" while an
advertising transaction sold with demographic targeting aimed at
men ages 18-35 with annual incomes of less than $25,000 may be
assigned the demographic targeting attribute value "1." Further
examples of demographic targeting attribute values are provided in
Table 4 below.
[0146] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product booking date
attribute. The advertising product booking date attribute indicates
the date upon which the advertising transaction is booked in the
seller's or seller's agent's booking system and entered into the
publisher's order management queue. Examples of advertising product
booking date attribute values include: a day booking date; a week
booking date; a month booking date; a year booking date; an hour
booking date; a minute booking date; a second booking date. The
booking date attribute identified in an advertising transaction
record may be transformed into and recorded in a standardized date
format.
[0147] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product launch date
attribute. This attribute indicates the date upon which the
advertising product commences delivery. Depending on lead time,
this date may be up to a year after the booking date, or may be
identical with booking date. Examples of advertising product launch
date attribute values include: a day launch date; a week launch
date; a month launch date; a year launch date; an hour launch date;
a minute launch date; a second launch date. The launch date
attribute identified in an advertising transaction record may be
transformed into and recorded in a standardized date format.
[0148] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product gross
transaction size attribute. This attribute indicates the gross
impression volumes purchased for a specific advertising transaction
for a specific campaign launch. Examples of gross transaction size
values include: a dollar quantity; a euro quantity; a yen quantity;
a rupee quantity; a renminbi quantity; a yuan quantity; a pound
quantity; a real quantity; a pound quantity; a franc quantity; a
ruble quantity; a peso quantity; a rupiah quantity; a dinar
quantity; a shekel quantity; a ringgit quantity; a rand quantity; a
won quantity; a shilling quantity; a dirham quantity; a gold
quantity; a platinum quantity; a silver quantity; a palladium
quantity; a point; a unit attribute; a minute quantity; a day
quantity; an hour quantity; a week quantity; a month quantity; an
impression quantity; a brainwave imprint quantity; a brainwave scan
quantity; a play quantity; a spot quantity; a click quantity; a
action quantity; a view quantity; a stream quantity; a listen
quantity; a recording quantity; a download quantity; a piece
quantity; a copy quantity; an issue quantity; an audience member
quantity; a gross rating point quantity; a location quantity; a
sign quantity; a session quantity; a unit quantity; a game
quantity; a keyword quantity; a bid quantity; an inch quantity; a
foot quantity; a meter quantity; a yard quantity; a square inch
quantity; a square foot quantity; a square meter quantity; a square
yard quantity size. The gross transaction size attribute identified
in an advertising transaction record may be transformed into a tier
number for ranking and organizing according to the taxonomy. This
tiering may be accomplished dynamically by the system based on the
transaction set under consideration. For example, a system computer
may analyze a set of transactions and rank them from largest to
smallest on the basis of specified attributes such as dollar
amount, minutes purchased, clicks purchased, etc.
[0149] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product transaction
gross revenue attribute. This attribute reflects the gross revenue
of the advertisement involved in the advertising transaction.
Examples of the units in which gross revenue attribute values may
be expressed include: dollar; euro; yen; rupee; renminbi; yuan;
pound; real; pound; franc; ruble; peso; rupiah; dinar; shekel;
ringgit; rand; won; shilling; dirham; gold; platinum; silver;
palladium; point; and unit.
[0150] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product transaction
net revenue attribute. This attribute reflects the net revenue of
the advertisement involved in the advertising transaction. Examples
of the units in which net revenue attribute values may be expressed
include: dollar; euro; yen; rupee; renminbi; yuan; pound; real;
pound; franc; ruble; peso; rupiah; dinar; shekel; ringgit; rand;
won; shilling; dirham; gold; platinum; silver; palladium; point;
and unit.
[0151] The standard attributes of advertising transactions used in
the taxonomy may also include an advertising product effective unit
revenue attribute. This attribute reflects the effective unit
revenue of the advertisement involved in the advertising
transaction. Examples of the units in which effective unit revenue
attribute values may be expressed include: dollar; euro; yen;
rupee; renminbi; yuan; pound; real; pound; franc; ruble; peso;
rupiah; dinar; shekel; ringgit; rand; won; shilling; dirham; gold;
platinum; silver; palladium; point; and unit.
[0152] The standard attributes of advertising transactions used in
the taxonomy may further include any one or all of the following: a
time-to-launch attribute; a geographic attribute; a location
attribute; a proximity attribute; a time period attribute; a
seasonal attribute; a keyword attribute; a target customer
attribute; an estimated viewer attribute; an estimated
click-through attribute; an estimated purchase attribute; an
estimated listener attribute; a duration attribute; a font
attribute; a font size attribute; an animation attribute; a motion
attribute; and a relative placement attribute.
[0153] Each advertising transaction received by a computerized
advertising futures market system can be parsed and analyzed to
recognize the values or parameters associated with a taxonomy based
upon some or all of the foregoing attributes. In such a system, a
processor can be configured with software to look for the
attributes specified in the taxonomy, extract the value of any
recognized attributes, in some cases transform the attribute value
into another value or tier specified in the taxonomy, and record
the extracted and/or transformed attribute values in a transaction
record. By automatically capturing advertising transactions from a
data stream of advertising transaction summaries and generating a
database of transaction records, the system can generate a
historical and current database that can be mined and exploited for
a variety of advertising related applications including the
embodiments described below.
[0154] The foregoing attributes may be organized or grouped for
analysis and display according to a structured organization, i.e.,
the taxonomy. This taxonomy can be general in structure so as to
accommodate any type of advertising transaction and any
investigation of particular types of advertising markets, products
and characteristics. At a top level, the taxonomy may be organized
by advertising market and media (or platform), as well as other top
level attribute categories. Then within each attribute category
further subcategories of attributes may be organized to further
characterize a particular advertising transaction. As an example, a
taxonomy may include Advertising Medium as a high level attribute,
which may include print, radio, television, electronic media, etc.
If electronic media is selected within this top level taxonomy, the
taxonomy may include the attribute categories and organization
shown in example Table 1 below.
TABLE-US-00001 TABLE 1 Electronic Display Advertising Taxonomy
Structure 1. Product Data a. Product Revenue Model (e.g., CPA, CPM)
b. Sales Channel (e.g., Direct Sales Force, Network, Agency,
Exchange) c. Product Category (e.g., Electronic Display: In-Page,
Off-Page) d. Product Type (e.g., Rectangle, Banner; HTML, Rich
Media, Video) e. Product Dimension (e.g., IMU dimensions for
Electronic Display f. Product Placement Level (e.g., Network, Site,
Page, Location) 2. Publisher Data a. Publisher Domain Traffic Tier
(e.g., Unique Visitor Count Tier) b. Publisher Domain
Classification (e.g., Subject Matter Classification) 3. Advertiser
Transformation a. Advertiser Transaction Tier (e.g., Tier I through
IV based on volume segmentation) b. Advertiser Buyer Channel c.
Advertiser Industry 4. Targeting Transformation a. Context Overlap
Tier b. Behavioral Targeting Package c. Geographic Targeting
Package d. Demographic Targeting Segment 5. Flight Transformation
a. Booking Date b. Launch Date c. Gross Transaction Size 6. Revenue
Transformation a. Transaction Gross Revenue b. Transaction Net
Revenue c. Effective cost per mille impressions or Effective cost
per action (e.g., Net Revenue/Total Impressions or Total
Actions)
[0155] Raw advertising transaction data that is captured from
various sources is parsed and analyzed to identify whether the
taxonomy attributes are present in each transaction, and if so, the
individual elements are extracted and/or transformed into values to
enable each transaction line to be ranked within the tiered
structure of the taxonomy across the entire attribute range. As a
result the advertising transactions can be categorized or clustered
according to selected attributes for purposes of benchmarking and
indexing. Advertising transaction records can be transformed in a
table look-up process utilizing transformation tables with
corresponding table values (i.e., the values obtained from the
look-up process) being included in the transformed advertising
transaction record. The resulting transformed data records then can
be stored in a relational database accessible for data pulls and
subsequent aggregation, such as to generate a reference entity,
index or benchmark.
[0156] The capture, extraction, transformation and recordation of
advertising transactions may be understood by reference to an
example that is illustrated in FIGS. 3A, 3B and described below. A
computer system can capture an advertising transaction from a data
stream, step 300. The captured advertising transaction record can
then be processed to identify and assign attribute values and
prepare a transaction data record for storage. The computer system
may assign a unique transaction ID to the transaction record, step
302. The source of the advertising transaction data may also be
recorded, step 304. In an embodiment, the data source may be
identified by an ID value rather than a name. For example, the
source of the data may be used in a table look-up process to obtain
a record source ID from a data table such as the example
illustrated in Table 2. In this example, if the advertising
transaction record was received from an ad server log, the source
ID "2" would be stored in the corresponding field in the
transaction record.
TABLE-US-00002 TABLE 2 Record Source Rec. Source Rec. Source ID
Accounting/Billing System ACCOUNTING 1 Ad Server Log SERVER_LOG 2
Buyside/Sellside Dashboard DASHBOARD 3 Reporting DB REPORTS_DB
4
[0157] The impression date for the transaction may also be
recorded, step 306. This may be accomplished by transforming the
native impression date (i.e., the date that the purchased
advertisement is to make an impression on consumers) for the
transaction into a standard format, such as MM_DD_YYYY. Similarly,
the impression time associated with the advertising transaction may
be transformed into a standard time format, such as Greenwich Mean
Time (GMT), step 308. The time block (e.g., morning, day or night)
of the purchased may also be determined and recorded, step 310. In
an embodiment, this may be accomplished by using the impression
time as a look-up quantity in a table look-up process to obtain an
impression time block ID using a data table such as the example
illustrated in Table 3.
TABLE-US-00003 TABLE 3 Impression Time Impression Local Hour Block
IMP_BLOCK_ID 6:00:00 AM to 7:59:00 AM Morning Block 2 8:00:00 AM to
10:59:00 PM Prime Block 1 11:00:00 PM to 6:00:00 AM Night Block
3
[0158] The advertising transaction is parsed and analyzed to
identify any demographic targeting specified in the transaction,
with the identified attribute values (if any) used to determine a
demographic targeting attribute ID, step 312. In an embodiment, the
demographic targeting attribute ID may be determined by using the
demographic targeting information in the advertising transaction as
look-up quantities in a table look-up process to obtain an ID using
a data table such as the example illustrated in Table 4. For
example, if the purchased advertisement is targeted at women age
35-45 with an annual income greater than $75,000, the table look-up
process using Table 4 would determine that the demographic target
attribute ID should be "2."
TABLE-US-00004 TABLE 4 Demographic Target ID None Specified
<$25k $25-50k $50-75k $75+k None Specified 0 0 0 0 0 M 18-35 0 1
1 1 1 F 18-35 0 1 1 1 1 M 35-45 0 2 2 2 2 F 35-45 0 2 2 2 2 M 45-55
0 3 3 3 3 F 45-55 0 3 3 3 3
[0159] The advertising transaction may be further analyzed to
identify behavioral targeting attributes, with the identified
attribute values (if any) used to determine behavioral target
attribute ID, step 314. In an embodiment, the demographic targeting
attribute ID may be determined by using the demographic targeting
information in the advertising transaction as look-up quantities in
a table look-up process to obtain an ID using a data table such as
the example illustrated in Table 5. For example, if the purchased
advertisement includes a keyword targeted package, the table
look-up process using Table 5 would determine that the behavioral
attribute ID would be "2."
TABLE-US-00005 TABLE 5 Behavioral Targeting Package Behavioral
Package ID NONE 0 PREVIOUS SITE VISIT 1 KEYWORD 2 REFERENT SITE 3
RETARGET 4 MULTI 5
[0160] The advertising transaction may be further analyzed to
identify geographic targeting attributes, with the identified
attribute values (if any) used to determine geographic target
attribute ID, step 316. In an embodiment, the demographic targeting
attribute ID may be determined by using the geographic targeting
information in the advertising transaction as look-up quantities in
a table look-up process to obtain an ID using a data table such as
the example illustrated in Table 6. For example, if the purchased
advertisement is targeted at a particular U.S. state, the table
look-up process using Table 6 would determine that the geographic
attribute ID would be "3."
TABLE-US-00006 TABLE 6 Geographic Targeting Package GEO_PACKAGE_ID
NONE 0 COUNTRY 1 DMA 2 STATE 3 CITY 4
[0161] The advertising transaction may be further analyzed to
determine the revenue model of the transaction, with the identified
revenue used to determine behavioral target attribute ID, step 318.
In an embodiment, the revenue model attribute ID may be determined
by using the revenue model information in the advertising
transaction as a look-up quantity in a table look-up process to
obtain an ID using a data table such as the example illustrated in
Table 7. For example, if the purchased advertisement is purchased
on the basis of a cost-per-click on the advertisement, the table
look-up process using Table 7 would determine that the revenue
model ID would be "2."
TABLE-US-00007 TABLE 7 Revenue Model Name REV_METRIC REV. MODEL ID
Cost Per Mille Impressions CPM 1 Cost Per `Click` CPC 2 Cost Per
`Action` (as defined by CPA 3 transacting parties) Cost Per
(Unique) Session CPS 4
[0162] The advertising transaction may be further analyzed to
identify sales channel information, with the identified information
used to determine a sale channel attribute ID, step 320. In an
embodiment, the sale channel attribute ID may be determined by
using the sale channel information in the advertising transaction
as look-up quantities in a table look-up process to obtain an ID
using a data table such as the example illustrated in Table 8. For
example, if the purchased advertisement was sold by a contracted
network agent, the table look-up process using Table 8 would
determine that the sale channel attribute ID would be "2."
TABLE-US-00008 TABLE 8 Sales Channel Name Sales Channel ID Direct
Sales Force 1 Contracted Network Agent 2 Tier II Reseller 3 Remnant
4
[0163] The advertising transaction may be further analyzed to
identify buy channel information, with the identified information
used to determine a buy channel attribute ID, step 322. In an
embodiment, the buy channel attribute ID may be determined by using
the buy channel information in the advertising transaction as
look-up quantities in a table look-up process to obtain an ID using
a data table such as the example illustrated in Table 9. For
example, if the purchased advertisement was purchased through an
agency buy desk, the table look-up process using Table 9 would
determine that the buy channel attribute ID would be "2."
TABLE-US-00009 TABLE 9 Buy Channel Buy Channel ID Advertiser Buy
Desk 1 Agency Buy Desk 2 Automated Remnant Fill 3
[0164] The advertising transaction may be further analyzed to
identify information related to the size of the advertiser account
with the publisher, with the identified information used to
determine an advertiser transaction share attribute ID, step 324.
This information may also be determined by querying the advertising
transaction database to determine the size of the advertiser's
account with the gross bookings of the publisher. In an embodiment,
the advertiser transaction share attribute ID may be determined by
using the advertiser's share of the publisher's bookings as look-up
quantities in a table look-up process to obtain an ID using a data
table such as the example illustrated in Table 10. For example, if
the advertiser's account represents less than one percent of the
publisher's total bookings, the table look-up process using Table
10 would determine that the advertiser transaction share attribute
ID would be "4."
TABLE-US-00010 TABLE 10 Advertiser Transaction Share Advertiser
Transaction Tier .sup. >10% 1 >5 < 10% 2 >1 < 5% 3
.sup. <1% 4
[0165] The advertising transaction may be further analyzed to
identify the advertiser's industry, with the identified information
used to determine an advertiser industry attribute ID, step 326. If
the advertiser's industry is not identified within the advertising
transaction, the advertiser's company name may be used in a table
look-up to identify that company's industry segment. In an
embodiment, the advertiser industry attribute ID may be determined
by using the advertiser industry information as a look-up quantity
in a table look-up process to obtain an ID using a data table such
as the example illustrated in Table 11. For example, if the
advertiser is in the telecom industry, the table look-up process
using Table 11 would determine that the advertiser industry
attribute ID would be "5."
TABLE-US-00011 TABLE 11 Advertiser Industry Advertiser Industry ID
Auto 1 Consumer 2 Financial 3 Media and Entertainment 4 Telecom 5
Computers and Technology 6 Travel 7 Other 8
[0166] The advertising transaction may be further analyzed to
determine the advertising product category information, with the
identified information used to determine a display product category
attribute ID, step 328. In an embodiment, the product category
attribute ID may be determined by using the advertisement
information in the advertising transaction as a look-up quantity in
a table look-up process to obtain an ID using a data table such as
the example illustrated in Table 12. For example, if the purchased
advertisement is for an off-page ad, the table look-up process
using Table 12 would determine that the display product category
attribute ID would be "2."
TABLE-US-00012 TABLE 12 Product Category Name Product Category ID
In-Page 1 Off-Page 2
[0167] The advertising transaction may be further analyzed to
determine advertising product type information, with the identified
information used to determine a product type attribute ID, step
330. In an embodiment, the product type attribute ID may be
determined by using the product type information in the advertising
transaction as a look-up quantity in a table look-up process to
obtain an ID using a data table such as the example illustrated in
Table 13. For example, if the purchased advertisement is for a
banner ad presented in an Internet webpage, the table look-up
process using Table 13 would determine that the product type
attribute ID would be "2."
