U.S. patent application number 10/407323 was filed with the patent office on 2004-10-07 for integrated dynamic pricing and procurement support for e-commerce advertising channels.
Invention is credited to Dresden, Scott.
Application Number | 20040199397 10/407323 |
Document ID | / |
Family ID | 33100979 |
Filed Date | 2004-10-07 |
United States Patent
Application |
20040199397 |
Kind Code |
A1 |
Dresden, Scott |
October 7, 2004 |
Integrated dynamic pricing and procurement support for e-commerce
advertising channels
Abstract
The present invention provides a virtual system that assists in
the procurement of advertising on an Internet vendor site for the
sale of products or services. The system links to a user's
financial package to get data on the products or services and
allows the user to set financial parameters based on the desired
financial goals related to the product and advertising. Performance
data regarding advertising is accessed and financial rules
generated which are applied to generate a target price for
advertising or one or more products. The system can acquire
advertising automatically or assist in the auction of advertising.
In a preferred embodiment, keywords are purchased on a search
engine in an auction.
Inventors: |
Dresden, Scott; (Delray
Beach, FL) |
Correspondence
Address: |
DORT CLOSE IP LAW GROUP PLLC
P. O. BOX 66148
WASHINGTON
DC
20035
US
|
Family ID: |
33100979 |
Appl. No.: |
10/407323 |
Filed: |
April 4, 2003 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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60457794 |
Mar 26, 2003 |
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Current U.S.
Class: |
705/1.1 |
Current CPC
Class: |
G06Q 30/0601 20130101;
G06Q 30/0256 20130101; G06Q 30/08 20130101; G06Q 30/02
20130101 |
Class at
Publication: |
705/001 |
International
Class: |
G06F 017/60 |
Claims
Having described our invention above, we claim:
1. A method for assisting a user in the procurement of a
advertisement for placement on at least one vendor Internet site
including: calculating a gross margin for said at least one product
based on said desired margin; accessing performance data, said
performance data related to said at least one vendor Internet site;
determining the relative cost of a successful advertising event for
said at least one product; and providing a advertisement price
target.
2. The method recited in claim 1, wherein said determining step
includes the following acts: retrieving a desired margin for a sale
of a set of at least one product; and applying a set of criteria in
order to perform said providing of said advertisement price target
based on said desired margin, said applying including evaluating
said performance data.
3. The method as recited in claim 1, wherein said vendor Internet
site is a search engine, said advertisement is in response to a
keyword search on said search engine and said successful
advertising event is a click-through.
4. The method as recited in claim 3, desired margin is based on a
percentage of a cost of a click-through.
5. The method as recited in claim 3, wherein said desired margin is
based on a net margin of said at least one product.
6. The method as recited in claim 3, wherein said set of criteria
includes at least one of: shipping cost of said at least one
product, tax information, geographical information, preferred
customer discounts and volume discounts.
7. The method as recited in claim 1, wherein said applying a set of
criteria includes the act of linking with a financial software
package.
8. The method recited in claim 3, wherein said method is
automatically activated by a keyword auction alert.
9. The method as recited in claim 8, wherein said keyword auction
alert monitors said at least one search engine.
10. The method as recited in claim 3, further including the act of
monitoring said user's keyword bid.
11. The method as recited in claim 3, wherein said performance data
includes at least data regarding keyword to click-through
ratios.
12. The method as recited in claim 3, wherein said performance data
includes click-through rates of one of more keywords of said at
least one search engine.
13. The method recited in claim 3, further including the act of
generating a list of alternate keywords.
14. The method as recited in claim 12, wherein the act of
generating a list of alternate keywords includes generating common
misspellings of said keyword.
15. The method as recited in claim 1, further including the act of
recording the results of said bidding and storing in a central
location.
16. The method as recited in claim 15, further including the act of
providing permission, said access to said central location
contingent on said permission being provided to said user.
17. A method for purchasing an advertising tool in order to
generate sales for an e-commerce site that sells at least one
product or service, and accessible through the Internet, wherein
said advertising tool is placed on a advertising site in response
to an action from a potential customer, and said advertising tool
is sold by means of an electronic auction; and wherein the
improvement includes automatically providing a bidder with a target
range for the purchase of said advertisement based on financial
information regarding at least one product or service, a set of
financial goals of seller of said at least one product or service,
and, if available, data relating to the performance of said
advertising site.
18. The method as recited in claim 17, wherein said advertising
tool is a keyword place on a search engine site.
19. The method as recited in claim 17, further including the act of
placing said bid in said electronic auction.
20. The method as recited in claim 17, wherein said financial
information is generated from said seller's financial or accounting
software.
21. The method as recited in claim 17, wherein said financial goals
include a target margin for one of said at least one product or
service.
22. The method as recited in claim 17, wherein said financial goals
include a target rate of return based on the cost of said
advertising tool.
Description
REFERENCE TO PRIORITY DOCUMENTS
[0001] This application claims priority under 35 U.S.C. 119(e) my
U.S. Provisional Application 60/______ entitled DYNAMIC MARGIN AND
PRICING DECISION SUPPORT TOOL FOR CUSTOMER PROCUREMENT TRANSACTIONS
filed on Mar. 26, 2003, which is hereby incorporate by reference
for all purposes.
BACKGROUND
[0002] Obtaining or losing a small segment of market share may mean
the difference between a an e-commerce enterprise going broke or
being profitable. . Thus, drawing the new customer to the
e-commerce site, over the competition, is vital for survival. One
of most natural ways to get a consumer to the passively come to the
entrance of the e-commerce site, is to capture them while they are
not sure on which e-commerce site to link for a particular product
or service. Thus, the use of Internet advertising on such Internet
referral mechanisms like search engines, linking services, or
directories to attract customers can be an important tool.
[0003] There are currently many theories on attracting customers
and e-commerce promotion. Such literature relating to advertising
on the Internet and maximizing its effect includes: Successful
Keyword Searching: Initiating Research on Popular Topics Using
Electronic Databases by Randall M. MacDonald and Susan Priest
MacDonald; 101 Ways to Boost Your Web Traffic: Internet Promotion
Made Easier, 2nd edition by Thomas Wong; and Streetwise Maximize
Web Site Traffic: Build Web Site Traffic Fast and Free by
Optimizing Search Engine Placement by Robin Nobles and Susan
O'Neil. These publications are hereby incorporated by
reference.
[0004] Many e-commerce sites capitalize on an existing brand name
product or service and have a recognizable domain name. Other
e-commerce sites have developed "site recognition" either by
innovative and attractive sites or attracting consumers by using
novel transaction techniques to draw customers in to their sites.
Quite a variety of these Internet and e-commerce techniques have
been developed over the last decade, which include non-traditional
ways to sell, buy, trade, barter, negotiate, manage, advertise and
promote their products and services over the Internet. Some
well-known examples include Ebay.RTM. (timed auctions, immediate
purchase options U.S. Pat. Nos. 6,058,417, 6,466,917 and 6,523,037
all incorporated by reference), Priceline.com.RTM. (reverse
auction, aggregate conditional purchase offers U.S. Pat. No.
