U.S. patent application number 14/473654 was filed with the patent office on 2016-03-03 for methods and apparatus to associate transactions with media impressions.
The applicant listed for this patent is The Nielsen Company (US), LLC. Invention is credited to Madhusudhan Reddy Alla, Jillian Renee Rollinger.
Application Number | 20160063539 14/473654 |
Document ID | / |
Family ID | 52006786 |
Filed Date | 2016-03-03 |
United States Patent
Application |
20160063539 |
Kind Code |
A1 |
Alla; Madhusudhan Reddy ; et
al. |
March 3, 2016 |
METHODS AND APPARATUS TO ASSOCIATE TRANSACTIONS WITH MEDIA
IMPRESSIONS
Abstract
Methods and apparatus to associate transactions with media
impressions are disclosed. An example method includes transmitting
a request for commercial transaction information to a database
proprietor, the request including an identifier corresponding to a
media impression associated with media presented via a computing
device; receiving the commercial transaction information in
response to the request, the commercial transaction information
comprising data associated with a commercial transaction conducted
using an account accessed by the computing device; and associating
the media impression with the commercial transaction.
Inventors: |
Alla; Madhusudhan Reddy;
(Allen, TX) ; Rollinger; Jillian Renee; (Tampa,
FL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
The Nielsen Company (US), LLC |
Schaumburg |
IL |
US |
|
|
Family ID: |
52006786 |
Appl. No.: |
14/473654 |
Filed: |
August 29, 2014 |
Current U.S.
Class: |
705/14.45 |
Current CPC
Class: |
G06Q 30/0201 20130101;
G06Q 30/0251 20130101; G06Q 30/0259 20130101; G06Q 30/0246
20130101; G06Q 30/0242 20130101; G06Q 30/0261 20130101; G06Q
30/0271 20130101; G06F 16/245 20190101 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02 |
Claims
1. A method comprising: transmitting a request for commercial
transaction information to a database proprietor, the request
including an identifier corresponding to a media impression
associated with media presented via a computing device; receiving
the commercial transaction information in response to the request,
the commercial transaction information comprising data associated
with a commercial transaction conducted using an account accessed
by the computing device; and associating, using a processor, the
media impression with the commercial transaction.
2. A method as defined in claim 1, wherein the identifier comprises
at least one of a unique identifier of the computing device or a
user identifier of a user associated with the account.
3. A method as defined in claim 1, further comprising identifying a
product represented in the media corresponding to the media
impression, the request further comprising a product identifier of
the product.
4. A method as defined in claim 3, wherein the media is an
advertisement for the product or media content including an
intentional product placement of the product in the media
content.
5. A method as defined in claim 1, wherein associating the media
impression with the commercial transaction comprises: determining
that the identifier corresponding to the media impression matches
an account identifier associated with the account used to perform
the commercial transaction; determining that the commercial
transaction involved a product or service represented in the media
corresponding to the media impression; and determining that the
media impression occurred prior to the commercial transaction.
6. A method as defined in claim 1, wherein the commercial
transaction information comprises a product identifier of a product
purchased in the commercial transaction and a date of the
commercial transaction.
7. A method as defined in claim 1, further comprising calculating a
media effectiveness metric for the media by: grouping first device
identifiers in a control set, the first device identifiers being
associated with computing devices not receiving the media, the
media corresponding to the media impression and representing a
product; grouping second device identifiers in an exposed set, the
second device identifiers being associated with computing devices
on which impressions of the media representing the product
occurred, and the first and second device identifiers being
recognizable by a merchant of the product; determining a difference
between sales corresponding to the first device identifiers and
sales corresponding to the second device identifiers; and
calculating the media effectiveness metric based on the sales
difference.
8. A method as defined in claim 1, further comprising calculating a
publisher effectiveness metric by: grouping first device
identifiers corresponding to impressions occurring via a first
publisher; grouping second device identifiers corresponding to
impressions occurring via a second publisher, the first device
identifiers and the second device identifiers being associated with
computing devices on which impressions of the media representing a
product occurred, and the first device identifiers and the second
device identifiers being recognizable by a merchant of the product;
determining a first sales lift for the first publisher based on
sales corresponding to the first device identifiers; determining a
second sales lift for the second publisher based on sales
corresponding to the second device identifiers; determining a sales
lift difference between the first sales lift and the second sales
lift; and calculating the publisher effectiveness metric for at
least one of the first publisher or the second publisher based on
the sales lift difference.
9. A method as defined in claim 1, wherein the commercial
transaction information is received from a proprietor of an
application executed on the computing device.
10. An apparatus, comprising: a transaction requester to request
commercial transaction information associated with a device
identifier, the device identifier corresponding to a media
impression occurring at a computing device; and a matcher to
associate the media impression with a commercial transaction
conducted using an account accessed by the computing device, the
matcher to associate the media impression with the commercial
transaction based on the commercial transaction information
received in response to the request, at least one of the
transaction requester or the matcher being implemented by a logic
circuit.
11. An apparatus as defined in claim 10, wherein the matcher is to
associate the media impression with the commercial transaction by:
determining that the device identifier corresponding to the media
impression matches a stored device identifier associated with the
account used to perform the commercial transaction; determining
that the commercial transaction is associated with a product
represented in media corresponding to the media impression; and
determining that the media impression occurred prior to the
commercial transaction.
12. An apparatus as defined in claim 10, further comprising a
product checker to identify a product represented in media
corresponding to the media impression, the request further
comprising a product identifier of the product.