TABLE-US-00013 TABLE 13 Product Type Name Product Type ID Rectangle
(HTML/Rich Media) 1 Banner (HTML/Rich Media) 2 Skyscraper
(HTML/Rich Media) 3 Button (HTML/Rich Media) 4 In-Stream Video
(Video) 5 Slide (HTML/Rich Media/Video) 6 Pop-Up (HTML/Rich
Media/Video) 7 Pop-Under (HTML/Rich Media) 8
[0168] The advertising transaction may be further analyzed to
identify the domain name of an Internet site in which the purchased
advertisement is slotted to appear (if applicable), and then using
Internet audience measuring services (such as Quantcast or
Nielsen), the traffic to that domain name can be determined and
used to define the domain attribute ID, step 332. In an embodiment,
the sale channel attribute ID may be determined by using the number
of hits on the domain name as a look-up quantity in a table look-up
process to obtain an ID using a data table such as the example
illustrated in Table 15. For example, if the purchased
advertisement will appear in a website with a domain monthly unique
visitor value of 3 million unique visitors per month (which falls
within the category 1.5 mm-5 mm), the table look-up process using
Table 15 would determine that the sale channel attribute ID would
be "4."
TABLE-US-00014 TABLE 15 Domain Monthly Gross Eligible Domain Unique
Visitors US Domains Tier ID +20 mm 30 1 10 mm-20 mm 60 2 5 mm-10 mm
160 3 1.5 mm-5 mm.sup. 1100 4
[0169] The advertising transaction may be further analyzed to
identify the publisher's subject matter information, with the
identified information used to determine a publisher domain
classification attribute ID, step 334. If the publisher's subject
matter is not included in the capture advertising transaction, the
publisher's name may be used in a table look-up process to
determine the subject matter covered by that publisher. In an
embodiment, the publisher domain classification attribute ID may be
determined by using the publisher's subject matter information as
look-up a quantity in a table look-up process to obtain an ID using
a data table such as the example illustrated in Table 16. For
example, if the purchased advertisement will appear in a sports
subject matter medium, the table look-up process using Table 16
would determine that the sale channel attribute ID would be
"4."
TABLE-US-00015 TABLE 16 Domain Subject Matter Domain Subject ID
News and Information 1 Financial 2 Entertainment 3 Sports 4
Computers & Technology 5 Social Media 6 Other 7
[0170] Using the determined advertiser's industry determined in
step 326 and the publisher's domain subject matter determined in
step 334, the system can assigned an attribute value to the context
overlap tier, step 336. As described above, this attribute reflects
a relative measure of the degree to which an advertisement in the
publisher's domain may have crossover application to other
industries. In an embodiment, the context overlap tier attribute
can be determined using the advertiser's industry and the
publisher's domain subject matter as look-up quantities in a table
look-up process to obtain an ID using a data table such as the
example illustrated in Table 17. For example, if the advertisement
is purchased by an automotive company and will appear in a sports
subject matter medium, the table look-up process using Table 17
would determine that the sale channel attribute ID would be
"1."
TABLE-US-00016 TABLE 17 Publisher Domain Subject Matter VALUE ID
News and Computers Social TIER Information Financial Entertainment
Sports & Tech. Media Advertiser Auto 2 1 3 1 3 2 Industry
Consumer 2 3 1 2 2 1 Financial 1 1 3 2 1 3 Media and 2 3 1 2 2 1
Entertainment Telecom 2 1 3 3 1 2 Computers & 2 1 2 2 1 2
Technology Travel 1 1 3 3 3 3
[0171] The advertising transaction may be further analyzed to
determine the advertisement product dimension information, with the
identified information used to determine a product dimension
attribute ID, step 338. In an embodiment, the product dimension
attribute ID may be determined by using the product dimension
information in the advertising transaction as a look-up quantity in
a table look-up process to obtain an ID using a data table such as
the example illustrated in Table 18. For example, if the purchased
advertisement is for a full banner ad measuring 468.times.60
pixels, the table look-up process using Table 18 would determine
that the product type attribute ID would be "5."
TABLE-US-00017 TABLE 18 Product Product Name Dimension Dimension ID
Leaderboard .sup. 728 .times. 90 IMU 1 (Universal Ad Package) Wide
Skyscraper (UAP) 160 .times. 600 2 Medium Rectangle (UAP) 300
.times. 250 3 Rectangle (UAP) 180 .times. 150 4 Full Banner 468
.times. 60 5 Half Banner 234 .times. 60 6 Vertical Banner 120
.times. 240 7 Skyscraper 120 .times. 600 8 Half Page 300 .times.
600 9 Large Rectangle 336 .times. 280 10 Vertical Rectangle 240
.times. 400 11 Square Button 125 .times. 125 12 Button 1 120
.times. 90 13 Button 2 120 .times. 60 14 Micro Bar 88 .times. 31 15
Large Video Rectangle 480 .times. 270 16 Medium Video Rectangle 320
.times. 180 17 Small Video Rectangle 240 .times. 135 18
[0172] The advertising transaction may be further analyzed to
determine advertisement placement information, with the identified
information used to determine a product placement attribute ID,
step 340. In an embodiment, the product placement attribute ID may
be determined by using the product placement information in the
advertising transaction as a look-up quantity in a table look-up
process to obtain an ID using a data table such as the example
illustrated in Table 19. For example, if the purchased
advertisement is for placement of an ad on any page within an
Internet website, the table look-up process using Table 19 would
determine that the product type attribute ID would be "2."
TABLE-US-00018 TABLE 19 Product Placement Placement Level ID
NETWORK 1 SITE 2 PAGE GROUP 3 PAGE 4
[0173] The advertising transaction may be further analyzed to
determine the advertisement booking date information, and the
identified booking date may be transformed into a consistent date
format, step 342. The advertising transaction may be further
analyzed to determine the ad revenue values, and generate a booking
size attribute value by transforming revenue values summed across a
single transaction, step 344. In an embodiment, the booking size
attribute value may be the dollar (or other currency) value itself.
Similarly, the advertising transaction may be further analyzed to
determine the ad revenue values, and for all transactions of a
shared transaction ID an effective revenue attribute value can be
calculated according to the calculation method indicated by the
transaction's revenue model (see step 318), step 346. All
transactions of a single transaction ID may be summed and then
divided by the number of transaction ID's attached to a single
transaction to generate the effective revenue attribute value.
[0174] Once all of the values for the attributes used in the
taxonomy have been extracted from the advertising transaction, the
attribute values can be stored in a relational database as a
transaction record indexed to the transaction record ID, step
348.
[0175] By capturing advertising transactions from data streams,
summarizing and organizing the information according to a taxonomy
as described above, and storing the advertising transaction records
in a relational database, many useful data products and market
measures can be generated. The following embodiments illustrate
some applications and uses of such an advertising transaction
database and the information products that can be generated.
[0176] FIG. 4 is a process flow diagram of an embodiment method for
aggregating and recording advertising transactions according to
standardized attributes of such transactions. In this method, a
plurality of advertising transaction for the placement of ads in
media are captured, step 400. As discussed above, the advertising
transactions may be automatically captured from a variety of
advertising transaction data. Captured advertising transaction data
are processed to determine the attribute values contained within
the transaction data, step 402. As discussed above, the advertising
transaction data may be parsed to recognize data corresponding to a
standard set of attributes. The identified attribute information
may be transformed into attribute values that can be stored in an
advertising transaction record within a database, step 404. The
advertising transaction attribute values may then be organized and
stored within an advertising transaction database according to a
taxonomy, step 406. The result of this process will be a database
that contains advertising market information that can be utilized
for a variety of purposes as described more fully herein. As
discussed above, the advertising transaction attributes that are
identified within transaction data may include the advertising
medium, the media platform, a revenue model, a media sales channel,
an advertising product category, an advertising product type, an
advertising product dimension, an advertising product placement, a
publisher tier, its publisher classification, an advertiser
transaction tier, an advertiser buy agent, an advertiser industry,
an advertising product context overlap tier, an advertising product
behavioral targeting package, an advertising product geographic
targeting package, an advertising product demographic targeting
package, an advertising product booking date, an advertising
product launch date, an advertising product gross transaction size,
an advertising product transaction with gross revenue, an
advertising product transaction net revenue, an effective unit
revenue, a time to launch, a geographic attribute, a location
attribute, a proximity attribute, a time attribute, a seasonal
attribute, a keyword attribute, a target customer act attribute, an
estimated viewer attribute, an estimated click-through attribute,
an estimated purchase attribute, an estimated listener attribute, a
duration attribute, a font attribute, a font size attribute, an
animation attribute, a motion attribute, and a relative placement
attribute. Examples of various attribute values are described above
in the discussion of the attribute taxonomy.
[0177] FIG. 5 illustrates a method that makes use of the attribute
taxonomy and advertising transaction data analysis described above
to provide a common market index for aggregating and characterizing
advertising transactions. As discussed above, a plurality of
advertising transactions may be captured from a data stream of
transaction data, step 400, and the captured advertising
transaction data processed to determine the attribute values
contained within the transaction data, step 402. The identified
attribute information may be transformed into attribute values that
can be stored in an advertising transaction record within a
database, step 404. The advertising transaction attribute values
may then be organized and stored within a advertising transaction
database according to a taxonomy, step 406. By using this database,
a common market index can be developed by aggregating selected
attributes of the stored advertising transaction records, step 500.
By aggregating advertising transactions according to particular
attributes, market indexes can be established for various types of
advertising associated with those attributes. For example, market
indexes may be generated for advertising transactions for
advertisements placed in electronic media, published media, radio
media, television media, as well as any other media addressed in
the attribute taxonomy discussed above. As another example, market
indexes may be generated for advertising transactions sold through
the various types of media sales channels. Thus, by storing
advertising transaction records that include attribute values
according to taxonomy, a wide variety of different market indexes
can be generated from a historical database of such
transactions.
[0178] A variety of different methods can be used for aggregating
advertising transactions. For example, the aggregation may include
averaging prices of the advertising transactions for a selected
attribute for a selected time period. Such averaging may be
accomplished over a variety of time periods, including: present
time; future time; custom-defined time; point in time; a reference
period; a benchmark period; a fiscal market duration; a calendar
year; a fiscal year; a calendar quarter; a fiscal quarter; a month;
a week; a day; a composite time period; a rolling time period; and
a fixed time period. The process of aggregating advertising
transactions may also include volume-weighted averaging of
advertising prices; booking-time-weighted averaging of prices;
flight-time-weighted averaging of prices; calculating the rolling
average prices of advertising; calculating the moving average
prices of advertising; dynamically averaging prices of advertising;
establishing the main point of advertising prices; and establishing
the medium point of advertising prices, with all of these
aggregation methods being performed for selected attributes over a
selected time period. Additionally, the aggregation process may
include assigning the transaction data to a taxonomy according to
standardized advertising transaction attributes such as those
described above.
[0179] The processes of establishing common market indexes can be
automated with raw data being automatically obtained from a variety
of parties via a variety of transmission mechanisms. For example,
raw advertising transaction data may be obtained from an advertiser
party, a publisher, a media buyer, an agent, a network, a carrier,
a theater, a database, an exchange or a market. The raw data may be
received via a variety of mechanisms, including for example a data
feed, a data scrape, a data syndication system, a data broadcast, a
wireless data transmission, a satellite data transmission, a
printed data transmission that is manually or automatically scanned
into the system, an Internet-protocol transmission, an electronic
mail transmission, an instant message or transmission, a telephone
transmission, and a facsimile transmission, as well as a variety of
other manual and semiautomatic mechanisms.
[0180] Advertising transaction records may be pre-processed before
the aggregation processing. For example, the advertising
transaction records may be normalized, cleansed and scanned to
identify and remove duplicate records (de-duplicate). Additionally,
advertising transaction records may be verified and the data
triangulated. Also, the source data for advertising transaction
records may be archived.
[0181] Advertising transaction indexes established according to the
method illustrated in FIG. 5 may be useful for estimating the cost
of future advertising transactions, pricing advertising, budgeting
for advertising, building a risk market for advertising; creating
an information market for advertising economic indicators;
incorporating indexes in a media order; buying, planning and
optimization systems; and establishing both primary and derivative
marketplaces for advertising transactions.
[0182] FIG. 6 illustrates an example method for establishing an
advertising market benchmark for use as a basis for advertising
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured and their
attribute values identified and stored in a database, step 600.
This database can be indexed and organized according to an
attribute taxonomy to enable selected data records to be sampled
and analyzed. To create a benchmark for advertising transactions
matching particular attribute values, a subset of advertising
transaction records are selected within the database for sampling
based on those attribute values, step 602. The sampled advertising
transaction records are then compiled in order to establish a
benchmark based on the sampled set of transactions, step 604.
Benchmark values can be determined for any subset of attribute
values to provide a wide range of measures for an advertising
marketplace. For example, a benchmark may be established for
television advertising in the evening time block for sports related
programming placement one month in advance of the present day by
selecting advertising transactions with attribute values
corresponding to those parameters. By searching the database of
advertising transactions using those attribute values as record
selection keys, many or all of the recorded transactions
corresponding to just such advertising purchases can be accessed
and used to generate the benchmark. A variety of mathematical
methods may be used to establish the benchmark based on the data
set, including for example averaging all the records to determine
the mean value or selecting the median value. Other methods include
weighting all transactions in the selected group by revenue such
that the benchmark reflects true economic value generated by
particular attribute combinations.
[0183] FIG. 7 illustrates steps of a method for establishing an
advertising reference entity using a top-down process. As described
above with reference to FIGS. 2-5, a plurality of advertising
transactions are captured and their attribute values identified and
stored in a database, step 700. This database can be indexed and
organized according to an attribute taxonomy to enable selected
data records to be sampled and analyzed. To create a reference
entity for advertising transactions matching particular attribute
values, a subset of advertising transaction records are selected
within the database for sampling based on those attribute values,
step 702. The sampled advertising transaction records are then
compiled in order to establish an advertising reference entity
based on the sampled set of transactions, step 704. The
transactions that compose the reference entity can then be
averaged, revenue-weighted, or otherwise defined according to the
mean or median value in the series. The mathematical output of this
operation can then serve as a proxy for the `value` of the
reference entity, and thus may be understood or interpreted to be
what a sample advertising transaction may be reasonably expected to
economically generate in the marketplace.
[0184] FIG. 8 illustrates steps of a method for establishing an
advertising reference entity by aggregating selected classes or
types of advertising transactions. As described above with
reference to FIGS. 2-5, a plurality of advertising transactions are
captured from any of a variety of data sources and data
transmission mechanisms, the transaction attribute values are
identified, certain transaction values are transformed to attribute
tier values, and the resulting advertising transaction records are
stored in a database, step 800. As part of this process, the
transaction records and the database can be indexed and organized
according to an attribute taxonomy to enable selected data records
to be sampled and analyzed. To establish an advertising reference
entity for selected classes or types of advertising transactions
matching particular attribute values, a subset of advertising
transaction records are selected within the database for sampling
based on those attribute values, step 802. For example, attribute
values may be selected to extract a subset of advertising
transaction records related to electronic display advertising,
mobile advertising, search advertising, video advertising, game
advertising, public display advertising, outdoor advertising, print
advertising, radio advertising, television advertising, direct
marketing advertising, telemarketing advertising, product placement
as described more fully below with reference to FIGS. 31 through
134. The sampled advertising transaction records are then
aggregated to establish an advertising reference entity value, step
804. The transactions that compose the reference entity can then be
averaged, revenue-weighted, or otherwise defined according to the
mean or median value in the series. The mathematical output of this
operation can then serve as a proxy for the `value` of the
reference entity, and thus may be understood or interpreted to be
what a sample advertising transaction may be reasonably expected to
economically generate in the marketplace. In the instance of a
`bottom-up` reference entity calculation, the specific attributes
targeted for selection and inclusion in the reference entity are
defined by the attributes of the broad set of transactions
initially under consideration, rather than being pre-determined or
blindly defined in advance of considering the transaction set. In
this way, the bottoms-up calculation methodology reflects the very
attribute profile of the entire eligible transaction set, rather
than having artificial constraints imposed upon it.
[0185] A reference entity may be established for the selected
advertising market using method steps such as those illustrated in
FIG. 9. As described above with reference to FIGS. 2-5, a plurality
of advertising transactions are captured from any of a variety of
data sources and data transmission mechanisms, the transaction
attribute values are identified, certain transaction values are
transformed to attribute tier values, and resulting advertising
transaction records are stored in a database, step 900. As part of
this process, the transaction records and the database can be
indexed and organized according to an attribute taxonomy to enable
selected data records to be sampled and analyzed. To establish an
advertising reference entity for the selected market segment
advertising transactions whose attributes match the selected
attribute values, a subset of advertising transaction records are
selected within the database for sampling based on those attribute
values, step 902. The identified targeted attribute values may
include single attributes or combinations of attributes associated
with electronic display advertising transactions. The sampled
advertising transaction records are then aggregated to establish an
advertising reference entity value, step 804.