6,466,919 incorporated by reference elimination of a secondary
trade channel (U.S. Pat. 6,434,536, incorporated by reference), and
Amazon.com's notorious "one-click" patent (U.S. Pat. No. 5,960,411,
incorporated by reference), and recommendations by using the
shopping cart (U.S. Pat. No. 6,317,722 incorporated by reference),
among others. One of the better discussions of the variety and
execution of e-commerce transactions is the book Digital Dealing by
economist Robert E. Hall (W. W. Norton, 2001) which provides a
review of the current state of electronic transactions in the
business-to-consumer and business-to-business electronic
environment. In particular, Dr. Hall discusses the various Internet
auction systems, which are depicted in a simplified form in FIGS. 1
and 2. This book is hereby incorporated by reference to show the
types of transactions and their transactional operation for
products and services being made over the Internet.
[0005] The increasing need for finding relevant data over the
Internet and the use of search engines to find products and
services indicates that keywords are a particularly important
customer procurement tool. Thus, the procurement of the advertising
in response to keywords is provided by well-known industry leaders
in the Internet searching business, including Google.TM. and
Overture.TM..
[0006] Searching techniques generally provide a result based on a
user's input terms by returning an appropriate document, page, or
uniform resource locator (URL). One very popular method for keyword
searching is the "scoring" method. Google, Inc. of Mountain View,
Calif. has several published U.S. Patent Applications related to
this method including 2001/0123988 entitled "Methods and Apparatus
for Employing Usage Statistics in Document Retrieval" by Dean et
al. and 2001/0133481 entitled "Methods and Apparatus for Providing
Search Results in Response to an Ambiguous Search Query."
Google.TM. owns other technology related to data searching
techniques, for example, a recently issued U.S. Pat. No. 6,526,440
entitled "Ranking Search Results by Reranking the Results Based on
Local Interconnectivity" by Krishna Bharat, which teaches the use
of connectivity to determine "relevance." These publications are
incorporated by reference as they show the use of keywords in
returning search results. However, techniques can be put into place
to manipulate results, such as U.S. Pat. No. 6,269,361 issued to
Davis, et al. and assigned to GoTo.com of Pasadena, Calif., which
describes such a technique for influencing a place in the list of a
search engine and hereby incorporated by reference.
[0007] One of the problems with advertising over the Internet is
accurately paying for the expected performance of the advertising.
Measuring performance of advertising on the Internet has two
problems. The first problem is that the Internet measurement
industry is simply getting used to the appropriate and relevant
criteria to measure. Companies such as Nielsen, Gartner Group, and
Arbitron have been measuring the "effectiveness" of exposures in
traditional media such as radio and television, but applying
traditional criteria to Internet advertising has not been
effective. Thus, the more easily measured "number of views" is a
particular criterion to which sellers of advertising space can
point as a pricing system for selling advertising space. Companies
such as Media Metrix.RTM.) have patents such as U.S. Pat. No.
6,115,680 (which is hereby incorporated by reference) currently
issued to them for placing and measuring advertising on typical
Internet site visit. Other companies such as DoubleClick.RTM. use
similar techniques. The second problem in determining the
cost-effectiveness of marketing tools placed over the Internet is
that interactivity and invasive recording are difficult to manage.
Simply put, a user of the Internet may view an "impression" on a
site. To some degree the placement of "cookies" on a user's
computer can help measure the Internet metrics, although tracking
consumer behavior after leaving a site is difficult unless the
consumer is consenting to invasive recording. Another way is
"tracking," which has infuriated many consumers who resent that
they are being spied on constantly.
[0008] A solution is for the search engine site to measure or
charge by the "click-through." The consumer responds to an
advertisement by clicking on a specific link, which redirects their
browser or opens a new window to another uniform resource locator
(URL). While the tracking is lost, charging by this behavior as
opposed to what the consumer sees may provide a better assessment
of advertising value. A particularly effective use of advertising
space is based on search engine criteria, also known in one aspect
as keywords. Keywords are generally important or targeted natural
language search "terms" entered into a search engine site query by
a user. The reason that keyword advertising may be a better
advertising mechanism is that the user chooses the type of ads that
will be presented as opposed to the pop-up advertisements that have
been compared to junk mail and junk email (spam). Thus, the
Internet advertisement system of click-through for keywords is a
much more cost related solution.
[0009] Other Internet advertising channels for procuring customers
may have different purchasing and performance mechanisms. These
include the link-based commission, affiliate-based relationships
and the banner ad/impression. Sample entities in the affiliate
relationship area include Befree.TM., Linkshare.TM., and Commission
Junction.TM.. Essociate.TM. of San Francisco, Calif. owns two U.S.
Patent applications 2001/47413 and 2002/82919, hereby incorporated
by reference, which detail sample mechanisms for implementing
affiliate referral systems. The relative cost of a commission has
the same determination difficulty as a keyword. The cost and
effectiveness of impressions or banner ads in relation to a product
or service sold also presents difficulties.
[0010] The second problem related to the procurement of advertising
over the Internet is that it is quite difficult to determine the
relative cost of advertising in relation to a product or group of
products to maintain a desired margin of profit. Often, to lure
customers and gain market share, e-commerce companies have sold
items at a loss to gain brand or site recognition. For example,
Amazon.com would sell items below cost in order to get market
share. Thus, the pricing of items sold over the Internet may have
very little to do with actual cost or the desired margin of each
item. Furthermore, the cost of customer procurement may seriously
vary the profit or loss from each item sold and the price of any
customer procurement. It has also been suggested by Martin Bichler
in The Future of e-Markets, Chapter 3 (Cambridge, 2001, which is
hereby incorporated by reference) that the Internet pricing models
have become not only varied but dynamic,. Thus, dynamic pricing
makes the relationship between customer procurement over the
Internet, performance and profit margin all the more difficult to
determine. Because much of the procurement of advertising over the
Internet takes place through an auction, the financial decisions
relating to the purchase of keywords, affiliate links, impressions
or other Internet advertising services is all the more difficult to
accurately determine.
SUMMARY
[0011] Because of the above-discussed problems in determining the
value of Internet advertisement and its relation to customer
procurement and the profitability of products or services sold, the
present invention provides e-commerce sellers with a system which
assists them in determining at what price advertising should be
acquired and/or how a product or service should be priced
considered the price of Internet advertising. The invention can
also executing procurement instructions based on results. The
invention also determines the advertising and/or product pricing
both at a product and a global levels, and in real or substantial
real time in order to assist in the time-critical decisions. The
invention may also work in reverse by providing dynamic pricing as
a function of Internet advertisement costs.
[0012] In a preferred embodiment, the present invention is a
virtual or physical e-commerce application with an interface. The
interface has a global tool and an optional specific tool for every
product that is sold on a particular site. The e-commerce site has
access to several vital pieces of information which provide the
interface with data on the particular product or service. Important
profit information is then calculated in cooperation with an
accounting package or a financial engine (which may reside as part
of the functionality of the-e-commerce interface as well) or simply
resides a fixed field in the e commerce package. A real time
understanding of the real cost of a click through or other
advertising mechanism exists either as an automated tool to login
to the Paid Performance interface or a field for a static pricing
provides the data need to value the advertising performance. Other
embodiments use pooled performance data in virtual storage to
generate a target price from a desired product margin.
[0013] The user can defines much of these factors and then the
invention, in real or near real-time can either change the bid/cost
of a procurement of a click-through or dynamically change of the
price of the product to accommodate the margin desired on a global
or product level basis and the variable expense of advertising. The
present invention also integrates a dynamically presenting a unique
price to the consumer as the consumer has a history of tolerating a
different pricing structure, this can be based on innumerable
parameters such as state, zip, title, etc. Also contemplated is
integrating and tolerating pricing based on shipping costs tax
tables, quantity discounts, or up-selling and cross-selling.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] FIG. 1 represents the current art in the acquisition of a
customer procurement device (simple Dutch auction).
[0015] FIG. 2 depicts a timed auction mechanisms used over the
Internet.
[0016] FIG. 3 depicts a basic block diagram of the present
invention.
[0017] FIG. 4 shows the simplified elements of a user stations
[0018] FIG. 5 represents a block diagram of an embodiment of the
e-commerce interface.
[0019] FIG. 6 shows the link between the individual product pricing
databases.
[0020] FIG. 7 represents an embodiment present invention in a
simplified block diagram.
[0021] FIG. 8 represents a bid delivery system as would be
implemented by an embodiment of the present invention (dutch or
sealed bid auction).
[0022] FIG. 9 represents a bid delivery system as would be
implemented by an embodiment of the present invention (english or
time-based multiple bid auction).
[0023] FIG. 10 shows a method of providing a keyword auction price
through an embodiment of the present invention.
[0024] FIG. 11 is a flowchart showing a sample method of computing
a target bid.
[0025] FIG. 12 represents a grouping of subproducts based on
pricing relationships.
[0026] FIG. 13 shows a method for dynamically computing a keyword
price.
[0027] FIG. 14 shows a method for applying the present invention in
a time-based auction.
[0028] FIG. 15 represents a method for practicing the multiple
search engine embodiment of the invention.
[0029] FIG. 16 is a sample contingency relationship table for
acquisition of keywords over multiple search engine bidding.
[0030] FIG. 17 represents a customer procurement device for
multiple search engines and key elements.
[0031] FIG. 18 shows a comparison table used in the embodiment of
the invention as shown in FIG. 17.
[0032] FIG. 19 depicts a system for analyzing multiple search
engines, key word elements, and permutations.
[0033] FIG. 20 shows a simplified resulting relationship table for
the system in FIG. 19.
[0034] FIG. 21 illustrates a method for automating the customer
procurement device bidding and acquisition system.
[0035] FIG. 22 is a sample embodiment of the up-selling or
cross-selling embodiment of the present invention.
[0036] FIG. 23 is an example of an affiliate-linking embodiment of
the invention.
DETAILED DESCRIPTION OF THE INVENTION
[0037] The following illustrations and descriptions are meant to
assist in the understanding of the invention and are meant to be
representative examples of the manner in which the present
invention may be implemented. As such, they are exemplary and not
limiting. In a preferred embodiment, the present invention
contemplates the key word auction as the primary method by which
the invention will be implemented. Of course, other customer
procurement mechanisms or Internet advertisements and "metrix" are
contemplated in alternate embodiments of the invention.
[0038] In the following detailed description, components are often
referred to in plural. These components are often numbered as
"19(n)," where n is meant to imply an integer or count of the
components. Thus, if there are four devices for which 19 stands for
19(n) is meant to refer to all items 19(1), 19(2), 19(3), and
19(4). The first in a set is referred t 19(a) and the last in a set
will be indicated by 19(z). Thus 19(n) will generally mean 19(a) .
. . 19(z) unless otherwise indicated. Where there may be singular
distinctions made between the plural components, the individual
number ("19(4)") will be indicated. Where there are intended to be
plural subcomponents of a plural components, the number indication
will be made as "19(n,n)." Furthermore, while a keyword auction is
described in detail as a preferred embodiment, other advertising
channels, such as affiliate-linking and banned ad/impressions may
be contemplated in alternate embodiments as well.
[0039] Referring now to FIG. 3, a simplified diagram of a first
embodiment of the e-commerce interface 100 is shown. The e-commerce
interface 100, can be represented as sitting virtually between the
bidder/procurement agent system 90(n) and the network 20. The
e-commerce interface 100 is shown to be virtual as can be
appreciated by those skilled in the art, as it may be implemented
on one or more computing machines that are separate from the
e-commerce interface 100 but connected to it. The e-commerce
interface 100 is connected internally or externally to virtual
performance data storage 200 and a wide area network 20, which in a
particular embodiment is the Internet. The system 10 also includes
at least one search engine site 50(n) on which a customer
procurement device may be obtained. The search engine site 50(n)
may include physical or virtual computation 60(n). The search
engine site 50(n) is connected to the network 20 through a
connection 22(n). The system includes one or more optional vendors
30(n), with a virtual computation device 35(n) connected through
connection 32(n). An optional consumer purchaser 80(n) may also be
part of the system and connected to the network 20 through
connection 82(n).
[0040] FIG. 4 is a simplified illustration of an individual
user/bidder system 90(n) as may be used in the present invention.
Many variations of the station 90 may be implemented as can be
appreciated by those skilled in the art. The user system 90(n)
includes a computation device 98(n) which can be one or more
computers or part of a computer. The computation device 98 is
connected to an optional user interface 97(n), which may be a
personal computer or workstation through an internal or external
bus or communication line 91(n). Optionally, there can be
individual or amalgamated product servers or databases 92(n,n),
which may keep inventory, pricing, availability, shipping costs and
other information updated. These servers or databases 92(n,n) may
be each single or multiple computational devices or all included as
part of a single virtual machine and part of a larger computing
machine. A financial engine/database 95(n) may be part of the
computation device 98(n) or a separate computation device or
computer. A user 96(n) may be a person, a group of people, an
e-commerce system, a computer or automated system or any
combination thereof The connection to the e-commerce interface 100
is provided by virtual connection 94(n). Virtual connection 94 may
be any combination of internal buses, external buses, communication
lines (Ethernet, T1), or software links and may overlap with many
other connection structures. These structures are shown to be
virtual and may be have physical embodiments that that are
implemented in a variety of ways. E-commerce interface components
which are local or particular to a user system 90(n) are indicated
by 100(n).
[0041] FIG. 5A is a simplified block diagram of the e-commerce
interface 100 as may be implemented in the present invention. Once
again the parts are shown to be virtual and may be embodied and
executed on one or any number of computing devices. The e-commerce
interface 100 is run on a virtual implementation computer 250,
which can include real or virtual storage 200, which is used to
store the performance of customer procurement devices for various
purchases on one or more search engines 50(n). The e-commerce
interface 100 is connected to the virtual storage 200 through a
communication system 190, which may be an internal or external bus
or a network or other communication line, such as T1, Ethernet,
etc.. The global tool 185 may be the virtual computation engine
which collects data and executes the computational instructions in
one embodiment. The connection interface 105 virtually or
physically connects the global 185 and product 150(n) tools to one
or more computation devices 98(n) and optionally the financial
engine 95 and network 20. The e-commerce interface may also include
optional product tools 150(n) which may be for individual or set of
products lines. As such, they may be linked to the individual
product databases 92(n,n) in the user systems 90(n), but they are
not required to be linked. Virtual data link 160 may be part of the
virtual connection 94 or the communication system 190 depending on
the implementation of the invention. Optional intelligence module
198 may be included in the virtual implementation computer 250 or
as part of the e-commerce interface 100. In a preferred embodiment
the e-commerce interface 100 has a local implementation module
199(n), of which a part are instructions which may be executed on
user system computation device 98(n) with access via virtual
connection 94 to the e-commerce interface 100 over a network. This
is shown in FIG. 5B.