[0186] In this application of the various embodiments, advertising
transaction records may be selected from an advertising transaction
database by specifying a particular attribute value (e.g.,
"electronic display" or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 900 may be limited to transactions purchasing advertising in
the selected market, as illustrated in FIG. 10. For example, the
data sources used to collect advertising transactions may be
limited to selected agency media buyer data feeds 1000, advertiser
data feeds 1002, advertising server data feeds 1004, advertising
networks and exchanges data feeds 1006, and publisher order
management system data feeds 1008. Additionally, the advertising
transaction data feeds may be filtered by a selected advertising
reference entity data filter, step 1010. As mentioned above, the
selected advertising transaction data received from the various
data feeds may be preprocessed to remove duplicate transaction
records, step 1012. The preprocessed advertising transaction data
may then be processed to transform attribute information into
attribute tier values with the resulting data records stored in a
database, step 1014.
[0187] FIG. 11 illustrates in more detail steps involved in
organizing advertising transaction records according to a taxonomy
of selected advertising attributes. Advertising transaction data
selected via a selected advertising reference entity data filter,
step 1010, may be preprocessed as described above, step 1102.
Information related to market and media popularity or viewing may
be obtained from ratings bureau databases (e.g., Quantcast.com and
Nielsen), websites and other such data feeds, step 1104. This data
may be combined to transform the information from advertising
transactions into attribute values and attribute tier values as
described above with reference to FIGS. 3A, 3B. For example, a
product data may be transformed into a product attribute tier
value, step 1106, publisher data information may be transformed
into publisher tier attribute values, step 1108, advertiser
information may be transformed into advertiser tier attribute
values, step 1110, targeting package information may be transformed
into one or more targeting attribute tier values, step 1112, flight
information may be transformed into advertising product flight
attribute values, and revenue information may be transformed into
one or more revenue attribute tier values, step 1116. The
transformed selected advertising transaction attribute values may
then be stored in a relational database or data warehouse, step
1118. The stored data may then be used to determine the selected
advertising reference entity value, step 1120.
[0188] In an embodiment illustrated in FIG. 12, a selected
advertising reference entity framework 1202 may be applied as an
automated filter to the eligible pool of archived selected
advertising transactions stored in a relational database or data
warehouse 1200. In this process, an advertising reference entity
server 1204 may use the selected advertising reference entity
framework 1202 as a filter or search framework for drawing archived
selected advertising transactions from the data warehouse 1200. The
advertising reference entity server 1204 may then use the sampled
transaction data to synthesize a selected advertising reference
entity 1206. The process of synthesizing the reference entity may
involve calculating the indexed reference entity value of the
transaction sampled on the basis of the defined attribute values
contained in the reference entity framework 1202. For example, the
indexed value may include a gross transaction size, a gross revenue
index, a net revenue index, and an effective unit revenue
index.
[0189] FIG. 13 illustrates a method that may be employed to use an
advertising reference entity as an advertising market benchmark. In
this method, the value of an advertising reference entity is
defined, step 1300, such as by using the methods described above
with reference to FIG. 7-11 for defining a market reference entity.
The selected market reference entity may then be used to establish
a selected advertising market benchmark, step 1302. This process
may involve publishing the value of the advertising reference
entity to the marketplace on a timely and consistent basis over
time. The publication of the value of the advertising reference
entity may be syndicated. The advertising reference entity may then
be established as an advertising market benchmark for subsequent
transactions, operations and the like. The process of defining the
advertising reference entity may include extracting, transforming
and loading a stream of advertising transaction data records into a
relational database from a plurality of data sources. The extracted
advertising transaction records may include organizing the records
according to attribute tiers defined in a taxonomy of advertising
attribute values. The process may also involve identifying targeted
attribute values that represent a selected plurality of advertising
transactions, and sampling a set of advertising transactions based
upon the defined attribute values. Publication of the advertising
reference entity may be accomplished at the time the value is
calculated using a variety of publication mechanisms. Similarly,
the syndication of advertising reference entities may be
accomplished using a variety of communication mechanisms. Examples
of such publication and syndication communication mechanisms
include electronic, wireless, broadcast, print, television, radio,
Internet, file transfer, and similar automated and electronic
communication mechanisms. The advertising reference entity may also
be published and syndicated via closed, open and public networks,
as well as via communication among different members of an
advertising marketplace. The advertising reference entity may also
be archived at the moment of calculation using any known data
archiving mechanisms and storage devices.
[0190] FIG. 14 illustrates a method in which a selected advertising
reference entity is used as an electronic display advertising
market benchmark. In this embodiment, a selected advertising
reference entity framework 1400 is used by an advertising reference
entity server 1402 to selectively sample selected advertising
transaction records stored within a relational database or data
warehouse 1404. The advertising reference entity server 1402 uses
the sampled transaction data to define the selected advertising
reference entity 1406. This reference entity is then published as a
selected advertising reference entity data publication 1408. The
reference entity definition may also be used to generate a selected
advertising reference entity data syndication 1410. In this
embodiment, the value of the selected advertising reference entity
may be calculated following a consistently defined and executed
advertising reference entity definition process with the results
published and syndicated as described above with reference to FIG.
13.
[0191] FIG. 15 illustrates a method for using a single advertising
product composite price as an advertising product composite price
benchmark. In this process, attribute values which define a
particular type of advertising product are used to sample an
advertising transaction relational database or data warehouse to
extract advertising transaction records associated with a selected
type of advertising product over a period of time, step 1500. Using
the extracted advertising transaction records, an advertising
composite price is determined, step 1502. This establishes an
advertising product composite price within the identified sample
transaction time frame. The advertising product composite price may
then be published to the marketplace on a timely and consistent
basis with the publication syndicated, thereby establishing the
advertising product composite price as an advertising composite
price benchmark for subsequent transactions and operations, step
1504. For example, advertising transaction records may be selected
for particular advertising products such as electronic display,
mobile advertising, search advertising, video advertising, game
advertising, public display, outdoor advertising, print, radio and
television advertising, direct marketing, telemarketing, and
product placement advertising products (see further discussion
below with reference to FIGS. 31-134). As another example, the
advertising product may be selected based upon demand, such as a
high-demand advertising product. Such high demand advertising
products may be defined by volume, impressions, broadcast time, on
air time, place, turns, displays, actions, clicks, purchases,
views, dollars, and other units of measure.
[0192] FIG. 16 illustrates a system network for identifying
attribute values and sampling advertising transactions whose
attribute values meet the identified values to define a set of
advertising transactions to be extracted, transformed and loaded
into a select advertising product composite price. Raw advertising
transaction data may be obtained from a variety of sources
including, for example, advertising buyer agent data feeds 1600,
advertiser data feeds 1602, at the pricing server data feeds 1604,
advertising networks and exchange data feeds 1606, and publisher
order management system data feeds 1608. The raw advertising
transaction data may be pre-processed to remove duplicates and
otherwise transform attribute values into attribute tier values,
step 1610, with the resulting data provided to an advertising
product composite pricing engine 1612. The advertising product
composite price engine may calculate a volume-weighted composite
price for sampled advertising products of the identified attribute
values conducted within an identify transaction time frame.
[0193] As illustrated in FIG. 17, the output from the advertising
product composite pricing engine, step 1700, may be published as an
advertising product composite price publication, step 1702, and
syndicated as an advertising product composite price indication,
step 1704. The publication and syndication of the advertising
product composite price may be accomplished on the composite price
as calculated via a variety of publication and communication
mechanisms. Examples of such publication and communication
mechanisms include, for example, electronic, wireless, broadcast,
print, television, radio, Internet, as file transfer, and other
electronic communication means. The advertising product composite
price may also be published and syndicated via closed, open and
public networks, as well as communications among market
participants. Additionally, the advertising product composite price
may be archived using any known archival methods and storage
devices.
[0194] FIG. 18 illustrates a generalized method that may be used to
originate a financial instrument from an advertising benchmark. An
advertising benchmark is generated based on information regarding
at least one advertising market or advertising product transaction
category utilizing various methods described above, step 1800. This
advertising benchmark is then used to originate an advertising
financial instrument, step 1802, whereby a party may enter into an
advertising transaction the terms of which are based on the
advertising benchmark. The benchmark used for originating an
advertising financial instrument may be an advertising reference
entity as described above. For example, the reference entity may be
any of electronic display, mobile advertising, search advertising,
video advertising, game advertising, public display advertising,
outdoor advertising, print advertising, radio advertising,
television advertising, direct marketing, telemarketing and product
placement advertising market reference entities. The benchmark also
may be the advertising product composite price for any of the
various advertising markets. The benchmark may also be an index,
such as an advertising sentiment index, an advertising activity
index, an advertising price index, an advertising spend migration
index, a relative strength index, a moving average index, and a
rolling index. The advertising market index may be an index for any
one or combination of the various advertising markets or
advertising products. The advertising financial instrument may be
any of a derivative financial instrument, a primary market
financial instrument, an exchange traded note, an option, a futures
contract, a reference entity futures contract, an option on a
futures contract, a composite price futures contract, a forward, a
principal protected note, securitization, a security, a single
advertising product future, an advertising sentiment future, an
advertising index future, an advertising activity future, a basis
for a swap, a collateralized obligation, a structured entity, a
primary market instrument, a security market instrument, a bespoke
instrument, an over-the-counter instrument, an exchange-listed
instrument, a liquid instrument, an illiquid instrument, a
cash-settlement instrument, a physical-settlement instrument, a
regulated instrument, a mark-to-market instrument, and a
standardized contract. The instruments and standardized contracts
may include terms such as trading unit, settlement method, point
sites, strike date, strike price, interval, limits, price banding,
minimum fluctuation, trading hours, listed platforms, minimum block
size, product calendar, issuance, market-to-market policies,
convergence with physical underlying entity, exchange rules,
distribution and leverage on money.
[0195] FIG. 19 illustrates a method for the origination, trading
and capture of advertising financial instruments. An advertising
financial instrument is originated, step 1900, such as according to
the method described above with reference to FIG. 18. As described
above, this process may involve taking an advertising benchmark
based upon information about at least one of an advertising market
or advertising product transaction activity, and providing an
advertising financial instrument whereby a party may enter into a
transaction terms of which are based on the advertising benchmark.
Mechanisms are provided for facilitating the exchange of
advertising market financial instruments whereby a party to an
instrument may enter into a transaction, including trading,
clearing and settling advertising financial instruments, step 1902.
In order to provide information to market participants, trades of
advertising financial instruments are captured and syndicated as
advertising financial instrument trade data, step 1904. Such trade
data may be published and syndicated to support the advertising
instrument market.
[0196] FIG. 20 illustrates a process for generating and trading
financial instruments. Origination of the advertising financial
instrument is made possible by providing advertising benchmarks
2000-2006. Advertising benchmarks may include advertising reference
entity benchmarks 2000, advertising composite price benchmarks
2002, index benchmarks 2004, and other benchmarks 2006. Such
benchmarks may be generated using the methods described above with
reference to FIGS. 6 and 15. Such benchmarks may be published 2008
and syndicated 2010 to provide market participants with easy access
to the benchmark information. Participants may include advertising
financial instrument buyers 2012 and advertising financial
instrument sellers 2014. If both participants in a bid and ask
auction have access to the same benchmark data then an orderly
marketplace can be afforded by matching bid and ask prices, such as
in an advertising financial instrument electronic communications
network (ECN) 2016.
[0197] FIG. 21 illustrates the components and interrelationships of
an advertising financial instrument market built around an
advertising financial instrument electronic communications network
(ECN) 2102. Such an exchange platform may automatically list, sort,
filter, batch and confirm best bids and offers for standardized
advertising financial instruments and derivative instruments. The
platform may use automatic listing and matching algorithms to match
best bids and offers, route instruments, account for transfers of
funds, clear and settle instruments and perform other processes
required in an orderly marketplace. The electronic communications
network may include an advertising financial instrument market
maker 2100 which may provide capital to facilitate an advertising
financial instrument transaction between a buyer 2104 and the
seller 2106. When the financial instrument is bought and sold, the
buyer's funds or promissory note and the financial instrument may
be recorded or otherwise maintained in an advertising financial
instrument escrow account 2108 until the financial instrument
transaction is cleared, step 2110, and the transaction settled,
step 2112. A cleared transaction may be processed and stored in an
advertising financial instrument fiduciary account 2114 which may
transmit certificates associated with the transaction to the buyer
2104 and seller 2106.
[0198] The electronic communications network may be open to
qualified members of the market and includes secure data
communications between qualified principal, non-principal and other
market participants. The electronic communications network may
enable the market parties to exchange and view advertising
financial instrument price and volume information in real-time
while communicating with an advertising trade counterparty, broker
or market maker 2100. For example, the electronic communication
network may include secure instant messaging services on a trader
desktop suite, a secure web portal, and secure electronic mail. The
financial instrument electronic communication network and related
systems may be the sole capture agent, archiving mechanism and
publisher of price, volume and transaction data for physical and
derivative advertising financial instruments. The financial
instrument electronic communication network may be a platform for
clearing an advertising financial instrument transaction between
buyers and sellers, and serve as an advertising financial
instrument Central Counterparty (CCP) for clearing advertising
financial instrument trades and related obligations. The financial
instrument electronic communication network may be a facility for
settling advertising financial instrument exchange transactions,
and may be the exclusive advertising financial instruments
registry, handling certification and validation of advertising
financial instrument trades and accounts, expiration dates, revenue
assignment rights, account and margin balances. The advertising
financial instrument electronic communication network and related
systems may serve as the capture and data provisioning platform for
all exchange traded and over-the-counter advertising financial
instrument transactions and trades. Functions performed by the
advertising financial instrument electronic communication network
may include recording, archiving, indexing, making searchable,
sorting and syndicating all data generated, including trading
parties, counterparties, instruments, transactions, expiration
dates, revenue assignment rights, physical delivery obligations,
and the like.
[0199] FIG. 22 illustrates market participants, components and
process flow for syndication of the historic and current market
data regarding advertising financial instruments and advertising
financial instrument transactions. Similar to the market structure
described above with reference to FIG. 21, a market maker 2200 may
provide capital to facilitate advertising financial instrument
transactions between a buyer 2202 and a seller 2206 in the
advertising financial instrument electronic communication network
2204. The electronic communication network may capture financial
instrument transaction data, step 2210 including information
provided for over-the-counter and bespoke trades of advertising
financial instruments 2208. Captured financial instrument
transaction data may be stored in an advertising financial
instrument registry 2212 which can then be syndicated to support a
futures market. Information regarding futures transaction data may
be provided by syndication to buyers 2202 and sellers 2206. The
advertising financial instrument electronic communication network
can serve to track the attributes of a plurality of advertising
transactions and provide a real-time data stream of all advertising
financial market instrument transactions having a standard set of
attribute values to form a composite advertising financial
instrument "tape" indicator. The composite advertising financial
instrument tape indicator may reflect or indicate the current
status of the advertising market financial instruments with
particular attributes or combinations of attributes. This real-time
data stream can be syndicated. In addition to the foregoing steps,
methods for syndicating financial instrument transaction market
data may include providing historic advertising financial
instrument transaction data according to a standard set of
attributes, providing a set of data tools to analyze the historical
data along multiple dimensions, composing standard and custom views
of the advertising financial instrument transactions, and providing
an index based on a set of advertising financial instrument
transactions matching a set of attribute values. The tape indicator
may synthesize all similar advertising transactions into a single,
composite transaction for purposes of accurately gauging market
levels. The syndication of advertising financial instrument
transaction data may include: a transaction record detail at a
point of time, a composite transaction record detail over a period
of time; a value of the transaction at a point of time; a rate of
change of the value of the transaction; a relative strength of the
transaction to its historic averages; an individual transaction
benchmarked to an index composed of like transaction; an individual
transaction benchmarked to a composite market index; an individual
transaction benchmarked to a composite media index; an individual
transaction benchmarked to a composite platform index; an
individual transaction benchmarked to a composite context index; an
individual transaction benchmarked to a composite demographic
targeting package; an individual transaction benchmarked to a
composite geographic targeting package; and an individual
transaction benchmarked to a composite psychographic targeting
package index. Such an advertising financial instrument transaction
data syndication may be based on a subscription and/or provided to
a terminal on a closed network. If the syndication is via a
terminal on a closed network, the syndication service or vehicle
may also include a user interface along with user interface
analysis tools for analyzing the syndicated and related underlying
physical advertising market and historical transaction data and
information.
[0200] FIG. 23 illustrates a method that may be used for providing
a user interface for viewing bid and ask prices and transaction
data for advertising financial instruments. The processes described
above with reference to FIG. 18-22 may be used to originate and
trade advertising financial instruments, step 2300. The prices and
related transaction data of advertising financial instrument trades
and transactions may then be displayed on the user interface, step
2302, to enable a party to view bid and ask transactions for
advertising financial market instruments. Example screenshots of
such a user interface are presented in FIGS. 24-29. This user
interface may also enable users to exchange advertising transaction
financial instruments or otherwise enter into transactions
regarding advertising market financial instruments with the terms
of the transactions based upon a benchmark identified in the user
interface display.