[0042] FIG. 6 shows a simplified schematic of the local portion of
an e-commerce interface 100(n) as would be used for multiple
related products 150(a) . . . 150(z). As mentioned above, the
product databases 92(n,n) in the user station 90(n) may be directly
or virtually linked with the optional individual product tools
150(n, n) in the e-commerce interface 100(n).
[0043] FIG. 7 shows a simplified illustration of a first embodiment
of the invention as may be used in a typical keyword procurement
scenario. In the illustration, there are 4 bidder systems 90(1) . .
. 90(4) for a keyword on a single search engine site A 50. To
illustrate the flow of information, inquiries or bids from
bidders/users come into the search engine site 50 through
communication in route 23 and information returning to the
bidders/users returns through communication out route 24. User
systems 90(3) and 90(2) have access to an e-commerce system 100(3)
and 100(2) as contemplated by the present invention. The access may
be either direct or virtual. For example, the e-commerce system 100
could be accessed as a subscription service over a private or
public network and either run on a central server or a java virtual
machine at the individual bidding systems 90(n) or a combination
thereof
[0044] FIG. 8 represents a "dutch" auction embodiment of the
present invention shown in FIG. 7. The dutch auction has a blind
single-bid system in which the highest bidder simply gets the
highest position, second highest bidder gets the second position
and so forth. Each user 90(n) supplies an individual bid 99(n) via
the network 20 and connections 22(n) to the single site selling the
keyword 50. E-commerce interfaces 100(n) supply the recommended
bidding price based on the computation to each user system 90(n).
The recommended bid 101(n) can be automatically supplied as the
individual bid 99(n) to the site 50, or a human or computer user
may screen it and accordingly or post it, allowing for a range of
optional automation options. In the shown embodiment the bids are
placed in a virtual bid collector 55, which may be on the site 50
selling the keyword or on another e-commerce processing site (not
shown). The bids 99(n) are posted and the winner 99(2), in this
case, gets position 1, 99(3) gets position 2, etc. The virtual bid
cutoff 985 represents where the minimum bid lies to get any
exposure or procurement (in this case three placements are
offered). As can be appreciated, there could be a single exposure
or any number of positions being bid for a keyword or other
customer procurement device on search engine site 50.
[0045] FIG. 9 represents a multiple bid, timed auction scenario in
the present invention in FIG. 7 ("english" auction). In this
illustration the bids 99(n) are placed in the bid collector 55.
However, at time t(2), the bids are posted at virtual location 980
so that the users/bidders 90(n) may access the other bids. The
e-commerce interface 100(n) can access this location 980 in order
to re-compute an appropriate bid for the customer procurement
device. Obviously, this process may occur once or many times as the
rules of the auction may vary. At time t(z-(increment)), the bids
will become final. In the illustration, e-commerce interface 100(2)
has determined that user/bidder 90(2) should no longer be involved
in the bidding and this is indicated by an "X." However the three
other users all submit final bids 99(n').
[0046] Referring now to the flowchart represented in FIG. 10, a
simplified depiction of the method 1000 for practicing an
embodiment of the present invention is described. In step 1010
available keywords and potential permutations are determined either
by a user or a machine. Such a step could simply be performed
manually, or could be an automatic search run by the e-commerce
interface 100 or another program on the user computation device
98(n). The site 50 on which the keyword or permutation is found is
accessed in step 1020. Steps 1010 and 1020 may be performed in
either order. In step 1030 the e-commerce interface 100 then
determines whether performance data is available for the site 50.
The performance data may be available from the site itself 50, in
which case it is loaded into the e-commerce interface 100 in step
1070. If not available, the e-commerce interface 100 accesses a
performance database in step 1050, either created by a third party
or through amalgamated data collected by one or more e-commerce
interface 100 transactions. It may also be stored on the virtual
storage device 200, which may be accessible as part of a
subscription service or provided as part of the e-commerce
interface 100 with optional levels of access.
[0047] Simultaneously while the above steps are being performed,
the auction data is accessed in step 1024, and the pricing or other
offers (in an english auction) are accessed and loaded into the
e-commerce interface 100 in step 1026. Optionally, the system can
access pricing and/or offers on available permutations of the
keyword in step 1028, if appropriate.
[0048] In step 1100, the accounting information on the target
product or group of products is accessed by the e-commerce
interface 100. This information may be included in the e-commerce
interface 100 or calculated and accessed by the user's accounting
package or financial engine/database 95. Depending on the structure
of the entity, this information may be stored and computed on the
individual product or product subset servers 92(n) or in the
product tools 150(n).
[0049] In step 1200, the target margin is loaded into the system.
This step may happen out of sequence as the determination of the
target margin in step 1150 may be time independent of some of the
other steps as in pre-determined. Choosing a target margin may be
as simple as a mandate from an officer of the company and stored in
the financial engine 95 and loaded in step 1150. The target margin
may also be entered by a human user for each relevant event, such
as an auction or at particular discrete times like calendared or
fiscally-related events, if appropriate. In step 1300 (discussed
below), the e-commerce interface 100 processes the site 50
performance data, target margin, keyword pricing, accounting
information, and global and product variables to provide the user
(machine or human) with a target price in step 1090. In optional
step 1500, the e-commerce interface 100 checks to make sure that
the keyword bid is appropriate before submitting as a bid it in
step 1600. These steps may be included as part of the optional
automated keyword bidding embodiment described below and shown in
FIG. 21.
[0050] In the particular embodiment shown, a non-sequential and
independent step, step 1150, a field is dedicated to what
percentage the user is willing to spend as a variable expense of
advertising (VAREXP) or what net margins (NETMAR) the user desires.
The generation of these variables is discussed below in detail.
[0051] FIG. 11 shows a method 1300 for dynamically setting the
target cost of a click-through in a particular embodiment. In step
2010, the e-commerce interface 100 determines a net margin from a
gross margin (GM) from accessed information including: price of a
product (PRICE); wholesale price of product (COGS); gross margin
(GRSMGN) calculated from the PRICE and COGS. In step 2020, the
(NETMAR) net margin (or other appropriate accounting benchmark as
discussed below) is calculated via an import from the company's
accounting package which may be executed on the financial engine 95
in step 2025. An accounting package may also reside as part of the
functionality of the-e-commerce package 100, either centrally 100
or locally 100(n)) or simply reside as a fixed field in the local
e-commerce interface 100(n) for simplification. This step may be
practiced with variation without departing from the scope of the
invention. For example, the financial engine 95 may track inventory
and reduce price based on aging products, and, therefore, the
product subset servers 92(n) are in communication with the
accounting package 95, which updates the pricing and entity's
financial records (not shown) and returns the new pricing data to
the product subset servers 92(n). Although it is not important to
the invention how such updating and internal pricing are
accomplished, it is contemplated that the e-commerce interface 100
and in particular the global tool 185 have speedy access to the
information in both of these virtual structures 92(n) and 95 (which
may be the same structure) in order to generate timely information.
Of course, for some entities the use of the global tool 185 may use
unnecessary computing resources when one or more product tools
150(n) will be sufficient.
[0052] In step 2050 a real-time or near real-time evaluation of the
real cost of a click through at a customer procurement device
inventory tool (ad inventory tool) is accessed and evaluated. These
ad inventory tools may be like those included in such search
engines as Overture.TM., Google.TM., LookSmart.TM., FindWhat or
other appropriate site 50. The real-time evaluation may exist in
alternate embodiments either as an automated tool to log in to the
Paid Performance.RTM. interface or equivalent, which is accessible
by the e-commerce interface 100, or through a humanly or machine
entered field for static pricing (STATPRICE). Step 1050 is one way
in which this may be provided as well.
[0053] In order to assess an outcome variable (OV); a series of
optional user contingency variables and evaluations CV(X) may be
added in step 2060 et seq. if they are warranted. These pricing
calculation factors may include choosing whether the controlling
parameter is a variable expense of advertising (VAREXP, see above),
at steps 2062-2063, or net margin (NETMAR, see above), steps
2064-65.
[0054] Whether certain pricing structures will apply in steps
2067-68 is dependent of the controlling parameters for the outcome
variable. Other optional dynamic pricing factors in the e-commerce
interface 100 applied at this step include: whether different
shipping which is based on accounting different shipping tables and
pricing based on shipping costs (SHIPCST), different tax tables for
accommodating different pricing structure (TAXTAB), quantity
discounts based on above rule sets (RULEDISC), and up-selling and
cross-selling (XSELL) based on rule sets which are stored either
locally or globally or apply at global or product levels.
[0055] At step 2100 the particular rules are loaded of the
particular rules and application step for determining a target
price this step is described below.
[0056] In a particular embodiment of the invention, the user
defines much of the above and then the automated global tool 185 or
one or more product tools 150(n), in real time can either change
the bid/cost of a procurement of a click-through or in an alternate
embodiment dynamically change the price of the product to
accommodate the margin desired on a global (NETMAR(global rule) or
product level (NETMAR(P1,P2), where P1 is a rule for one or more
products) basis. The VAREXP or the variable expense of advertising
(VAREXP(global) or VAREXP(P1)), see above) or cost acquisition of
customer procurement devices can be used for outcome determination
and in a particular embodiment is defined on the product level
(VAREXP(product rule)) by the admin functionality of the user
system 90(n) or of the e-commerce interface 100. However, it is
typically expected that this variable would be mandated by a VP of
sales or a CFO on a global or product level basis.
[0057] In an alternate embodiment of the present invention the
result is that the e-commerce interface 100 may also dynamically
present a unique price to the consumer, as the consumer has a
history of tolerating an alternate pricing structure (consumer
dependent pricing structure), which can be based on innumerable
parameters such as state, zip, title, etc. as there many types of
these alternate pricing structures which can be chosen to implement
dynamic pricing. If it is determined that alternate pricing
structures apply in step 2080, the particular details are indicated
in step 2085. These is factored into the dynamic pricing system at
step 2100 (described below) based on the user preferences for
alternate pricing mechanisms.
[0058] Of course, a preferred embodiment of the present is
primarily designed to assist in the acquisition of customer
procurement devices by providing dynamic pricing (price target
ranges) to assist in the acquisition of such devices. In alternate
embodiments, the present invention can assess pricing of one or a
define set of products based on the cost of advertising (VAREXP) or
using the cost of customer procurement device acquisition simply as
part of the dynamic pricing model. As can be appreciated by those
skilled in the art, a set of related products may or not be
connected through acquisition of different customer procurement
devices and thus may have different pricing considerations for each
acquisition. This is shown in FIG. 12, a virtual product pricing
relationship table, 950 which may be store locally or in virtual
storage 200.
[0059] Referring now to FIG. 13, step 2100 is shown in greater
detail as to steps in a particular embodiment for dynamically
determining a target price. The algorithms that have been
determined to apply for the pricing rules are loaded in step 2110.
It is determined if consumer pricing factors apply in step 2115 and
if so, they are loaded in step 2117. Any consumer pricing factors
(discussed above) may optionally be determined by determining
market conditions in step 2148, if such conditions are available
for pricing. A preliminary target price is computed in step 2120.
In step 2145 it is determined if a decision support factor (DSF) is
to be applied. If so, in step 2147 the interface 100 determines
whether market conditions apply to the DSF or are available. If so,
the market conditions are located in step 2148. In step 2149, the
interface 100 then determines if the market conditions warrant
application of market-based DSFs (discussed below), and if so, in
step 2150 the market-based DSFs are loaded into the system. Other
accounting and financial rules, which are not based on the market
conditions, may be applied at step 2155. In step 2190, the
interface 100 determines whether the target price meets the DSF
rules or consuming pricing factors. The interface can revert to
step 2115 if new consumer pricing factors need to be loaded or if
DSFs indicate an unacceptable situation, can warn the user in step
2195. If all DSFs are satisfied, the target is submitted in step
2199.
[0060] Such decision support factors may take into account both
global and specific accounting and marketing principles and range
from the simple to the complex. Such decision support factors may
also provide the user with adequate warnings when the advertising
procurement or product pricing is not within a set of acceptable
parameters. For example, a novice may wish to sell 100 G's at
$20.00 each with a profit of $15 per sale (expected profit $1,500).
The cost of a click-though may be $0.25, which appears reasonable
to the novice. However, the performance tool indicates to the
e-commerce interface that over an hour there will be 10,000
click-throughs ($2,500!) and a conversion rate of 1:50. Thus, the
novice will be purchasing enough performance over an hour to sell
200 and will not be able to derive any profit past the sale of the
last of the 100th item. Thus, there is expected to be a $1,000
loss, even though selling 200 would result in a profit of $3,000.
While this is a relatively simple example of a decision support
factor being applied, the dynamic relationship between open-ended
advertising costs, product pricing mechanisms, and generating
market share provided by the present invention provides much-needed
support not contemplated by any relevant art.
[0061] In a simplified sample procurement engine method implemented
in one embodiment of the invention, a method 3000 for real time or
near real time application of the e-commerce dynamic pricing tool
is shown in FIG. 14. In this example, the auction for keywords is
taking place for five minutes and will accept bids up to the
closing time. It also posts all bids in five second increments. The
time intervals from t1 to t5 given below are examples and not meant
to indicate that the e-commerce interface 100 is limited to
specific time intervals. However, as can be appreciated by those
skilled in the art, there may be a calculation for strategic timing
of specific acts, like evaluating and placing bids, for which the
e-commerce interface 100 may be particularly well suited for both
evaluation and execution purposes and an optional part of an
alternate embodiment. The following example also illustrates the
suitability for the present invention in such a time-constrained
acquisition environment.