[0201] By generating a number of benchmark values for the various
advertising products, advertising media and revenue models (among
other attributes), useful market reference information can be
generated. Such market information may be presented in an
electronic display to provide a user interface to enable market
participants to view underlying advertising reference entity
composition and pricing information. An example of such displays is
provided in FIG. 30. For example, a display 3000 may be provided
for viewing the advertising transactions that underpin a particular
benchmark, such as a benchmark for mobile WAP banner ads. Displays
3002 and 2004 illustrate user interfaces for viewing the
advertising transactions under pinning benchmarks for a broadband
video cash market and an electronic display cash market,
respectively.
[0202] The general embodiments described above, and particularly
the general embodiments described above with reference FIGS. 8-17,
may be used to generate reference entities, benchmarks, market
indexes and other information products useful to selected
advertising transaction markets. For example, as discussed below
with reference to FIGS. 31-134, selected reference entities,
benchmarks, indexes and market information products may be
generated for electronic display, mobile advertising, search
advertising, video advertising, game advertising, public display
advertising, outdoor advertising, print, radio and television
advertising, direct marketing, telemarketing, and product placement
advertising products.
[0203] FIG. 31 illustrates steps of a method for establishing an
electronic display advertising reference entity by aggregating
selected transactions. As described above with reference to FIGS.
2-5, a plurality of advertising transactions are captured from any
of a variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
3100. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the electronic display attribute
value, a subset of advertising transaction records are selected
within the database for processing, step 3102. The identified
targeted attribute values may include single attributes or
combinations of attributes associated with electronic display
advertising transactions. The sampled advertising transaction
records are then aggregated to establish an electronic display
advertising reference entity value, step 3104.
[0204] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"electronic display" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 3100 may be limited to transactions purchasing advertising in
electronic media, such as Internet advertising, as illustrated in
FIG. 32. For example, the data sources used to collect advertising
transactions may be limited to agency electronics delayed media
buyers data feeds 3200, electronic display advertisers data feeds
3202, electronic display advertising server data feeds 3204,
electronic display advertising networks and exchanges data feeds
3206, and electronic display publisher order management system data
feeds 3208. Additionally, the advertising transaction data feeds
may be filtered by an electronic display advertising reference
entity data filter, step 3210. As mentioned above, the electronic
display advertising transaction data received from the various data
feeds may be preprocessed to remove duplicate transaction records,
step 3212. The preprocessed electronic display advertising
transaction data may then be processed to transform attribute
information into attribute tier values and data records stored in a
database, step 3214.
[0205] FIG. 33 illustrates in more detail steps involved in
organizing electronic display advertising transaction records
according to a taxonomy of electronic display advertising
attributes. Advertising transaction data selected via an electronic
display advertising reference entity data filter, step 3310, may be
preprocessed as described above, step 3302. Information regarding
Internet traffic to domain names listed in electronic display
advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 3304. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 3306, publisher data information
may be transformed into publisher tier attribute values, step 3308,
advertiser information may be transformed into advertiser tier
attribute values, step 3310, targeting package information may be
transformed into one or more targeting attribute tier values, step
3312, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
3316. The transformed electronic display advertising transaction
attribute values may then be stored in a database or data
warehouse, step 3318. The data stored in a database may then be
used to determine the electronic display advertising reference
entity value, step 3320.
[0206] In an embodiment illustrated in FIG. 34, an electronic
display advertising reference entity framework 3402 may be applied
as an automated filter to the eligible pool of archived electronic
display advertising transactions stored in a data warehouse 3400.
In this process, an advertising reference entity server 3404 may
use the electronic display advertising reference entity framework
3402 as a filter or search framework for drawing archived
electronic display advertising transactions from the data warehouse
3400. The advertising reference entity server 3404 may then use the
sampled transaction data in order to synthesize an electronic
display advertising reference entity 3406. The process of
synthesizing the electronic display reference entity may involve
calculating the indexed reference entity value of the transactions
sampled on the basis of the defined attribute values contained in
the electronic display reference entity framework 3402. For
example, the indexed value may include a gross transaction size, a
gross revenue index, a net revenue index, and an effective unit
revenue index.
[0207] FIG. 35 illustrates a method in which an electronic display
advertising reference entity is used as an electronic display
advertising market benchmark. In this embodiment, an electronic
display advertising reference entity framework 3500 is used by an
electronic display advertising reference entity server 3502 to
selectively sample electronic advertising transaction records
stored within a data warehouse 3504. The electronic display
advertising reference entity server 3502 uses the sampled
transaction data to define an electronic display advertising
reference entity 3506. This reference entity is then published as
an electronic display advertising reference entity data publication
3508. The reference entity definition may also be used to generate
an electronic display advertising reference entity data syndication
3510. In this embodiment, the value of the electronic display
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0208] FIG. 36 illustrates a method for using a single electronic
display advertising product composite price as an electronic
display advertising product composite price benchmark. In this
process, electronic display attribute values which define a
particular type of electronic display advertising product are used
to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 3600. This
establishes an electronic display advertising product composite
price within the identified sample transaction time frame. The
electronic display advertising product composite price may then be
published to the marketplace on a timely and consistent basis with
the publication syndicated, thereby establishing the electronic
display advertising product composite price as an electronic
display advertising composite price benchmark for subsequent
transactions and operations, step 3602.
[0209] FIG. 37 illustrates a system network for identifying a set
of electronic display advertising transactions to be extracted,
transformed and used to define an electronic display advertising
product composite price. Raw electronic display advertising
transaction data may be obtained from a variety of sources
including, for example, agency electronic display advertising buyer
data feeds 3700, electronic display advertiser data feeds 3702,
electronic display advertising server data feeds 3704, electronic
display advertising networks and exchange data feeds 3706, and
electronic display publisher order management system data feeds
3708. The raw electronic display advertising transaction data may
be pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 3710, with the
resulting data provided to an electronic display advertising
product composite pricing engine 3712. The electronic display
advertising product composite price engine may include a
volume-weighted composite price for sampled electronic display
advertising products of the identified attribute values conducted
within an identify transaction time frame.
[0210] As illustrated in FIG. 38, the output from the electronic
display advertising product composite pricing engine, step 3800,
may be published as an electronic display advertising product
composite price publication, step 3802, and syndicated as an
electronic display advertising product composite price syndication,
step 3804. The publication and syndication of the electronic
display advertising product composite price may be accomplished via
a variety of publication and communication mechanisms. The
electronic display advertising product composite price may also be
published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
electronic display advertising product composite price may be
archived using any known archival methods and storage devices.
[0211] FIG. 39 illustrates steps of a method for establishing a
mobile advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
3900. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the mobile attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 3902. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with mobile advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a mobile advertising reference entity value, step
3904.
[0212] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"mobile" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 3900 may be
limited to transactions purchasing advertising in mobile media, as
illustrated in FIG. 40. For example, the data sources used to
collect advertising transactions may be limited to agency
electronics delayed media buyers data feeds 4000, mobile
advertisers data feeds 4002, mobile advertising server data feeds
4004, mobile advertising networks and exchanges data feeds 4006,
and mobile publisher order management system data feeds 4008.
Additionally, the advertising transaction data feeds may be
filtered by a mobile advertising reference entity data filter, step
4010. As mentioned above, the mobile advertising transaction data
received from the various data feeds may be preprocessed to remove
duplicate transaction records, step 4012. The preprocessed mobile
advertising transaction data may then be processed to transform
attribute information into attribute tier values and data records
stored in a database, step 4014.
[0213] In selecting mobile advertising transactions, advertising
transaction records may be selected based upon an advertising media
platform having a mobile advertising value. Examples of mobile
advertising attribute values include a digital medium, an analog
medium, an internet-enabled medium, a wireless medium, a social
medium, a satellite-based medium, a print medium, a broadcast
medium, a networked medium, a telephonic medium, a telepathic
medium, a brainwave medium, a recorded medium, a live medium, an
electronic display medium, an internet-enabled display medium, an
internet-enabled rich media display medium, an internet-enabled
text medium, an internet-enabled video medium, a social medium, an
internet-enabled social medium, a mobile display medium, a mobile
text medium, a mobile location based medium, a mobile video medium,
a mobile social medium, an internet-enabled search medium, a mobile
search medium, a video search medium, a video medium, a broadband
video medium, an internet protocol enabled broadband video medium,
a closed circuit video medium, a network served video medium, a
satellite-based video medium, an electronic game medium, an
internet-enabled game medium, a console game medium, a downloadable
game medium, a massively-multiplayer game medium, a public display
medium, an outdoor advertising medium, a radio medium, an Internet
Protocol radio medium, a satellite-broadcast radio medium, a
television medium, broadcast television medium, a spot television
medium, a cable television medium, a digitally recorded television
medium, and an Internet Protocol Television (IPTV) broadcast
medium.
[0214] FIG. 41 illustrates in more detail steps involved in
organizing mobile advertising transaction records according to a
taxonomy of mobile advertising attributes. Advertising transaction
data selected via a mobile advertising reference entity data
filter, step 4110, may be preprocessed as described above, step
4102. Information regarding viewings of mobile advertising
transactions may be obtained from ratings bureau databases (e.g.,
Quantcast.com and Nielsen), websites and other such data feeds,
step 4104. This data may be combined to transform the information
from advertising transactions into attribute values and attribute
tier values as described above with reference to FIG. 3A, 3B. For
example, a product data may be transformed into a product attribute
tier value, step 4106, publisher data information may be
transformed into publisher tier attribute values, step 4108,
advertiser information may be transformed into advertiser tier
attribute values, step 4110, targeting package information may be
transformed into one or more targeting attribute tier values, step
4112, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
4116. The transformed mobile advertising transaction attribute
values may then be stored in a database or data warehouse, step
4118. The data stored in a database may then be used to determine
the mobile advertising reference entity value, step 4120.
[0215] In an embodiment illustrated in FIG. 42, a mobile
advertising reference entity framework 4202 may be applied as an
automated filter to the eligible pool of archived mobile
advertising transactions stored in a data warehouse 4200. In this
process, an advertising reference entity server 4204 may use the
mobile advertising reference entity framework 4202 as a filter or
search framework for drawing archived mobile advertising
transactions from the data warehouse 4200. The advertising
reference entity server 4204 may then use the sampled transaction
data in order to synthesize a mobile advertising reference entity
4206. The process of synthesizing the mobile reference entity may
involve calculating the indexed reference entity value of the
transactions sampled on the basis of the defined attribute values
contained in the mobile reference entity framework 4202. For
example, the indexed value may include a gross transaction size, a
gross revenue index, a net revenue index, and an effective unit
revenue index.
[0216] FIG. 43 illustrates a method in which a mobile advertising
reference entity is used as a mobile advertising market benchmark.
In this embodiment, a mobile advertising reference entity framework
4300 is used by a mobile advertising reference entity server 4302
to selectively sample electronic advertising transaction records
stored within a data warehouse 4304. The mobile advertising
reference entity server 4302 uses the sampled transaction data to
define a mobile advertising reference entity 4306. This reference
entity is then published as a mobile advertising reference entity
data publication 4308. The reference entity definition may also be
used to generate a mobile advertising reference entity data
syndication 4310. In this embodiment, the value of the mobile
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0217] FIG. 44 illustrates a method for using a single mobile
advertising product composite price as a mobile advertising product
composite price benchmark. In this process, mobile attribute values
which define a particular type of mobile advertising product are
used to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 4400. This
establishes a mobile advertising product composite price within the
identified sample transaction time frame. The mobile advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the mobile advertising product composite price
as a mobile advertising composite price benchmark for subsequent
transactions and operations, step 4402.
[0218] FIG. 45 illustrates a system network for identifying a set
of mobile advertising transactions to be extracted, transformed and
used to define a mobile advertising product composite price. Raw
mobile advertising transaction data may be obtained from a variety
of sources including, for example, agency mobile advertising buyer
data feeds 4500, mobile advertiser data feeds 4502, mobile
advertising server data feeds 4504, mobile advertising networks and
exchange data feeds 4506, and mobile publisher order management
system data feeds 4508. The raw mobile advertising transaction data
may be pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 4510, with the
resulting data provided to a mobile advertising product composite
pricing engine 4512. The mobile advertising product composite price
engine may include a volume-weighted composite price for sampled
mobile advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0219] As illustrated in FIG. 46, the output from the mobile
advertising product composite pricing engine, step 4600, may be
published as a mobile advertising product composite price
publication, step 4602, and syndicated as a mobile advertising
product composite price syndication, step 4604. The publication and
syndication of the mobile advertising product composite price may
be accomplished via a variety of publication and communication
mechanisms. The mobile advertising product composite price may also
be published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
mobile advertising product composite price may be archived using
any known archival methods and storage devices.
[0220] FIG. 47 illustrates steps of a method for establishing a
search advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
4700. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the search attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 4702. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with search advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a search advertising reference entity value, step
4704.
[0221] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"search" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 4700 may be
limited to transactions purchasing advertising in search engines,
such as Internet advertising, as illustrated in FIG. 48. For
example, the data sources used to collect advertising transactions
may be limited to agency electronics delayed media buyers data
feeds 4800, search advertisers data feeds 4802, search advertising
server data feeds 4804, search advertising networks and exchanges
data feeds 4806, and search publisher order management system data
feeds 4808. Additionally, the advertising transaction data feeds
may be filtered by a search advertising reference entity data
filter, step 4810. As mentioned above, the search advertising
transaction data received from the various data feeds may be
preprocessed to remove duplicate transaction records, step 4812.
The preprocessed search advertising transaction data may then be
processed to transform attribute information into attribute tier
values and data records stored in a database, step 4814.
[0222] In selecting search advertising transactions, advertising
transaction records may be selected based upon an advertising media
platform having a search advertising value. Examples of search
advertising attribute values include a keyword search platform, a
location-based search platform, a mobile search platform, a video
search platform, a text search platform, an image search platform,
an audio search platform, a broadband video search platform, an
Internet-Protocol enabled search platform, an analog search
platform, a game search platform, a mobile in-vehicle network
served search platform, a mobile in-elevator network served search
platform, a mobile in-flight network served search platform, a
radio search platform, a mobile satellite-broadcast radio platform,
a mobile television platform, a mobile broadcast television
platform, a mobile spot television platform, a mobile cable
television platform, a mobile digitally recorded television
platform, a mobile Internet Protocol Television (IPTV) broadcast
platform, a mobile direct marketing platform, a mobile media insert
product placement platform, a graphical search platform, a social
search platform, a semantic search platform, a textual search
platform, a contextual search platform, a predictive search
platform, an algorithmic search platform, a Boolean search
platform, a syndicated search platform, a network search platform,
a branded search platform, a white label search platform, an
institutional search platform, a private search platform, an
educational search platform, a corporate search platform, a
governmental search platform, a geographic search platform, a
database search platform, a downloadable search platform, an
executable search platform, a print search platform.
[0223] FIG. 49 illustrates in more detail steps involved in
organizing search advertising transaction records according to a
taxonomy of search advertising attributes. Advertising transaction
data selected via a search advertising reference entity data
filter, step 4910, may be preprocessed as described above, step
4902. Information regarding traffic to search engines listed in
search advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 4904. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 4906, publisher data information
may be transformed into publisher tier attribute values, step 4908,
advertiser information may be transformed into advertiser tier
attribute values, step 4910, targeting package information may be
transformed into one or more targeting attribute tier values, step
4912, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
4916. The transformed search advertising transaction attribute
values may then be stored in a database or data warehouse, step
4918. The data stored in a database may then be used to determine
the search advertising reference entity value, step 4920.
[0224] In an embodiment illustrated in FIG. 50, a search
advertising reference entity framework 5002 may be applied as an
automated filter to the eligible pool of archived search
advertising transactions stored in a data warehouse 5000. In this
process, an advertising reference entity server 5004 may use the
search advertising reference entity framework 5002 as a filter or
search framework for drawing archived search advertising
transactions from the data warehouse 5000. The advertising
reference entity server 5004 may then use the sampled transaction
data in order to synthesize a search advertising reference entity
5006. The process of synthesizing the search reference entity may
involve calculating the indexed reference entity value of the
transactions sampled on the basis of the defined attribute values
contained in the search reference entity framework 5002. For
example, the indexed value may include a gross transaction size, a
gross revenue index, a net revenue index, and an effective unit
revenue index.
[0225] FIG. 51 illustrates a method in which a search advertising
reference entity is used as a search advertising market benchmark.
In this embodiment, a search advertising reference entity framework
5100 is used by a search advertising reference entity server 5102
to selectively sample electronic advertising transaction records
stored within a data warehouse 5104. The search advertising
reference entity server 5102 uses the sampled transaction data to
define a search advertising reference entity 5106. This reference
entity is then published as a search advertising reference entity
data publication 5108. The reference entity definition may also be
used to generate a search advertising reference entity data
syndication 5110. In this embodiment, the value of the search
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0226] FIG. 52 illustrates a method for using a single search
advertising product composite price as a search advertising product
composite price benchmark. In this process, search attribute values
which define a particular type of search advertising product are
used to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 5200. This
establishes a search advertising product composite price within the
identified sample transaction time frame. The search advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the search advertising product composite price
as a search advertising composite price benchmark for subsequent
transactions and operations, step 5202.