[0062] At time t1 (-05:00), the customer procurement device engine
informs a user that desired keywords($A,$B)are being auctioned for
time period (Y to Y+INTERVAL). The bidding of click-throughs starts
at $0.05, which the e-commerce interface 100 monitors.
[0063] At time t2 (-04:25), the e-commerce interface 100 accesses
any performance data available either through the search engine
sites 50 or through the accumulated data stored in the virtual
storage 200. Also, at time t2 the financial engine 95 is accessed
for relevant information on a target product or set of products.
The individual product databases 92(n) may have to be accessed at
this time as well, if there is not a continuous update. The
e-commerce interface 100 also screens for potential permutations or
variations of the keyword that may be available and beneficial to
the user. This aspect of the invention is discussed below.
[0064] For auctions that use the open bid, like the english auction
model, at this (or another) time interval, the e-commerce interface
100 accesses the early bids for the keyword. Such early bids may
provide the global tool 185 or product tools 150(n) with valuable
information in computing the target keyword price range. In
particular embodiments, previous bid information may be available,
not only as absolute pricing information, but in the timed bidding
aspect as well. Thus, the e-commerce interface 100 has optional
built-in artificial intelligence module 198, of which one of the
functions is detecting pattern to (timed) auctions and developing a
rule in calculating the pricing target. In the background section,
there are several patents and publications relating to electronic
auctions are discussed, and those patents and publications are
hereby incorporated by reference for all purposes, and in
particular to illustrate the details of electronic auction and
related transactions.
[0065] At time t3A (-3:00), the e-commerce interface 100 prompts
the user 96 (or user/machine) for any missing information that must
be entered. If the user 96 cannot enter the information, the
interface 100 will have standing or contingency instructions as to
whether it should continue in the keyword auction.
[0066] If the bidding is to continue, at time t3B (-2:45), the
e-commerce interface 100 determines whether a bid is within range
of the calculated target price. If it is within range, then the bid
is either passed along to the user for bidding, or is posted to the
auction location. The permission may include any pre-registration
features that auction participation requires such as registering a
credit card or providing other personal or business information.
Although it is expected that many users will have pre-registered,
there may be advantages with not being pre-registered, as can be
appreciated. Permission steps may also include any time of
authorization by the user or officers, such as a comptroller, who
may be monitoring the bidding manually or automatically.
[0067] If the bid is not within the target range, the user is
informed that the bid has exceeded the target range. The user or
other authorizer may then choose to override the target range and
place a bid. Optionally, the bid may be entered manually and
directly posting or the e-commerce interface 100 via the global
tool 185 or product tools 150(n) which can adjust the new bid
incrementally or by other factors back to the permission stage.
[0068] At time t4 (-1:30), if permission is granted, the initial
bid is placed at the bid posting area 55, which may be on the
search engine server or computing machine 60 or in another
location, such as the transaction server for the auction. Any
posted bids are monitored until the target ending time (t5), when
the e-commerce interface 100 must assist the user with a final bid
decision. Thus, all bids until the time t5- evaluation time are
evaluated by the interface 100.
[0069] Also, at time t4, if permission is not granted, the data
regarding the bids and target range are recorded by the e-commerce
interface 100 as much as would be possible for future use and may
proceed to the next available advertising sale. For example, an
optional aspect to the invention is that it will gather data on
customer procurement tools even when acquisition fails and store
locally or globally in the virtual storage 200.
[0070] At time t5 (-0:30), with very little time left to go in the
auction, the e-commerce interface 100 determines whether a new bid
is warranted based on any new information, particularly new bids.
If a new bid is warranted and still within the target range then
the user is informed and/or the bid is posted to the bid posting
area 55. If the bid is not within range any more, the e-commerce
interface can opt out and simply record the data from the failure
or prompt the user to determine whether the user wants an override.
Of course, as can be appreciated the time intervals may be
constructed to allow for various user options. Thus, in an
embodiment where a user 96 manually posts a bid, there would be
more time allowed than 30 seconds. Whether or not the customer
procurement tool is acquired, the e-commerce interface 100 will
record and store the data in a preferred embodiment for future
decision support. However, if the customer procurement tool is
acquired, other monitoring algorithms may be implemented in order
to accurately determine value and performance of customer
procurement devices.
[0071] In a highly simplified scenario, the following numbers may
be included in a simplified calculation of the present invention:
For seller A, on Sunday, from 1-5 pm, the keyword "skin care
products" generates 17,500 click-throughs, 796 customers who
purchase $4,117 worth of merchandise. 525 of the 796 sales were for
skin care products.
1TABLE 1.1 Sample variables for calculating the relative real cost
of a click-through Variable Definition Example Previous Last
procurement of "keyword" $A = 0.17 per click-through Price Adj.
Factor Time period normalization factors present? (Sunday 1-5 pm) Y
= N* 1.17 CT Rate Number of click-throughs per hour 17,500/4 hrs =
4375 cts/hr Conv. Rate Customer procurement (actual purchase) to
22:1 click-through ratio Rev. per Gross revenue per sale $5.17 Sale
Ret. Cust Return customers (from click-through sale) = 12.7% (per 6
months) Ret. Return customers through click-throughs = 5% (per 6
months) Cust/CT Keywrd/ Customers who bought products related to
the 525/796 = 66% Sale product keyword (if more than one set of
products)
[0072] In this table the Sunday 1-5 pm slot gets 17% more traffic
than the average daytime amount of traffic. Thus, the search engine
auction for the skin care products keyword may adjust the lowest
bidding price. However, the search engine may not adjust pricing at
all, and the e-commerce interface 100 will have to account for such
factors (if executed by the user) in order to accurately bid on a
keyword. This table also represents previous data of one user
during one time period. As can be appreciated by those skilled in
the art, the collection of data for multiple entities or search
engines for multiple keyword performances will require a great deal
of computing power and data storage. The present invention
contemplates that providing optional accesses by individual
e-commerce interfaces 100 to a centralized data storage 200 and
virtual implementation computing system 250 may be advantageous to
all embodiments of the invention whether virtual or physical and
regardless of location.
[0073] The above table is representative of summary data that may
be provided by the search engine site, or collected by the present
invention for each search engine or each user. It is also
contemplated that a pool of users of the present invention collect
their data in a central data storage such that the set of customers
has access to alternate or better information regarding performance
than the search engines. Varying levels of data access may also be
implemented in particular embodiments.
2TABLE 1.2 Sample calculations used from variables in determining
performance Calc. Definition Example GR/CT Gross revenue per
click-through $4117/17,500 Acquisition Cost of any new customer
sale per (.17 * 22) - 12.7% price of click-throughs (returning
customer) = $3.29 Target Margin of primary product or set of ($1.27
* 450)/17500 Product/CT products for keyword per click- through
Crossover Percentage of sale for unrelated "skin care" = products
from a keyword 34% xsell @ $6.17 per sale
[0074] Of course, these are highly simplified factors and
calculations and are just some examples of how the present
invention may use such variables and support factors to provide a
target price to the user. As can be appreciated by those skilled in
the art, there are numerous other factors that can be amalgamated
into the decision many of which are listed in the specification.