[0227] FIG. 53 illustrates a system network for identifying a set
of search advertising transactions to be extracted, transformed and
used to define a search advertising product composite price. Raw
search advertising transaction data may be obtained from a variety
of sources including, for example, agency search advertising buyer
data feeds 5300, search advertiser data feeds 5302, search
advertising server data feeds 5304, search advertising networks and
exchange data feeds 5306, and search publisher order management
system data feeds 5308. The raw search advertising transaction data
may be pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 5310, with the
resulting data provided to a search advertising product composite
pricing engine 5312. The search advertising product composite price
engine may include a volume-weighted composite price for sampled
search advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0228] As illustrated in FIG. 54, the output from the search
advertising product composite pricing engine, step 5400, may be
published as a search advertising product composite price
publication, step 5402, and syndicated as a search advertising
product composite price syndication, step 5404. The publication and
syndication of the search advertising product composite price may
be accomplished via a variety of publication and communication
mechanisms. The search advertising product composite price may also
be published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
search advertising product composite price may be archived using
any known archival methods and storage devices.
[0229] FIG. 55 illustrates steps of a method for establishing a
video advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
5500. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the video attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 5502. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with video advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a video advertising reference entity value, step
5504.
[0230] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"electronic display" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 5500 may be limited to transactions purchasing advertising in
video media, as illustrated in FIG. 56. For example, the data
sources used to collect advertising transactions may be limited to
agency electronics delayed media buyers data feeds 5600, video
advertisers data feeds 5602, video advertising server data feeds
5604, video advertising networks and exchanges data feeds 5606, and
video publisher order management system data feeds 5608.
Additionally, the advertising transaction data feeds may be
filtered by a video advertising reference entity data filter, step
5610. As mentioned above, the video advertising transaction data
received from the various data feeds may be preprocessed to remove
duplicate transaction records, step 5612. The preprocessed video
advertising transaction data may then be processed to transform
attribute information into attribute tier values and data records
stored in a database, step 5614.
[0231] In selecting video advertising transactions, advertising
transaction records may be selected based upon an advertising media
platform having a video advertising value. Examples of video
advertising attribute values include a digital medium, an analog
medium, an internet-enabled medium, a wireless medium, a social
medium, a satellite-based medium, a print medium, a broadcast
medium, a networked medium, a telephonic medium, a telepathic
medium, a brainwave medium, a recorded medium, a live medium, an
electronic display medium, an internet-enabled display medium, an
internet-enabled rich media display medium, an internet-enabled
text medium, an internet-enabled video medium, a social medium, an
internet-enabled social medium, a mobile display medium, a mobile
text medium, a mobile location based medium, a mobile video medium,
a mobile social medium, an internet-enabled search medium, a mobile
search medium, a video search medium, a video medium, a broadband
video medium, an internet protocol enabled broadband video medium,
a closed circuit video medium, a network served video medium, a
satellite-based video medium, an electronic game medium, an
internet-enabled game medium, a console game medium, a downloadable
game medium, a massively-multiplayer game medium, a public display
medium, an outdoor advertising medium, a radio medium, an Internet
Protocol radio medium, a satellite-broadcast radio medium, a
television medium, broadcast television medium, a spot television
medium, a cable television medium, a digitally recorded television
medium, an Internet Protocol Television (IPTV) broadcast medium, a
cable television medium, a studio produced medium, a syndicated
medium, a broadcast television medium, a filmed medium, a digitally
recorded filmed medium.
[0232] FIG. 57 illustrates in more detail steps involved in
organizing video advertising transaction records according to a
taxonomy of video advertising attributes. Advertising transaction
data selected via a video advertising reference entity data filter,
step 5710, may be preprocessed as described above, step 5702.
Information regarding consumer viewing of the video listed in video
advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 5704. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 5706, publisher data information
may be transformed into publisher tier attribute values, step 5708,
advertiser information may be transformed into advertiser tier
attribute values, step 5710, targeting package information may be
transformed into one or more targeting attribute tier values, step
5712, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
5716. The transformed video advertising transaction attribute
values may then be stored in a database or data warehouse, step
5718. The data stored in a database may then be used to determine
the video advertising reference entity value, step 5720.
[0233] In an embodiment illustrated in FIG. 58, a video advertising
reference entity framework 5802 may be applied as an automated
filter to the eligible pool of archived video advertising
transactions stored in a data warehouse 5800. In this process, an
advertising reference entity server 5804 may use the video
advertising reference entity framework 5802 as a filter or search
framework for drawing archived video advertising transactions from
the data warehouse 5800. The advertising reference entity server
5804 may then use the sampled transaction data in order to
synthesize a video advertising reference entity 5806. The process
of synthesizing the video reference entity may involve calculating
the indexed reference entity value of the transactions sampled on
the basis of the defined attribute values contained in the video
reference entity framework 5802. For example, the indexed value may
include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0234] FIG. 59 illustrates a method in which a video advertising
reference entity is used as a video advertising market benchmark.
In this embodiment, a video advertising reference entity framework
5900 is used by a video advertising reference entity server 5902 to
selectively sample electronic advertising transaction records
stored within a data warehouse 5904. The video advertising
reference entity server 5902 uses the sampled transaction data to
define a video advertising reference entity 5906. This reference
entity is then published as a video advertising reference entity
data publication 5908. The reference entity definition may also be
used to generate a video advertising reference entity data
syndication 5910. In this embodiment, the value of the video
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0235] FIG. 60 illustrates a method for using a single video
advertising product composite price as a video advertising product
composite price benchmark. In this process, video attribute values
which define a particular type of video advertising product are
used to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 6000. This
establishes a video advertising product composite price within the
identified sample transaction time frame. The video advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the video advertising product composite price
as a video advertising composite price benchmark for subsequent
transactions and operations, step 6002.
[0236] FIG. 61 illustrates a system network for identifying a set
of video advertising transactions to be extracted, transformed and
used to define a video advertising product composite price. Raw
video advertising transaction data may be obtained from a variety
of sources including, for example, agency video advertising buyer
data feeds 6100, video advertiser data feeds 6102, video
advertising server data feeds 6104, video advertising networks and
exchange data feeds 6106, and video publisher order management
system data feeds 6108. The raw video advertising transaction data
may be pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 6110, with the
resulting data provided to a video advertising product composite
pricing engine 6112. The video advertising product composite price
engine may include a volume-weighted composite price for sampled
video advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0237] As illustrated in FIG. 62, the output from the video
advertising product composite pricing engine, step 6200, may be
published as a video advertising product composite price
publication, step 6202, and syndicated as a video advertising
product composite price syndication, step 6204. The publication and
syndication of the video advertising product composite price may be
accomplished via a variety of publication and communication
mechanisms. The video advertising product composite price may also
be published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
video advertising product composite price may be archived using any
known archival methods and storage devices.
[0238] FIG. 63 illustrates steps of a method for establishing a
game advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
6300. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the game attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 6302. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with game advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a game advertising reference entity value, step 6304.
[0239] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"game" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 6300 may be
limited to transactions purchasing advertising in games and gaming
media, as illustrated in FIG. 64. For example, the data sources
used to collect advertising transactions may be limited to agency
electronics delayed media buyers data feeds 6400, game advertisers
data feeds 6402, game advertising server data feeds 6404, game
advertising networks and exchanges data feeds 6406, and game
publisher order management system data feeds 6408. Additionally,
the advertising transaction data feeds may be filtered by a game
advertising reference entity data filter, step 6410. As mentioned
above, the game advertising transaction data received from the
various data feeds may be preprocessed to remove duplicate
transaction records, step 6412. The preprocessed game advertising
transaction data may then be processed to transform attribute
information into attribute tier values and data records stored in a
database, step 6414.
[0240] In selecting game advertising transactions, advertising
transaction records may be selected based upon game publisher
classification having a game advertising value. Examples of game
advertising attribute values include a casual game type, a core
enthusiast game type, a networked game type, a static game type, a
downloadable game type, a multi-player game type, a massively
multiplayer game type, an advergame type, a strategy game type, a
first-person shooter game type, a fantasy role-playing game type, a
multi-location massively multi-player game type, a location-based
assassin game type, an assassin game type, a sports hero game type,
a music hero game type, an explorer hero game type, a war hero game
type, a criminal game type, a criminal pursuit game type, a
publisher-owned content type, a user-generated content type, a film
clip content type, a trailer content type, a short film content
type, a film content type, a television show content type, an
animation content type, and an instructional content type.
[0241] FIG. 65 illustrates in more detail steps involved in
organizing game advertising transaction records according to a
taxonomy of game advertising attributes. Advertising transaction
data selected via a game advertising reference entity data filter,
step 6510, may be preprocessed as described above, step 6502.
Information regarding purchase and usage of the game listed in game
advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 6504. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 6506, publisher data information
may be transformed into publisher tier attribute values, step 6508,
advertiser information may be transformed into advertiser tier
attribute values, step 6510, targeting package information may be
transformed into one or more targeting attribute tier values, step
6512, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
6516. The transformed game advertising transaction attribute values
may then be stored in a database or data warehouse, step 6518. The
data stored in a database may then be used to determine the game
advertising reference entity value, step 6520.
[0242] In an embodiment illustrated in FIG. 66, a game advertising
reference entity framework 6602 may be applied as an automated
filter to the eligible pool of archived game advertising
transactions stored in a data warehouse 6600. In this process, an
advertising reference entity server 6604 may use the game
advertising reference entity framework 6602 as a filter or search
framework for drawing archived game advertising transactions from
the data warehouse 6600. The advertising reference entity server
6604 may then use the sampled transaction data in order to
synthesize a game advertising reference entity 6606. The process of
synthesizing the game reference entity may involve calculating the
indexed reference entity value of the transactions sampled on the
basis of the defined attribute values contained in the game
reference entity framework 6602. For example, the indexed value may
include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0243] FIG. 67 illustrates a method in which a game advertising
reference entity is used as a game advertising market benchmark. In
this embodiment, a game advertising reference entity framework 6700
is used by a game advertising reference entity server 6702 to
selectively sample electronic advertising transaction records
stored within a data warehouse 6704. The game advertising reference
entity server 6702 uses the sampled transaction data to define a
game advertising reference entity 6706. This reference entity is
then published as a game advertising reference entity data
publication 6708. The reference entity definition may also be used
to generate a game advertising reference entity data syndication
6710. In this embodiment, the value of the game advertising
reference entity may be defined following a consistently defined
and executed advertising reference entity definition process with
the results published and syndicated.
[0244] FIG. 68 illustrates a method for using a single game
advertising product composite price as a game advertising product
composite price benchmark. In this process, game attribute values
which define a particular type of game advertising product are used
to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 6800. This
establishes a game advertising product composite price within the
identified sample transaction time frame. The game advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the game advertising product composite price
as a game advertising composite price benchmark for subsequent
transactions and operations, step 6802.
[0245] FIG. 69 illustrates a system network for identifying a set
of game advertising transactions to be extracted, transformed and
used to define a game advertising product composite price. Raw game
advertising transaction data may be obtained from a variety of
sources including, for example, agency game advertising buyer data
feeds 6900, game advertiser data feeds 6902, game advertising
server data feeds 6904, game advertising networks and exchange data
feeds 6906, and game publisher order management system data feeds
6908. The raw game advertising transaction data may be
pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 6910, with the
resulting data provided to a game advertising product composite
pricing engine 6912. The game advertising product composite price
engine may include a volume-weighted composite price for sampled
game advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0246] As illustrated in FIG. 70, the output from the game
advertising product composite pricing engine, step 7000, may be
published as a game advertising product composite price
publication, step 7002, and syndicated as a game advertising
product composite price syndication, step 7004. The publication and
syndication of the game advertising product composite price may be
accomplished via a variety of publication and communication
mechanisms. The game advertising product composite price may also
be published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
game advertising product composite price may be archived using any
known archival methods and storage devices.
[0247] FIG. 71 illustrates steps of a method for establishing a
public display advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
7100. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the public display attribute
value, a subset of advertising transaction records are selected
within the database for processing, step 7102. The identified
targeted attribute values may include single attributes or
combinations of attributes associated with public display
advertising transactions. The sampled advertising transaction
records are then aggregated to establish a public display
advertising reference entity value, step 7204.
[0248] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"public display" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 7100 may be limited to transactions purchasing advertising in
public display media, as illustrated in FIG. 72. For example, the
data sources used to collect advertising transactions may be
limited to agency electronics delayed media buyers data feeds 7200,
public display advertisers data feeds 7202, public display
advertising server data feeds 7204, public display advertising
networks and exchanges data feeds 7206, and public display
publisher order management system data feeds 7208. Additionally,
the advertising transaction data feeds may be filtered by a public
display advertising reference entity data filter, step 7210. As
mentioned above, the public display advertising transaction data
received from the various data feeds may be preprocessed to remove
duplicate transaction records, step 7212. The preprocessed public
display advertising transaction data may then be processed to
transform attribute information into attribute tier values and data
records stored in a database, step 7214.
[0249] FIG. 73 illustrates in more detail steps involved in
organizing public display advertising transaction records according
to a taxonomy of public display advertising attributes. Advertising
transaction data selected via a public display advertising
reference entity data filter, step 7310, may be preprocessed as
described above, step 7302. Information regarding consumer viewings
of public displays listed in public display advertising
transactions may be obtained from ratings bureau databases (e.g.,
Quantcast.com and Nielsen), websites and other such data feeds,
step 7304. This data may be combined to transform the information
from advertising transactions into attribute values and attribute
tier values as described above with reference to FIG. 3A, 3B. For
example, a product data may be transformed into a product attribute
tier value, step 7306, publisher data information may be
transformed into publisher tier attribute values, step 7308,
advertiser information may be transformed into advertiser tier
attribute values, step 7310, targeting package information may be
transformed into one or more targeting attribute tier values, step
7312, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
7316. The transformed public display advertising transaction
attribute values may then be stored in a database or data
warehouse, step 7318. The data stored in a database may then be
used to determine the public display advertising reference entity
value, step 7320.
[0250] In an embodiment illustrated in FIG. 74, a public display
advertising reference entity framework 7402 may be applied as an
automated filter to the eligible pool of archived public display
advertising transactions stored in a data warehouse 3400. In this
process, an advertising reference entity server 7404 may use the
public display advertising reference entity framework 7402 as a
filter or search framework for drawing archived public display
advertising transactions from the data warehouse 7400. The
advertising reference entity server 7404 may then use the sampled
transaction data in order to synthesize a public display
advertising reference entity 7406. The process of synthesizing the
public display reference entity may involve calculating the indexed
reference entity value of the transactions sampled on the basis of
the defined attribute values contained in the public display
reference entity framework 7402. For example, the indexed value may
include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0251] FIG. 75 illustrates a method in which a public display
advertising reference entity is used as a public display
advertising market benchmark. In this embodiment, a public display
advertising reference entity framework 7500 is used by a public
display advertising reference entity server 7502 to selectively
sample electronic advertising transaction records stored within a
data warehouse 7504. The public display advertising reference
entity server 7502 uses the sampled transaction data to define a
public display advertising reference entity 7506. This reference
entity is then published as a public display advertising reference
entity data publication 7508. The reference entity definition may
also be used to generate a public display advertising reference
entity data syndication 7510. In this embodiment, the value of the
public display advertising reference entity may be defined
following a consistently defined and executed advertising reference
entity definition process with the results published and
syndicated.
[0252] FIG. 76 illustrates a method for using a single public
display advertising product composite price as a public display
advertising product composite price benchmark. In this process,
public display attribute values which define a particular type of
public display advertising product are used to sample an
advertising transaction data warehouse to extract advertising
transaction records associated with a type of advertising product
over a period of time, with that data used to determine an
advertising composite price, step 7600. This establishes a public
display advertising product composite price within the identified
sample transaction time frame. The public display advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the public display advertising product
composite price as a public display advertising composite price
benchmark for subsequent transactions and operations, step
7602.
[0253] FIG. 77 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a public display advertising product composite price. Raw
public display advertising transaction data may be obtained from a
variety of sources including, for example, agency public display
advertising buyer data feeds 7700, public display advertiser data
feeds 7702, public display advertising server data feeds 7704,
public display advertising networks and exchange data feeds 7706,
and public display publisher order management system data feeds
7708. The raw public display advertising transaction data may be
pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 7710, with the
resulting data provided to a public display advertising product
composite pricing engine 7712. The public display advertising
product composite price engine may include a volume-weighted
composite price for sampled public display advertising products of
the identified attribute values conducted within an identify
transaction time frame.
[0254] As illustrated in FIG. 78, the output from the public
display advertising product composite pricing engine, step 7800,
may be published as a public display advertising product composite
price publication, step 7802, and syndicated as a public display
advertising product composite price syndication, step 7804. The
publication and syndication of the public display advertising
product composite price may be accomplished via a variety of
publication and communication mechanisms. The public display
advertising product composite price may also be published in
syndicated via closed, open and public networks as well as
communications among market participants. Additionally, the public
display advertising product composite price may be archived using
any known archival methods and storage devices.
[0255] FIG. 79 illustrates steps of a method for establishing an
outdoor advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
7900. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the outdoor attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 7902. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with outdoor advertising transactions. The
sampled advertising transaction records are then aggregated to
establish an outdoor advertising reference entity value, step
7904.
[0256] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"outdoor" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 7900 may be
limited to transactions purchasing outdoor advertising, as
illustrated in FIG. 80. For example, the data sources used to
collect advertising transactions may be limited to agency
electronics delayed media buyers data feeds 8000, outdoor
advertisers data feeds 8002, outdoor advertising server data feeds
8004, outdoor advertising networks and exchanges data feeds 8006,
and outdoor publisher order management system data feeds 8008.
Additionally, the advertising transaction data feeds may be
filtered by an outdoor advertising reference entity data filter,
step 8010. As mentioned above, the outdoor advertising transaction
data received from the various data feeds may be preprocessed to
remove duplicate transaction records, step 8012. The preprocessed
outdoor advertising transaction data may then be processed to
transform attribute information into attribute tier values and data
records stored in a database, step 8014.
[0257] FIG. 81 illustrates in more detail steps involved in
organizing outdoor advertising transaction records according to a
taxonomy of outdoor advertising attributes. Advertising transaction
data selected via an outdoor advertising reference entity data
filter, step 8110, may be preprocessed as described above, step
8102. Information regarding consumer exposure to outdoor displays
listed in outdoor advertising transactions may be obtained from
ratings bureau databases (e.g., Quantcast.com and Nielsen),
websites and other such data feeds, step 8104. This data may be
combined to transform the information from advertising transactions
into attribute values and attribute tier values as described above
with reference to FIG. 3A, 3B. For example, a product data may be
transformed into a product attribute tier value, step 8106,
publisher data information may be transformed into publisher tier
attribute values, step 8108, advertiser information may be
transformed into advertiser tier attribute values, step 8110,
targeting package information may be transformed into one or more
targeting attribute tier values, step 8112, flight information may
be transformed into advertising product flight attribute values,
and revenue information may be transformed into one or more revenue
attribute tier values, step 8116. The transformed outdoor
advertising transaction attribute values may then be stored in a
database or data warehouse, step 8118. The data stored in a
database may then be used to determine the outdoor advertising
reference entity value, step 8120.
[0258] In an embodiment illustrated in FIG. 82, an outdoor
advertising reference entity framework 3402 may be applied as an
automated filter to the eligible pool of archived outdoor
advertising transactions stored in a data warehouse 8200. In this
process, an advertising reference entity server 8204 may use the
outdoor advertising reference entity framework 8202 as a filter or
search framework for drawing archived outdoor advertising
transactions from the data warehouse 8200. Outdoor advertising may
be identified or filtered based upon display attributes including
for example a billboard attribute, a taxi display attribute, a
building attribute, a location attribute, an on-taxi display
attribute, a bus-side display attribute, a transportation vehicle
display attribute, a video board attribute, an LED board attribute,
an on-building display attribute, a wall display attribute, a
transportation location display attribute, a bench display
attribute, a roadside display attribute, a sign attribute, and the
like. The advertising reference entity server 8204 may then use the
sampled transaction data in order to synthesize an outdoor
advertising reference entity 8206. The process of synthesizing the
outdoor reference entity may involve calculating the indexed
reference entity value of the transactions sampled on the basis of
the defined attribute values contained in the outdoor reference
entity framework 8202. For example, the indexed value may include a
gross transaction size, a gross revenue index, a net revenue index,
and an effective unit revenue index.
[0259] FIG. 83 illustrates a method in which an outdoor advertising
reference entity is used as an outdoor advertising market
benchmark. In this embodiment, an outdoor advertising reference
entity framework 8300 is used by an outdoor advertising reference
entity server 8302 to selectively sample electronic advertising
transaction records stored within a data warehouse 8304. The
outdoor advertising reference entity server 8302 uses the sampled
transaction data to define an outdoor advertising reference entity
8306. This reference entity is then published as an outdoor
advertising reference entity data publication 8308. The reference
entity definition may also be used to generate an outdoor
advertising reference entity data syndication 8310. In this
embodiment, the value of the outdoor advertising reference entity
may be defined following a consistently defined and executed
advertising reference entity definition process with the results
published and syndicated.
[0260] FIG. 84 illustrates a method for using a single outdoor
advertising product composite price as an outdoor advertising
product composite price benchmark. In this process, outdoor
attribute values which define a particular type of outdoor
advertising product are used to sample an advertising transaction
data warehouse to extract advertising transaction records
associated with a type of advertising product over a period of
time, with that data used to determine an advertising composite
price, step 8400. This establishes an outdoor advertising product
composite price within the identified sample transaction time
frame. The outdoor advertising product composite price may then be
published to the marketplace on a timely and consistent basis with
the publication syndicated, thereby establishing the outdoor
advertising product composite price as an outdoor advertising
composite price benchmark for subsequent transactions and
operations, step 8402.
[0261] FIG. 85 illustrates a system network for identifying a set
of outdoor advertising transactions to be extracted, transformed
and used to define an outdoor advertising product composite price.
Raw outdoor advertising transaction data may be obtained from a
variety of sources including, for example, agency outdoor
advertising buyer data feeds 8500, outdoor advertiser data feeds
8502, outdoor advertising server data feeds 8504, outdoor
advertising networks and exchange data feeds 8506, and outdoor
publisher order management system data feeds 3708. The raw outdoor
advertising transaction data may be pre-processed to remove
duplicates and otherwise transform attribute values into attribute
tier values, step 8510, with the resulting data provided to an
outdoor advertising product composite pricing engine 8512. The
outdoor advertising product composite price engine may include a
volume-weighted composite price for sampled outdoor advertising
products of the identified attribute values conducted within an
identify transaction time frame.
[0262] As illustrated in FIG. 86, the output from the outdoor
advertising product composite pricing engine, step 8600, may be
published as an outdoor advertising product composite price
publication, step 8602, and syndicated as an outdoor advertising
product composite price syndication, step 8604. The publication and
syndication of the outdoor advertising product composite price may
be accomplished via a variety of publication and communication
mechanisms. The outdoor advertising product composite price may
also be published in syndicated via closed, open and public
networks as well as communications among market participants.
Additionally, the outdoor advertising product composite price may
be archived using any known archival methods and storage
devices.
[0263] FIG. 87 illustrates steps of a method for establishing a
print advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
8700. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the print attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 8702. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with print advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a print advertising reference entity value, step
8704.
[0264] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"print" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 8700 may be
limited to transactions purchasing advertising and in printed
media, as illustrated in FIG. 88. For example, the data sources
used to collect advertising transactions may be limited to agency
electronics delayed media buyers data feeds 8800, print advertisers
data feeds 8802, print advertising server data feeds 8804, print
advertising networks and exchanges data feeds 8806, and print
publisher order management system data feeds 8808. Additionally,
the advertising transaction data feeds may be filtered by a print
advertising reference entity data filter, step 8810. As mentioned
above, the print advertising transaction data received from the
various data feeds may be preprocessed to remove duplicate
transaction records, step 8812. The preprocessed print advertising
transaction data may then be processed to transform attribute
information into attribute tier values and data records stored in a
database, step 8814.
[0265] FIG. 89 illustrates in more detail steps involved in
organizing print advertising transaction records according to a
taxonomy of print advertising attributes. Advertising transaction
data selected via a print advertising reference entity data filter,
step 8910, may be preprocessed as described above, step 8902.
Information regarding readership of print publications listed in
print advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 8904. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 8906, publisher data information
may be transformed into publisher tier attribute values, step 8908,
advertiser information may be transformed into advertiser tier
attribute values, step 8910, targeting package information may be
transformed into one or more targeting attribute tier values, step
8912, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
8916. The transformed print advertising transaction attribute
values may then be stored in a database or data warehouse, step
8918. The data stored in a database may then be used to determine
the print advertising reference entity value, step 8920.
[0266] In an embodiment illustrated in FIG. 90, a print advertising
reference entity framework 9002 may be applied as an automated
filter to the eligible pool of archived print advertising
transactions stored in a data warehouse 9000. In this process, an
advertising reference entity server 9004 may use the print
advertising reference entity framework 9002 as a filter or search
framework for drawing archived print advertising transactions from
the data warehouse 9000. The advertising reference entity server
9004 may then use the sampled transaction data in order to
synthesize a print advertising reference entity 9006. The process
of synthesizing the print reference entity may involve calculating
the indexed reference entity value of the transactions sampled on
the basis of the defined attribute values contained in the print
reference entity framework 9002. For example, the indexed value may
include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0267] FIG. 91 illustrates a method in which a print advertising
reference entity is used as a print advertising market benchmark.
In this embodiment, a print advertising reference entity framework
9100 is used by a print advertising reference entity server 9102 to
selectively sample electronic advertising transaction records
stored within a data warehouse 9104. The print advertising
reference entity server 9102 uses the sampled transaction data to
define a print advertising reference entity 9106. This reference
entity is then published as a print advertising reference entity
data publication 9108. The reference entity definition may also be
used to generate a print advertising reference entity data
syndication 9110. In this embodiment, the value of the print
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0268] FIG. 92 illustrates a method for using a single print
advertising product composite price as a print advertising product
composite price benchmark. In this process, print attribute values
which define a particular type of print advertising product are
used to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 9200. This
establishes a print advertising product composite price within the
identified sample transaction time frame. The print advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the print advertising product composite price
as a print advertising composite price benchmark for subsequent
transactions and operations, step 9202.
[0269] FIG. 93 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a print advertising product composite price. Raw print
advertising transaction data may be obtained from a variety of
sources including, for example, agency print advertising buyer data
feeds 9300, print advertiser data feeds 9302, print advertising
server data feeds 9304, print advertising networks and exchange
data feeds 9306, and print publisher order management system data
feeds 9308. The raw print advertising transaction data may be
pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 9310, with the
resulting data provided to a print advertising product composite
pricing engine 9312. The print advertising product composite price
engine may include a volume-weighted composite price for sampled
print advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0270] As illustrated in FIG. 94, the output from the print
advertising product composite pricing engine, step 9400, may be
published as a print advertising product composite price
publication, step 9402, and syndicated as a public display
advertising product composite price syndication, step 9404. The
publication and syndication of the print advertising product
composite price may be accomplished via a variety of publication
and communication mechanisms. The print advertising product
composite price may also be published in syndicated via closed,
open and public networks as well as communications among market
participants. Additionally, the print advertising product composite
price may be archived using any known archival methods and storage
devices.
[0271] FIG. 95 illustrates steps of a method for establishing a
radio advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
9500. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the radio attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 9502. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with radio advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a radio advertising reference entity value, step
9504.
[0272] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"radio" (or a corresponding attribute ID value) as the selection
value for the advertising medium attribute. Alternatively, the
advertising transactions that are captured in step 9500 may be
limited to transactions purchasing radio advertising, as
illustrated in FIG. 96. For example, the data sources used to
collect advertising transactions may be limited to agency
electronics delayed media buyers data feeds 9600, radio advertisers
data feeds 9602, radio advertising server data feeds 9604, radio
advertising networks and exchanges data feeds 9606, and radio
publisher order management system data feeds 9608. Additionally,
the advertising transaction data feeds may be filtered by a radio
advertising reference entity data filter, step 9610. As mentioned
above, the radio advertising transaction data received from the
various data feeds may be preprocessed to remove duplicate
transaction records, step 9612. The preprocessed radio advertising
transaction data may then be processed to transform attribute
information into attribute tier values and data records stored in a
database, step 9614.
[0273] FIG. 97 illustrates in more detail steps involved in
organizing radio advertising transaction records according to a
taxonomy of radio advertising attributes. Advertising transaction
data selected via a radio advertising reference entity data filter,
step 9710, may be preprocessed as described above, step 9702.
Information regarding the audience of radio stations listed in
radio advertising transactions may be obtained from ratings bureau
databases (e.g., Quantcast.com and Nielsen), websites and other
such data feeds, step 9704. This data may be combined to transform
the information from advertising transactions into attribute values
and attribute tier values as described above with reference to FIG.
3A, 3B. For example, a product data may be transformed into a
product attribute tier value, step 9706, publisher data information
may be transformed into publisher tier attribute values, step 9708,
advertiser information may be transformed into advertiser tier
attribute values, step 9710, targeting package information may be
transformed into one or more targeting attribute tier values, step
9712, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
9716. The transformed radio advertising transaction attribute
values may then be stored in a database or data warehouse, step
9718. The data stored in a database may then be used to determine
the radio advertising reference entity value, step 9720.
[0274] In an embodiment illustrated in FIG. 98, a radio advertising
reference entity framework 9802 may be applied as an automated
filter to the eligible pool of archived radio advertising
transactions stored in a data warehouse 9800. In this process, an
advertising reference entity server 9804 may use the radio
advertising reference entity framework 9802 as a filter or search
framework for drawing archived radio advertising transactions from
the data warehouse 9800. The advertising reference entity server
9804 may then use the sampled transaction data in order to
synthesize a radio advertising reference entity 9806. The process
of synthesizing the radio reference entity may involve calculating
the indexed reference entity value of the transactions sampled on
the basis of the defined attribute values contained in the radio
reference entity framework 9802. For example, the indexed value may
include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0275] FIG. 99 illustrates a method in which a radio advertising
reference entity is used as a radio advertising market benchmark.
In this embodiment, a radio advertising reference entity framework
9900 is used by a radio advertising reference entity server 9902 to
selectively sample electronic advertising transaction records
stored within a data warehouse 9904. The radio advertising
reference entity server 9902 uses the sampled transaction data to
define a radio advertising reference entity 9906. This reference
entity is then published as a radio advertising reference entity
data publication 9908. The reference entity definition may also be
used to generate a radio advertising reference entity data
syndication 9910. In this embodiment, the value of the radio
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0276] FIG. 100 illustrates a method for using a single radio
advertising product composite price as a radio advertising product
composite price benchmark. In this process, radio attribute values
which define a particular type of radio advertising product are
used to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 10000. This
establishes a radio advertising product composite price within the
identified sample transaction time frame. The radio advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the radio advertising product composite price
as a radio advertising composite price benchmark for subsequent
transactions and operations, step 10002.
[0277] FIG. 101 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a radio advertising product composite price. Raw radio
advertising transaction data may be obtained from a variety of
sources including, for example, agency radio advertising buyer data
feeds 10000, radio advertiser data feeds 10102, radio advertising
server data feeds 10104, radio advertising networks and exchange
data feeds 10106, and radio publisher order management system data
feeds 10108. The raw radio advertising transaction data may be
pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 10110, with the
resulting data provided to a radio advertising product composite
pricing engine 10112. The radio advertising product composite price
engine may include a volume-weighted composite price for sampled
radio advertising products of the identified attribute values
conducted within an identify transaction time frame.
[0278] As illustrated in FIG. 102, the output from the radio
advertising product composite pricing engine, step 10200, may be
published as a radio advertising product composite price
publication, step 10202, and syndicated as a radio advertising
product composite price syndication, step 10204. The publication
and syndication of the radio advertising product composite price
may be accomplished via a variety of publication and communication
mechanisms. The radio advertising product composite price may also
be published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
radio advertising product composite price may be archived using any
known archival methods and storage devices.
[0279] FIG. 103 illustrates steps of a method for establishing a
television advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
10300. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the television attribute value, a
subset of advertising transaction records are selected within the
database for processing, step 10302. The identified targeted
attribute values may include single attributes or combinations of
attributes associated with television advertising transactions. The
sampled advertising transaction records are then aggregated to
establish a television advertising reference entity value, step
10304.
[0280] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"television" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 10300 may be limited to transactions purchasing television
advertising, as illustrated in FIG. 104. For example, the data
sources used to collect advertising transactions may be limited to
agency electronics delayed media buyers data feeds 10400,
television advertisers data feeds 10402, television advertising
server data feeds 10404, television advertising networks and
exchanges data feeds 10406, and television publisher order
management system data feeds 10408. Additionally, the advertising
transaction data feeds may be filtered by a television advertising
reference entity data filter, step 10410. As mentioned above, the
television advertising transaction data received from the various
data feeds may be preprocessed to remove duplicate transaction
records, step 10412. The preprocessed television advertising
transaction data may then be processed to transform attribute
information into attribute tier values and data records stored in a
database, step 10414.
[0281] FIG. 105 illustrates in more detail steps involved in
organizing television advertising transaction records according to
a taxonomy of television advertising attributes. Advertising
transaction data selected via a television advertising reference
entity data filter, step 10510, may be preprocessed as described
above, step 10502. Information regarding viewership of television
networks and programs listed in television advertising transactions
may be obtained from ratings bureau databases (e.g., Quantcast.com
and Nielsen), websites and other such data feeds, step 10504. This
data may be combined to transform the information from advertising
transactions into attribute values and attribute tier values as
described above with reference to FIG. 3A, 3B. For example, a
product data may be transformed into a product attribute tier
value, step 10506, publisher data information may be transformed
into publisher tier attribute values, step 10508, advertiser
information may be transformed into advertiser tier attribute
values, step 10510, targeting package information may be
transformed into one or more targeting attribute tier values, step
10512, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
10516. The transformed television advertising transaction attribute
values may then be stored in a database or data warehouse, step
10518. The data stored in a database may then be used to determine
the television advertising reference entity value, step 10520.