The specific set of variables that is applied will depend on many
factors chosen by the user of the e-commerce interface 100 and the
structure and implementation of the present invention. For example,
global rules are more likely applied to embodiments of the
invention that take the form of a subscription service.
[0075] Thus, the present invention contemplates that calculating
the cost of a click-though will need to account for all the
financial information related to a product and all relevant pricing
information. There is no reason that the e-commerce interface 100,
which includes the global tool 185 and product tools 150(n), cannot
pre-configure or calculate much of this needed information in order
to better conduct real-time or near real-time analysis while using
less computer resources at time-critical periods. A sample of
database items from an accounting package executed on the financial
engine 95 would be processed before auctions in order to generate
any pre-configured parameters.
[0076] As stated above, rules for pricing based on the information
may be applied in various ways without departing from the spirit of
the present invention. Rules may be applied from a central location
for a subscription service embodiment generated by virtual
implementation computer 250 or applied on the user's computation
device 98(n) in an embodiment of the invention that can be executed
locally or both. Rule sets may be defined by both general
principles of transactions and customization routines specific to
particular entities. In the simplest embodiment the global tool 185
will apply a set of rules, which can be chosen by a user 96 in a
setup configuration. Of course, the rule sets will change for each
individual user 96 based on data captured and analyzed from
previous customer procurement acquisition attempts by either the
individual or collectively.
3TABLE 1.3 Sample application of rules for pricing products Rules
for keyword Scenario procurement/product pricing Pricing of one
single item F Rule 1 (A) Pricing of multiple single items F
(<25) Rule 1 (B) = 15% discount Pricing of multiple single items
F (>25) Rule 1 (C) = 15% + .1 discount over 25 ct. Pricing of
subset A (D, E, F, G) of total Rule 2 (B) = average of price of
inventory multiple items each item plus 15% discount Pricing of any
number of each item in Rule (3, All sale) = only count total
inventory (D-H) average of 5 most expensive items and subtract
shipping costs
[0077] The above table provides for a highly simplified rule
application by the global or individual product tools 150(n).
Obviously, the more the sales of one or more products the less the
relative real cost of a click-through. However, there are factors
that may optionally be accounted for differently for each user of
the e-commerce interface 100. For example in Rule 3, "all sale"
would make sense for a large entity that had a large price range of
products and low shipping costs and where only the higher priced
items should be included in the calculation of the advertising
procurement target range. However, Rule 1(B) would be more
applicable to a small entity with large shipping costs and small
margin on product F (perhaps even a loss). Thus, the purchase of 24
items F does not provide the entity with a large profit over the
sale of 2 and no additional discount is applied until 25, in which
the shipping costs drop enough to make a profit, when Rule 1(C)
would apply. Thus, Rule 1(B) may be a good rule application where a
site uses F as its signature product or customer draw to the
website in order to sell more profitable products.
[0078] As stated above, it is not necessary for the invention to be
limited to the pricing of advertising because the invention works
in inverse as well to dynamically adjust the price of a single
product, multiple single products or multiple sales of plural
products. Thus, the price of F, which is the signature product of
the company, and is sold at a loss, can be dynamically determined
by the real cost of the click-through. The real cost can be
constantly updated to improve the profit generated from a
click-through or to prevent too many losses. For example, a
click-through costs $1.00 and the profit margin of product F before
advertising is $0.25. Thus for a click-through/ conversion ratio of
10:1 for each single F sold, the more the company loses $9.75.
However, if a purchaser buys 40 Fs at time, the company breaks
even. Thus, the e-commerce interface will determine that if the
click through/conversion ration improves or the average sale of F
(or related and more profitable products) increases, the more the
company can afford to lower the price of F based on a volume
discount. However, if consumers are only purchasing a single F at a
loss of $9.75 per sale, the e-commerce interface 100 can adjust the
price such that losses are minimized.
[0079] The price determination may also account for other market
factors based on usage, timing, etc., and is loaded at step 2150
and applied in step 2190. For example, a problem with any type of
English auction bidding is that the experts generally submit bids
at the last minute, hiding their true intentions and expert bidding
from less experienced entities. Thus, less experienced bidders may
overbid, driving up the price unnecessarily. Dutch auctions may
eliminate the time pressure aspect present in the English auction
for a keyword that drives the price upward toward the end of the
bidding. Step 2149 may detect the situation and step 2150 applies a
rule that50 may account for this spike in keyword bidding and
advise the user accordingly in step 2190. As such, the e-commerce
interface 100 will have intelligence capabilities built into the
global tool 185 and product tools 150(n).
[0080] As can be appreciated by those skilled in the art, the
performance of a click-through has many variables involved not the
least of which is often dependent on the search engine site itself.
Of course, the metrics accumulated by the search engines themselves
may be important criteria in showing the true value of a "click
through" or an "impression" (or other advertising mechanism). As
such, the present invention helps a user to successfully analyze of
information controlled by the search engine services and gives a
bidder for a customer procurement device real-time assistance in
acquiring such advertising with all available performance data. Of
course, payment for a "click-through" may be a fairly good
indicator of how many people are responding to an advertisement,
but really does not measure the cost-effectiveness in total. To
some degree there may be some uncertainty built into Internet
advertising performance measures, but the present invention can
account for variances by accumulating and storing information for
use in the e-commerce interface 100. Such data may be acquired in a
single location or virtually and disseminated in the e-commerce
calculation) as part of an alternate embodiment of the invention.
As such, comparisons between search sites, keyword elements and
permutations, and variations, among other factors, have already
been discussed above.
[0081] Referring now to FIG. 15, a multiple search engine
embodiment of the invention is shown. This embodiment simply has
multiple search engines 50(1) . . . 50(n) on which keywords or
other customer procurement devices may be acquired. This embodiment
is similar to the single search engine keyword procurement
embodiment described in FIG. 3, except that the virtual performance
data storage 200 will have an inter-site comparison module 998.
This module will access and/or store individual performance
data-related sites and keywords and related information. A
simplified example is shown in the table of FIG. 16, which compares
the pricing and performance characteristics for three search
engines 50(1) . . . 50(3), and is a table showing a sample database
of table query as would be used by an embodiment of the present
invention as used in the multiple search engine keyword acquisition
shown. As can be appreciated by those skilled in the art, the
factors used in determining an appropriate auction price may vary
widely and take in account time of day, type of word, etc.
[0082] Referring now to FIG. 17, an embodiment of the present
invention which factors in keyword "elements" for acquisition is
shown. For example, entity A wishes to purchase "discount Caribbean
cruises," which has proven to be an effective keyword tool for
entity A. However, due to a recent revision of a couple of keyword
systems, the desired keywords have been divided into different
categories. Thus, "discount cruises" and "discount Caribbean" are
available. However, e-commerce interface 100 has data that most of
the keyword searches for cruises are in fact looking to go on a
Caribbean cruise when purchased in January. Thus, the
unavailability and competition for "discount cruises" may be high,
but the purchase of the term "discount Caribbean" may be acquired
at better performance-to-price ratios. The table shown in FIG. 18
is an example of how this calculation may be made.