[0282] In an embodiment illustrated in FIG. 106, a television
advertising reference entity framework 10602 may be applied as an
automated filter to the eligible pool of archived television
advertising transactions stored in a data warehouse 10600. In this
process, an advertising reference entity server 10604 may use the
television advertising reference entity framework 10602 as a filter
or search framework for drawing archived television advertising
transactions from the data warehouse 10600. The advertising
reference entity server 10604 may then use the sampled transaction
data in order to synthesize a television advertising reference
entity 10606. The process of synthesizing the television reference
entity may involve calculating the indexed reference entity value
of the transactions sampled on the basis of the defined attribute
values contained in the television reference entity framework
10602. For example, the indexed value may include a gross
transaction size, a gross revenue index, a net revenue index, and
an effective unit revenue index.
[0283] FIG. 107 illustrates a method in which a television
advertising reference entity is used as a television advertising
market benchmark. In this embodiment, a television advertising
reference entity framework 10700 is used by a television
advertising reference entity server 10702 to selectively sample
electronic advertising transaction records stored within a data
warehouse 10704. The television advertising reference entity server
10702 uses the sampled transaction data to define a television
advertising reference entity 10706. This reference entity is then
published as a television advertising reference entity data
publication 10708. The reference entity definition may also be used
to generate a television advertising reference entity data
syndication 10710. In this embodiment, the value of the television
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0284] FIG. 108 illustrates a method for using a single television
advertising product composite price as a television advertising
product composite price benchmark. In this process, television
attribute values which define a particular type of television
advertising product are used to sample an advertising transaction
data warehouse to extract advertising transaction records
associated with a type of advertising product over a period of
time, with that data used to determine an advertising composite
price, step 10800. This establishes a television advertising
product composite price within the identified sample transaction
time frame. The television advertising product composite price may
then be published to the marketplace on a timely and consistent
basis with the publication syndicated, thereby establishing the
television advertising product composite price as a television
advertising composite price benchmark for subsequent transactions
and operations, step 10802.
[0285] FIG. 109 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a television advertising product composite price. Raw
television advertising transaction data may be obtained from a
variety of sources including, for example, agency television
advertising buyer data feeds 10900, television advertiser data
feeds 10902, television advertising server data feeds 10904,
television advertising networks and exchange data feeds 10906, and
television publisher order management system data feeds 10908. The
raw television advertising transaction data may be pre-processed to
remove duplicates and otherwise transform attribute values into
attribute tier values, step 10910, with the resulting data provided
to a television advertising product composite pricing engine 10912.
The television advertising product composite price engine may
include a volume-weighted composite price for sampled television
advertising products of the identified attribute values conducted
within an identify transaction time frame.
[0286] As illustrated in FIG. 110, the output from the television
advertising product composite pricing engine, step 11000, may be
published as a television advertising product composite price
publication, step 11002, and syndicated as a television advertising
product composite price syndication, step 11004. The publication
and syndication of the television advertising product composite
price may be accomplished via a variety of publication and
communication mechanisms. The television advertising product
composite price may also be published in syndicated via closed,
open and public networks as well as communications among market
participants. Additionally, the television advertising product
composite price may be archived using any known archival methods
and storage devices.
[0287] FIG. 111 illustrates steps of a method for establishing a
direct marketing advertising reference entity by aggregating
selected transactions. As described above with reference to FIGS.
2-5, a plurality of advertising transactions are captured from any
of a variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
11100. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the direct marketing attribute
value, a subset of advertising transaction records are selected
within the database for processing, step 11102. The identified
targeted attribute values may include single attributes or
combinations of attributes associated with direct marketing
advertising transactions. The sampled advertising transaction
records are then aggregated to establish a direct marketing
advertising reference entity value, step 11104.
[0288] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"direct marketing" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 11100 may be limited to transactions purchasing direct
marketing advertising services, as illustrated in FIG. 112. For
example, the data sources used to collect advertising transactions
may be limited to agency electronics delayed media buyers data
feeds 11200, direct marketing advertisers data feeds 11202, direct
marketing advertising server data feeds 11204, direct marketing
advertising networks and exchanges data feeds 11206, and direct
marketing publisher order management system data feeds 11208.
Additionally, the advertising transaction data feeds may be
filtered by a direct marketing advertising reference entity data
filter, step 11210. As mentioned above, the direct marketing
advertising transaction data received from the various data feeds
may be preprocessed to remove duplicate transaction records, step
11212. The preprocessed direct marketing advertising transaction
data may then be processed to transform attribute information into
attribute tier values and data records stored in a database, step
11214.
[0289] FIG. 113 illustrates in more detail steps involved in
organizing direct marketing advertising transaction records
according to a taxonomy of direct marketing advertising attributes.
Advertising transaction data selected via a direct marketing
advertising reference entity data filter, step 11310, may be
preprocessed as described above, step 11302. Information regarding
effectiveness of direct marketing entities listed in direct
marketing advertising transactions may be obtained from ratings
bureau databases (e.g., Quantcast.com and Nielsen), websites and
other such data feeds, step 11304. This data may be combined to
transform the information from advertising transactions into
attribute values and attribute tier values as described above with
reference to FIG. 3A, 3B. For example, a product data may be
transformed into a product attribute tier value, step 11306,
publisher data information may be transformed into publisher tier
attribute values, step 11308, advertiser information may be
transformed into advertiser tier attribute values, step 11310,
targeting package information may be transformed into one or more
targeting attribute tier values, step 11312, flight information may
be transformed into advertising product flight attribute values,
and revenue information may be transformed into one or more revenue
attribute tier values, step 11316. The transformed direct marketing
advertising transaction attribute values may then be stored in a
database or data warehouse, step 11318. The data stored in a
database may then be used to determine the direct marketing
advertising reference entity value, step 11320.
[0290] In an embodiment illustrated in FIG. 114, a direct marketing
advertising reference entity framework 11402 may be applied as an
automated filter to the eligible pool of archived direct marketing
advertising transactions stored in a data warehouse 11400. In this
process, an advertising reference entity server 11404 may use the
direct marketing advertising reference entity framework 11402 as a
filter or search framework for drawing archived direct marketing
advertising transactions from the data warehouse 11400. The
advertising reference entity server 11404 may then use the sampled
transaction data in order to synthesize a direct marketing
advertising reference entity 11406. The process of synthesizing the
direct marketing reference entity may involve calculating the
indexed reference entity value of the transactions sampled on the
basis of the defined attribute values contained in the direct
marketing reference entity framework 11402. For example, the
indexed value may include a gross transaction size, a gross revenue
index, a net revenue index, and an effective unit revenue
index.
[0291] FIG. 115 illustrates a method in which a direct marketing
advertising reference entity is used as a direct marketing
advertising market benchmark. In this embodiment, a direct
marketing advertising reference entity framework 11500 is used by a
direct marketing advertising reference entity server 11502 to
selectively sample electronic advertising transaction records
stored within a data warehouse 11504. The direct marketing
advertising reference entity server 11502 uses the sampled
transaction data to define a direct marketing advertising reference
entity 11506. This reference entity is then published as a direct
marketing advertising reference entity data publication 11508. The
reference entity definition may also be used to generate a direct
marketing advertising reference entity data syndication 11510. In
this embodiment, the value of the direct marketing advertising
reference entity may be defined following a consistently defined
and executed advertising reference entity definition process with
the results published and syndicated.
[0292] FIG. 116 illustrates a method for using a single direct
marketing advertising product composite price as a direct marketing
advertising product composite price benchmark. In this process,
direct marketing attribute values which define a particular type of
direct marketing advertising product are used to sample an
advertising transaction data warehouse to extract advertising
transaction records associated with a type of advertising product
over a period of time, with that data used to determine an
advertising composite price, step 11600. This establishes a direct
marketing advertising product composite price within the identified
sample transaction time frame. The direct marketing advertising
product composite price may then be published to the marketplace on
a timely and consistent basis with the publication syndicated,
thereby establishing the direct marketing advertising product
composite price as a direct marketing advertising composite price
benchmark for subsequent transactions and operations, step
11602.
[0293] FIG. 117 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a direct marketing advertising product composite price.
Raw direct marketing advertising transaction data may be obtained
from a variety of sources including, for example, agency direct
marketing advertising buyer data feeds 11700, direct marketing
advertiser data feeds 11702, direct marketing advertising server
data feeds 11704, direct marketing advertising networks and
exchange data feeds 11706, and direct marketing publisher order
management system data feeds 11708. The raw direct marketing
advertising transaction data may be pre-processed to remove
duplicates and otherwise transform attribute values into attribute
tier values, step 11710, with the resulting data provided to a
direct marketing advertising product composite pricing engine
11712. The direct marketing advertising product composite price
engine may include a volume-weighted composite price for sampled
direct marketing advertising products of the identified attribute
values conducted within an identify transaction time frame.
[0294] As illustrated in FIG. 118, the output from the direct
marketing advertising product composite pricing engine, step 11800,
may be published as a direct marketing advertising product
composite price publication, step 11802, and syndicated as a direct
marketing advertising product composite price syndication, step
11804. The publication and syndication of the direct marketing
advertising product composite price may be accomplished via a
variety of publication and communication mechanisms. The direct
marketing advertising product composite price may also be published
in syndicated via closed, open and public networks as well as
communications among market participants. Additionally, the direct
marketing advertising product composite price may be archived using
any known archival methods and storage devices.
[0295] FIG. 119 illustrates steps of a method for establishing a
telemarketing advertising reference entity by aggregating selected
transactions. As described above with reference to FIGS. 2-5, a
plurality of advertising transactions are captured from any of a
variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
11900. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the telemarketing attribute
value, a subset of advertising transaction records are selected
within the database for processing, step 11902. The identified
targeted attribute values may include single attributes or
combinations of attributes associated with telemarketing
advertising transactions. The sampled advertising transaction
records are then aggregated to establish a telemarketing
advertising reference entity value, step 11904.
[0296] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"telemarketing" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 11900 may be limited to transactions purchasing telemarketing
advertising and telemarketing services, as illustrated in FIG. 120.
For example, the data sources used to collect advertising
transactions may be limited to agency electronics delayed media
buyers data feeds 12000, telemarketing advertisers data feeds
12002, telemarketing advertising server data feeds 12004,
telemarketing advertising networks and exchanges data feeds 12006,
and telemarketing publisher order management system data feeds
12808. Additionally, the advertising transaction data feeds may be
filtered by a telemarketing advertising reference entity data
filter, step 12010. As mentioned above, the telemarketing
advertising transaction data received from the various data feeds
may be preprocessed to remove duplicate transaction records, step
12012. The preprocessed telemarketing advertising transaction data
may then be processed to transform attribute information into
attribute tier values and data records stored in a database, step
12014.
[0297] FIG. 121 illustrates in more detail steps involved in
organizing telemarketing advertising transaction records according
to a taxonomy of telemarketing advertising attributes. Advertising
transaction data selected via a telemarketing advertising reference
entity data filter, step 12110, may be preprocessed as described
above, step 12102. Information regarding the effectiveness of
telemarketing entities listed in telemarketing advertising
transactions may be obtained from ratings bureau databases (e.g.,
Quantcast.com and Nielsen), websites and other such data feeds,
step 12104. This data may be combined to transform the information
from advertising transactions into attribute values and attribute
tier values as described above with reference to FIG. 3A, 3B. For
example, a product data may be transformed into a product attribute
tier value, step 12106, publisher data information may be
transformed into publisher tier attribute values, step 12108,
advertiser information may be transformed into advertiser tier
attribute values, step 12110, targeting package information may be
transformed into one or more targeting attribute tier values, step
12112, flight information may be transformed into advertising
product flight attribute values, and revenue information may be
transformed into one or more revenue attribute tier values, step
12116. The transformed telemarketing advertising transaction
attribute values may then be stored in a database or data
warehouse, step 12118. The data stored in a database may then be
used to determine the telemarketing advertising reference entity
value, step 12120.
[0298] In an embodiment illustrated in FIG. 122, a telemarketing
advertising reference entity framework 12202 may be applied as an
automated filter to the eligible pool of archived telemarketing
advertising transactions stored in a data warehouse 12200. In this
process, an advertising reference entity server 12204 may use the
telemarketing advertising reference entity framework 12202 as a
filter or search framework for drawing archived telemarketing
advertising transactions from the data warehouse 12200. The
advertising reference entity server 13004 may then use the sampled
transaction data in order to synthesize a telemarketing advertising
reference entity 12206. The process of synthesizing the
telemarketing reference entity may involve calculating the indexed
reference entity value of the transactions sampled on the basis of
the defined attribute values contained in the telemarketing
reference entity framework 12202. For example, the indexed value
may include a gross transaction size, a gross revenue index, a net
revenue index, and an effective unit revenue index.
[0299] FIG. 123 illustrates a method in which a telemarketing
advertising reference entity is used as a telemarketing advertising
market benchmark. In this embodiment, a telemarketing advertising
reference entity framework 12300 is used by a telemarketing
advertising reference entity server 12302 to selectively sample
electronic advertising transaction records stored within a data
warehouse 12304. The telemarketing advertising reference entity
server 12302 uses the sampled transaction data to define a
telemarketing advertising reference entity 12306. This reference
entity is then published as a telemarketing advertising reference
entity data publication 12308. The reference entity definition may
also be used to generate a telemarketing advertising reference
entity data syndication 12310. In this embodiment, the value of the
telemarketing advertising reference entity may be defined following
a consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0300] FIG. 124 illustrates a method for using a single
telemarketing advertising product composite price as a
telemarketing advertising product composite price benchmark. In
this process, telemarketing attribute values which define a
particular type of telemarketing advertising product are used to
sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 12400. This
establishes a telemarketing advertising product composite price
within the identified sample transaction time frame. The
telemarketing advertising product composite price may then be
published to the marketplace on a timely and consistent basis with
the publication syndicated, thereby establishing the telemarketing
advertising product composite price as a telemarketing advertising
composite price benchmark for subsequent transactions and
operations, step 12402.
[0301] FIG. 125 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a telemarketing advertising product composite price. Raw
telemarketing advertising transaction data may be obtained from a
variety of sources including, for example, agency telemarketing
advertising buyer data feeds 12500, telemarketing advertiser data
feeds 12502, telemarketing advertising server data feeds 12504,
telemarketing advertising networks and exchange data feeds 12506,
and telemarketing publisher order management system data feeds
12508. The raw telemarketing advertising transaction data may be
pre-processed to remove duplicates and otherwise transform
attribute values into attribute tier values, step 12510, with the
resulting data provided to a telemarketing advertising product
composite pricing engine 12512. The telemarketing advertising
product composite price engine may include a volume-weighted
composite price for sampled telemarketing advertising products of
the identified attribute values conducted within an identify
transaction time frame.
[0302] As illustrated in FIG. 126, the output from the
telemarketing advertising product composite pricing engine, step
12600, may be published as a telemarketing advertising product
composite price publication, step 12602, and syndicated as a
telemarketing advertising product composite price syndication, step
12604. The publication and syndication of the telemarketing
advertising product composite price may be accomplished via a
variety of publication and communication mechanisms. The
telemarketing advertising product composite price may also be
published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
telemarketing advertising product composite price may be archived
using any known archival methods and storage devices.
[0303] FIG. 127 illustrates steps of a method for establishing a
product placement advertising reference entity by aggregating
selected transactions. As described above with reference to FIGS.
2-5, a plurality of advertising transactions are captured from any
of a variety of data sources and data transmission mechanisms, the
transaction attribute values are identified, selected transaction
values are transformed to attribute tier values, and the resulting
advertising transaction records are stored in a database, step
12700. As part of this process, the transaction records and the
database can be indexed and organized according to an attribute
taxonomy to enable selected data records to be sampled and
analyzed. To establish an advertising reference entity for
advertising transactions matching the product placement attribute
value, a subset of advertising transaction records are selected
within the database for processing, step 12702. The identified
targeted attribute values may include single attributes or
combinations of attributes associated with product placement
advertising transactions. The sampled advertising transaction
records are then aggregated to establish a product placement
advertising reference entity value, step 12704.
[0304] In this embodiment, advertising transaction records may be
selected for an advertising transaction database by specifying
"product placement" (or a corresponding attribute ID value) as the
selection value for the advertising medium attribute.
Alternatively, the advertising transactions that are captured in
step 12700 may be limited to transactions purchasing product
placement advertising, as illustrated in FIG. 128. For example, the
data sources used to collect advertising transactions may be
limited to agency electronics delayed media buyers data feeds
12800, product placement advertisers data feeds 12802, product
placement advertising server data feeds 12804, product placement
advertising networks and exchanges data feeds 12806, and product
placement publisher order management system data feeds 12808.
Additionally, the advertising transaction data feeds may be
filtered by a product placement advertising reference entity data
filter, step 12810. As mentioned above, the product placement
advertising transaction data received from the various data feeds
may be preprocessed to remove duplicate transaction records, step
12812. The preprocessed product placement advertising transaction
data may then be processed to transform attribute information into
attribute tier values and data records stored in a database, step
12814.