[0083] Referring now to FIGS. 19-20, yet another embodiment of the
invention that contemplates possible multiple search engines, key
word segmentation and/or permutations is shown. By "permutations"
at least two different types of things are meant. First, there are
key synonym variations on the target keyword that are valuable for
an entity which may recognize that targeting a small group of
searches of a certain type can lead to improved sales. Second, as
is common in keyword searching, spelling errors are fairly common
in using search engines, and such misspellings may often be a
valuable capture for an entity looking to capitalize on such
exposure.
4TABLE 2.1 Sample keyword permutations and weighting factors (type
I) Relative Incidence Relative Price Keyword per Performance Search
Eng. Factor for Synonyms Target (/100) to Target (/1) Adjustment
Acquisition "dermatology" 22 1.3 N/A Apply rule X "dry skin 34 .75
N/A Apply rule Y treatment" "skin care" 55 .65 N/A Apply rule Y
"dermatologist 6 3.2 N/A Apply rule Z approved"
[0084] Of course, rules X, Y, and Z are hypothetical financially
based algorithms that are applied based on the target needs of the
users. For example, rule Z may apply in situations where the
incidence of the alternate keyword is very low (0.06), but the
performance is very high (over 3 times normal). Thus, the value of
this keyword may be higher based on traffic factors, like time of
day, day of week, sophistication of the search engine, etc. Rules X
and Y may be more straightforward, possibly even linear pricing
factors. Furthermore, there is not enough data on this table to
account for any search engine factor, but after the purchase of a
keyword, or even through the accumulation of data by the search
engine 50 itself, the data may become available. As stated above,
this data may be available as part of a sales tool, or as part of a
subscription or downloadable data service provided as a supplement
to the present invention.
5TABLE 2.2 Sample keyword permutations and weighting factors (type
II) Relative Relative Price Search Keyword Incidence per
Performance Factor for Eng. Variations Target (/100) to Target
Acquisition Factor "dermotology" 2.1 1.1 Rule A N/A "dermoltgy" .7
.87 Rule A N/A "dirmotology" .4 .89 Rule C N/A "dermotological" .34
.05 Rule B N/A
[0085] The above table acts very much like table 2.1 in that it
accounts for the past performance of mistaken spellings of the
target keyword in order to provide a value for acquiring a
misspelled keyword. Of course, not all keyword auctions or sales
may offer the kinds of variations sales that are discussed in this
specification. However, search engines and other advertisers may
recognize the value of these variations either packaged as a bundle
with the target keyword or purchased for "residual" value by other
entities. Certainly, a purchaser of a bundle of keywords, which
include synonyms and misspellings, may resell one or more of the
set to another entity. The present invention contemplates the
resale of such keywords in order to maximize the value to a user.
For example, a purchaser who buys words A, A', and A" for 32 cents
a click-through may find that keyword A and variation A" are
valuable for customer procurement and sales of product X1, but A'
is not useful. Thus the purchaser desires to sell A' to a
subpurchaser who may benefit from using it in the sale of products
Y1 and Z1.
[0086] In a preferred embodiment, the present invention
contemplates the key word auction as the primary use of the method
by which the present invention operates. However, as can be
appreciated by those skilled in the art, other types of purchases
for various types of customer procurement mechanisms may be
acquired though the teachings of the present invention. The present
invention contemplates various levels of search engine optimization
methods which link up with a user's financial engine 95(n) in order
to provide the most effective use of advertising channels for
particular products. The intelligence module 198 of the e-commerce
interface 100 will be responsible for generating rule sets based on
such information.
[0087] Referring now to FIG. 21 an automated method for the
customer procurement device (advertising channel) acquisition
system 2700 is shown. The automated customer procurement device has
a scheduling and notification module 300 as a virtual part of
e-commerce interface 100. The scheduling and notification module
300 may be physically located on the computing device. The
scheduling and notification module 300 can self-activate in step
2710 or monitor keyword selling sites discretely or continuously in
step 2720. If the module finds that a target keyword is available
in step 2750, then the method shown and described in FIG. 10 above
is performed in step 2760. If the system is not deactivated in step
2762 it returns to the monitoring state. Simultaneously, if the
system was not successful in step 2770, it performs a notification
and adjustment in step 2780. If it was successful it records any
performance detection programs in step 2790 before being
reactivated.
[0088] Referring now to FIG. 22, a cross-selling, up-selling and/or
agency system 5000 using the present invention is shown and
includes one or more vendor systems 70(n) and one or more buyer
systems 40(n). The e-commerce interface 100 advises the user 90 who
is now brokering both between one or more vendors 70(n) and
purchasers 40(n) as well as procuring Internet advertising devices
on search engines 50 at the same time. As can be appreciated, the
complexity of such dynamic transactions almost requires the dynamic
pricing e-commerce interface 100 to maximize potential profits and
assist with the pricing.
[0089] The invention is also clearly suited for dynamic pricing
support for the purchase of banner ads or impression based on
similar criteria as recited in the keyword placement. The placement
of banner ads or impressions may or may not be related to specific
criteria collected by the selling of the advertisements. However,
the invention contemplates measuring any criteria, which are
indicators of advertising performance for relative pricing. Thus,
if a banner ad or a series of banner ads (for example, in sets of
1000) is (are) placed in response to a user action or inquiry, and
has a particular effective click-through rate, the conditions, as
best they can be determined, are recorded and implemented by the
e-commerce interface 100, through the intelligence module 198. As
can be appreciated by those skilled in the are, the amount of data
required to improve intelligence capabilities may be very large and
accumulated on virtual storage location 200 in stages or by other
entities.
[0090] Referring now to FIG. 23, an affiliate-linking embodiment
method 4000 of the invention is shown. The mechanisms that power
the keyword advertising procurement method in FIG. 10 are quite
similar to the affiliate linking method. As can be appreciate by
those skilled in the art, the performance data may be based on a
different type of mechanism, like a commission on a sale, or still
based on a click-through. The commission for the link may be
processed and negotiated by similar mechanism as described above in
the keyword auction. The e-commerce interface 100 will still link
with the user's financial engine 95(n) in order to determine the
appropriate cost of advertising or correct the product pricing at
step 4800. In the same way that the e-commerce interface 100 can
respond to the keyword auction in various embodiments (dutch,
english), the affiliate can negotiate a commission in the same
basic manner, although it may not have the same time constraints
(although the auction may be for a commission percentage as well).
Step 4098 provides for a commission tracking effectiveness step
which is performed by the e-commerce interface as the
commission-based advertising may have additional tracking
requirements.
[0091] As can be also appreciated by those skilled in the art,
while the present invention is contemplated in a preferred
embodiment to assist those seeking to acquire keywords for
impressions or click-throughs, or affiliate links, there are other
advertising devices that would be appropriately acquired in similar
environments by the present invention. The present invention is
also dynamic and scalable, as can be appreciated by those skilled
in the art, and can be used by individuals as well as large
Internet sales organizations.
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