[0305] FIG. 129 illustrates in more detail steps involved in
organizing product placement advertising transaction records
according to a taxonomy of product placement advertising
attributes. Advertising transaction data selected via a product
placement advertising reference entity data filter, step 12910, may
be preprocessed as described above, step 12902. Information
regarding the effectiveness of product placements listed in product
placement advertising transactions may be obtained from ratings
bureau databases (e.g., Quantcast.com and Nielsen), websites and
other such data feeds, step 12904. This data may be combined to
transform the information from advertising transactions into
attribute values and attribute tier values as described above with
reference to FIG. 3A, 3B. For example, a product data may be
transformed into a product attribute tier value, step 12906,
publisher data information may be transformed into publisher tier
attribute values, step 12908, advertiser information may be
transformed into advertiser tier attribute values, step 12910,
targeting package information may be transformed into one or more
targeting attribute tier values, step 12912, flight information may
be transformed into advertising product flight attribute values,
and revenue information may be transformed into one or more revenue
attribute tier values, step 12916. The transformed product
placement advertising transaction attribute values may then be
stored in a database or data warehouse, step 12918. The data stored
in a database may then be used to determine the product placement
advertising reference entity value, step 12920.
[0306] In an embodiment illustrated in FIG. 130, a product
placement advertising reference entity framework 13002 may be
applied as an automated filter to the eligible pool of archived
product placement advertising transactions stored in a data
warehouse 13000. In this process, an advertising reference entity
server 13004 may use the product placement advertising reference
entity framework 13002 as a filter or search framework for drawing
archived product placement advertising transactions from the data
warehouse 13000. The advertising reference entity server 13004 may
then use the sampled transaction data in order to synthesize a
product placement advertising reference entity 13006. The process
of synthesizing the product placement reference entity may involve
calculating the indexed reference entity value of the transactions
sampled on the basis of the defined attribute values contained in
the product placement reference entity framework 13002. For
example, the indexed value may include a gross transaction size, a
gross revenue index, a net revenue index, and an effective unit
revenue index.
[0307] FIG. 131 illustrates a method in which a product placement
advertising reference entity is used as a product placement
advertising market benchmark. In this embodiment, a product
placement advertising reference entity framework 13100 is used by a
product placement advertising reference entity server 13102 to
selectively sample electronic advertising transaction records
stored within a data warehouse 13104. The product placement
advertising reference entity server 13102 uses the sampled
transaction data to define a product placement advertising
reference entity 13106. This reference entity is then published as
a product placement advertising reference entity data publication
13108. The reference entity definition may also be used to generate
a product placement advertising reference entity data syndication
13110. In this embodiment, the value of the product placement
advertising reference entity may be defined following a
consistently defined and executed advertising reference entity
definition process with the results published and syndicated.
[0308] FIG. 132 illustrates a method for using a single product
placement advertising product composite price as a product
placement advertising product composite price benchmark. In this
process, product placement attribute values which define a
particular type of product placement advertising product are used
to sample an advertising transaction data warehouse to extract
advertising transaction records associated with a type of
advertising product over a period of time, with that data used to
determine an advertising composite price, step 13200. This
establishes a product placement advertising product composite price
within the identified sample transaction time frame. The product
placement advertising product composite price may then be published
to the marketplace on a timely and consistent basis with the
publication syndicated, thereby establishing the product placement
advertising product composite price as a product placement
advertising composite price benchmark for subsequent transactions
and operations, step 13202.
[0309] FIG. 133 illustrates a system network for identifying a set
of advertising transactions to be extracted, transformed and used
to define a product placement advertising product composite price.
Raw produce placement advertising transaction data may be obtained
from a variety of sources including, for example, agency product
placement advertising buyer data feeds 13300, product placement
advertiser data feeds 13302, product placement advertising server
data feeds 13304, product placement advertising networks and
exchange data feeds 13306, and product placement publisher order
management system data feeds 13308. The raw product placement
advertising transaction data may be pre-processed to remove
duplicates and otherwise transform attribute values into attribute
tier values, step 13310, with the resulting data provided to a
product placement advertising product composite pricing engine
13312. The product placement advertising product composite price
engine may include a volume-weighted composite price for sampled
product placement advertising products of the identified attribute
values conducted within an identify transaction time frame. In
particular pricing attribute used in determining a product
composite price may include price per viewer, price per spot, price
per episode, price per session, price per estimated viewer, price
per duration, price per action, and the like.
[0310] As illustrated in FIG. 134, the output from the product
placement advertising product composite pricing engine, step 13400,
may be published as a product placement advertising product
composite price publication, step 13402, and syndicated as a
product placement advertising product composite price syndication,
step 13404. The publication and syndication of the product
placement advertising product composite price may be accomplished
via a variety of publication and communication mechanisms. The
product placement advertising product composite price may also be
published in syndicated via closed, open and public networks as
well as communications among market participants. Additionally, the
product placement advertising product composite price may be
archived using any known archival methods and storage devices.
[0311] FIG. 135 illustrates steps of a method for surveying parties
to advertising transactions to establish advertising market
activity benchmarks. In this process market participants in an
advertising market may be surveyed with a predefined set of
questions intended to solicit information about activity levels in
the advertising market, with the survey answers transformed into at
least one activity level score or index, step 13500. The activity
level score or index can then be used to establish an activity
level benchmark for the selected type of advertising activity, step
13502. The activity levels surveyed may be marketing activity
levels, inquiry activity levels, hiring activity levels, account
visit activity levels, and proposal activity levels. The selected
advertising markets may be any of the different markets defined in
the topology. The parties survey may be any of the parties involved
in an advertising market.
[0312] The survey questions asked of market participants may
include any of spending by product, spending by platform, spending
by media, spending by revenue model type, selling by product,
selling by platform, selling by media, selling by revenue model
type, viewing by product, viewing by platform, viewing by media,
viewing by revenue model type, allocation across products,
allocation across platforms, allocation across media, migration
among products, migration among platforms, migration among media,
revenue by product, revenue by platform, revenue by media, relative
strength by product, relative strength by platform, relative
strength by media, relative strength by revenue model type, inquiry
by product, inquire by platform, inquiry by media, inquiry by
revenue model type, requests for pricing by product, requests for
pricing by platform, requests for pricing by media, and requests
for pricing by revenue model type.
[0313] FIG. 136 illustrates more details regarding how market
participants can be surveyed and the results processed. Market
participants can be surveyed with responses received through a
variety of data feeds 13600-13608. Specifically, survey responses
may be received from advertiser agent survey data feeds 13600,
advertiser survey data feeds 13602, content publisher survey data
feeds 13604, broadcast, carrier and data infrastructure survey data
feeds 13606, and traffic and rating bureau survey data feeds 13608.
Survey responses may be preprocessed and de-duplicated, step 13610,
and the results processed by an advertiser activity index
composition engine 13612 where the survey response data is
aggregated and taxonomized, and indexed values for individual and
combined activity level survey responses are calculated and
composed. The survey responses may be received by any known
transmission method and channel.
[0314] FIG. 137 illustrates a method for establishing an
advertising activity index as an advertising market benchmark.
Indexed advertising activity level values are generated from an
advertising activity index engine, step 13700, and the results are
published as an advertising activity index, step 13702. The indexed
activity level values may be syndicated, step 13704. Further, the
indexed advertising activity level values may be archived. Through
public dissemination and permanent access to historic data,
advertising activity index level values are established as viable
and tradable advertising spot, current and recent market activity
level benchmarks for subsequent transactions, operations, and the
like. The advertising index value may be published, syndicated and
disseminated using any known publishing and communication
mechanism.
[0315] FIG. 138 illustrates steps of a method for surveying parties
to advertising transactions to establish advertising sentiment
benchmarks. In this process market participants in an advertising
market may be surveyed with a predefined set of questions intended
to solicit information about future or proposed activity levels in
the advertising markets for some future time period, estimates
regarding pricing and activity levels in the advertising markets
for some future time period, anticipated shifts or migration in
advertising market pricing, revenue generation or overall activity
levels for some future time period, with the survey answers
transformed into at least one future activity level or sentiment
score, step 138500. The future activity level or sentiment score
can be indexed and used to establish a future activity level
benchmark for a type of advertising activity, step 13802. The
future activity levels surveyed may be purchasing activity levels,
selling activity levels, viewing activity levels, marketing
activity levels, inquiry activity levels, hiring activity levels,
account visit activity levels, proposal activity levels, and
migration levels. The selected advertising markets may be any of
the different markets defined in the topology. The parties survey
may be any of the parties involved in an advertising market.
[0316] The survey questions asked of market participants may
include any of expected spending by product, expected spending by
platform, expected spending by media, expected spending by revenue
model type, expected selling by product, expected selling by
platform, expected selling by media, expected selling by revenue
model type, viewing by product, expected viewing by platform,
expected viewing by media, expected viewing by revenue model type,
expected allocation across products, expected allocation across
platforms, expected allocation across media, expected migration
among products, expected migration among platforms, expected
migration among media, expected revenue by product, expected
revenue by platform, expected revenue by media, expected relative
strength by product, expected relative strength by platform,
expected relative strength by media, expected relative strength by
revenue model type, expected inquiry by product, expected inquire
by platform, expected inquiry by media, expected inquiry by revenue
model type, expected request for pricing by product, expected
request for pricing by platform, expected request for pricing by
media, expected request for pricing by revenue model type, expected
disruptions in spending, expected migration in spending, expected
reallocation in spending, perceived value of products, perceived
value of platforms, perceived value of media, perceived value of
sales channel, perceived preference among advertising media,
perceived effectiveness of a type of media, perceived ad spend
migration, perceived or derived value from ad spend, and spend
allocation forecasts.
[0317] FIG. 139 illustrates more details regarding how market
participants can be surveyed and the results processed. Market
participants can be surveyed with responses received through a
variety of data feeds 13900-13908. Specifically, survey responses
may be received from advertiser agent survey data feeds 13900,
advertiser survey data feeds 13902, content publisher survey data
feeds 13904, broadcast, carrier and data infrastructure survey data
feeds 13906, and traffic and rating bureau survey data feeds 13908.
Advertiser sentiment survey responses may be preprocessed and
de-duplicated, step 13910, and the results processed by an
advertiser sentiment index composition engine 13912 where the
survey response data is aggregated and taxonomized, and indexed
values for individual and combined activity level survey responses
are calculated and composed. The survey responses may be received
by any known transmission method and channel.
[0318] FIG. 140 illustrates a method for establishing an
advertising sentiment index as an advertising market benchmark.
Indexed advertising sentiment level values are generated from an
advertising sentiment index engine, step 14000, that are published
as an advertising sentiment index, step 14002. The indexed
sentiment level values may further be syndicated, step 14004.
Further, the indexed advertising sentiment level values may be
archived. Through public dissemination and permanent access to
historic data, advertiser sentiment index level values are
established as viable and tradable forward-looking advertising
market activity level benchmarks for subsequent transactions,
operations, and the like. The advertising sentiment index value may
be published, syndicated and disseminated using any known
publishing and communication mechanism.
[0319] The elements depicted in flow charts and block diagrams
throughout the figures imply logical boundaries between the
elements. However, according to software or hardware engineering
practices, the depicted elements and the functions thereof may be
implemented as parts of a monolithic software structure, as
standalone software modules, or as modules that employ external
routines, code, services, and so forth, or any combination of
these, and all such implementations are within the scope of the
present disclosure. Thus, while the foregoing drawings and
description set forth functional aspects of the disclosed systems,
no particular arrangement of software for implementing these
functional aspects should be inferred from these descriptions
unless explicitly stated or otherwise clear from the context.
[0320] Similarly, it will be appreciated that the various steps
identified and described above may be varied, and that the order of
steps may be adapted to particular applications of the techniques
disclosed herein. All such variations and modifications are
intended to fall within the scope of this disclosure. As such, the
depiction and/or description of an order for various steps should
not be understood to require a particular order of execution for
those steps, unless required by a particular application, or
explicitly stated or otherwise clear from the context.
[0321] The methods or processes described above, and steps thereof,
may be realized in hardware, software, or any combination of these
suitable for a particular application. The hardware may include a
general-purpose computer and/or dedicated computing device. The
processes may be realized in one or more microprocessors,
microcontrollers, embedded microcontrollers, programmable digital
signal processors or other programmable device, along with internal
and/or external memory. The processes may also, or instead, be
embodied in an application specific integrated circuit, a
programmable gate array, programmable array logic, or any other
device or combination of devices that may be configured to process
electronic signals. It will further be appreciated that one or more
of the processes may be realized as computer executable code
created using a structured programming language such as C, an
object oriented programming language such as C++, or any other
high-level or low-level programming language (including assembly
languages, hardware description languages, and database programming
languages and technologies) that may be stored, compiled or
interpreted to run on one of the above devices, as well as
heterogeneous combinations of processors, processor architectures,
or combinations of different hardware and software. Whether such
functionality is implemented as hardware or software depends upon
the particular application and design constraints imposed on the
overall system. Skilled artisans may implement the described
functionality in varying ways for each particular application, but
such implementation decisions should not be interpreted as causing
a departure from the scope of the present invention.
[0322] As a specific example, the embodiments described above may
be implemented on any of a variety of computing devices, such as a
computer 160 illustrated in FIG. 141. Such a computer 160 typically
includes a processor 161 coupled to volatile memory 162 and a large
capacity nonvolatile memory, such as a disk drive 163. The computer
13 may also include a floppy disc drive 164 and a compact disc (CD)
drive 165 coupled to the processor 161. Typically the computer will
also include a pointing device such as a mouse 167, a user input
device such as a keyboard 168 and a display 166. The computer
device 13 may also include a number of connector ports coupled to
the processor 161 for establishing data connections or receiving
external memory devices, such as a USB or FireWire.RTM. connector
sockets or other network connection circuits 166 for coupling the
processor 161 to a network. In a notebook configuration, the
computer housing includes the pointing device 167, keyboard 168 and
the display 169 as is well known in the computer arts.
[0323] The various embodiments may be implemented by a computer
processor 161 executing software instructions configured to
implement one or more of the described methods. Such software
instructions may be stored in memory 162, 163 as separate
applications, or as compiled software implementing an embodiment
method. Reference database may be stored within internal memory
162, in hard disc memory 164, on tangible storage medium or on
servers accessible via a network (not shown). Further, the software
instructions and databases may be stored on any form of tangible
processor-readable memory, including: a random access memory 162,
hard disc memory 163, a floppy disc (readable in a floppy disc
drive 164), a compact disc (readable in a CD drive 165),
electrically erasable/programmable read only memory (EEPROM), read
only memory (such as FLASH memory), and/or a memory module (not
shown) plugged into the computer 160, such as an external memory
chip or a USB-connectable external memory (e.g., a "flash drive")
plugged into a USB network port 166.
[0324] The order in which the steps of a method described above and
shown in the figures is for example purposes only as the order of
some steps may be changed from that described herein without
departing from the spirit and scope of the present invention and
the claims.
[0325] The steps of a method or algorithm described in connection
with the embodiments disclosed herein may be embodied directly in
hardware, in a software module executed by a processor, or in a
combination of the two. A software module may reside in processor
readable memory which may be any of RAM memory, flash memory, ROM
memory, EPROM memory, EEPROM memory, registers, hard disk, a
removable disk, a CD-ROM, or any other form of storage medium known
in the art. An exemplary storage medium is coupled to a processor
such that the processor can read information from, and write
information to, the storage medium. In the alternative, the storage
medium may be integral to the processor. The processor and the
storage medium may reside in an ASIC. The ASIC may reside in a user
terminal or mobile device. In the alternative, the processor and
the storage medium may reside as discrete components in a user
terminal or mobile device. Additionally, in some aspects, the steps
and/or actions of a method or algorithm may reside as one or any
combination or set of codes and/or instructions on a machine
readable medium and/or computer readable medium, which may be
incorporated into a computer program product. Also, any connection
is properly termed a computer-readable medium. For example, if the
software is transmitted from a website, server, or other remote
source using a coaxial cable, fiber optic cable, twisted pair,
digital subscriber line (DSL), or wireless technologies such as
infrared, radio, and microwave, then the coaxial cable, fiber optic
cable, twisted pair, DSL, or wireless technologies such as
infrared, radio, and microwave are included in the definition of
medium. Disk and disc, as used herein, includes compact disc (CD),
laser disc, optical disc, digital versatile disc (DVD), floppy disk
and blu-ray disc where disks usually reproduce data magnetically,
while discs reproduce data optically with lasers. Combinations of
the above should also be included within the scope of
computer-readable or processor-readable media and computer program
product.
[0326] Thus, in one aspect, each method described above and
combinations thereof may be embodied in computer executable code
that, when executing on one or more computing devices, performs the
steps thereof. In another aspect, the methods may be embodied in
systems that perform the steps thereof, and may be distributed
across devices in a number of ways, or all of the functionality may
be integrated into a dedicated, standalone device or other
hardware. In another aspect, means for performing the steps
associated with the processes described above may include any of
the hardware and/or software described above. All such permutations
and combinations are intended to fall within the scope of the
present disclosure.
[0327] The foregoing description of the various embodiments is
provided to enable any person skilled in the art to make or use the
present invention. Various modifications to these embodiments will
be readily apparent to those skilled in the art, and the generic
principles defined herein may be applied to other embodiments
without departing from the spirit or scope of the invention. Thus,
the present invention is not intended to be limited to the
embodiments shown herein, and instead the claims should be accorded
the widest scope consistent with the principles and novel features
disclosed herein.
* * * * *
References