13. An apparatus as defined in claim 12, wherein the media is an
advertisement for the product or media content including an
intentional product placement of the product in the media
content.
14. An apparatus as defined in claim 10, further comprising: a
group identifier to identify first device identifiers as a control
set and to identify second device identifiers as an exposed set,
the first device identifiers being collected from computing devices
not receiving media representing a product, the second device
identifiers being collected from computing devices on which
impressions of the media representing the product occurred, and the
first and second device identifiers being recognizable by a
merchant of the product; a transaction aggregator to determine a
difference between sales corresponding to the control set and sales
corresponding to the exposed set; and an effectiveness calculator
to calculate a media effectiveness metric based on the sales
difference.
15. An apparatus as defined in claim 10, further comprising: a
group identifier to identify first device identifiers associated
with media presented on first computing devices via a first
publisher and to identify second device identifiers associated with
media presented on second computing devices via a second publisher,
the media representing a product, and the first device identifiers
and the second device identifiers being recognizable by a merchant
of the product; a transaction aggregator to determine a first sales
lift based on sales corresponding to the first device identifiers
and to determine a second sales lift based on sales corresponding
to the second device identifiers; and an effectiveness calculator
to determine a sales lift difference between the first sales lift
and the second sales lift and to calculate a publisher
effectiveness metric for at least one of the first publisher or the
second publisher based on the sales lift difference.
16. A tangible computer readable storage medium comprising computer
readable instructions which, when executed, cause a logic circuit
to at least: transmit a request for commercial transaction
information to a database proprietor, the request including an
identifier corresponding to a media impression associated with
media presented via a computing device; access the commercial
transaction information in response to the request, the commercial
transaction information comprising data associated with a
commercial transaction conducted using an account accessed by the
computing device; and associate the media impression with the
commercial transaction.
17. A storage medium as defined in claim 16, wherein the identifier
comprises at least one of a unique identifier of the computing
device or a user identifier of a user associated with the
account.
18. A storage medium as defined in claim 16, wherein the
instructions are further to cause the logic circuit to identify a
product represented in the media corresponding to the media
impression, the request further comprising a product identifier of
the product.
19. A storage medium as defined in claim 16, wherein the
instructions are to cause the logic circuit to associate the media
impression with the commercial transaction by: determining that the
identifier corresponding to the media impression matches an account
identifier associated with the account used to perform the
commercial transaction; determining that the commercial transaction
involved a product or service represented in the media
corresponding to the media impression; and determining that the
media impression occurred prior to the commercial transaction.
20. A storage medium as defined in claim 16, wherein the commercial
transaction information comprises a product identifier of a product
purchased in the commercial transaction and a date of the
commercial transaction.
21. A storage medium as defined in claim 16, wherein the
instructions are further to cause the logic circuit to calculate a
media effectiveness metric for media corresponding to the media
impression by: grouping first device identifiers in a control set,
the first device identifiers being associated with computing
devices not receiving the media, the media corresponding to the
media impression and representing a product; grouping second device
identifiers in an exposed set, the second device identifiers being
associated with computing devices on which impressions of the media
representing the product occurred, and the first and second device
identifiers being recognizable by a merchant of the product;
determining a difference between sales corresponding to the first
device identifiers and sales corresponding to the second device
identifiers; and calculating the media effectiveness metric based
on the sales difference.
22. A storage medium as defined in claim 16, wherein the
instructions are further to cause the logic circuit to calculate a
publisher effectiveness metric by: grouping first device
identifiers corresponding to impressions occurring via a first
publisher; grouping second device identifiers corresponding to
impressions occurring via a second publisher, the first device
identifiers and the second device identifiers being associated with
computing devices on which impressions of the media representing a
product occurred, and the first device identifiers and the second
device identifiers being recognizable by a merchant of the product;
determining a first sales lift for the first publisher based on
sales corresponding to the first device identifiers; determining a
second sales lift for the second publisher based on sales
corresponding to the second device identifiers; determining a sales
lift difference between the first sales lift and the second sales
lift; and calculating a publisher effectiveness metric for at least
one of the first publisher or the second publisher based on the
sales lift difference.
23-42. (canceled)
Description
FIELD OF THE DISCLOSURE
[0001] The present disclosure relates generally to monitoring media
and, more particularly, to methods and apparatus to associate
transactions with media impressions.
BACKGROUND
[0002] Traditionally, audience measurement entities determine
audience engagement levels for media programming based on
registered panel members. That is, an audience measurement entity
enrolls people who consent to being monitored into a panel. The
audience measurement entity then monitors those panel members to
determine media (e.g., television programs or radio programs,
movies, DVDs, advertisements, etc.) exposed to those panel members.
In this manner, the audience measurement entity can determine
exposure measures for different media based on the collected media
measurement data.
[0003] Techniques for monitoring user access to Internet resources
such as web pages, advertisements and/or other media have evolved
significantly over the years. Some prior systems perform such
monitoring primarily through server logs. In particular, entities
serving media on the Internet can use such prior systems to log the
number of requests received for their media at their server.
BRIEF DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 depicts an example system to collect impressions of
media presented at mobile devices and to collect user information
from distributed database proprietors for associating with the
collected impressions.
[0005] FIG. 2 is an example impression-transaction analyzer which
may be implemented in the example audience measurement server of
FIG. 1 to compare and/or match impression information associated
with a mobile device to transaction information performed using a
user account accessed by the mobile device.
[0006] FIG. 3 illustrates an example table illustrating an example
determination of publisher effectiveness.
[0007] FIG. 4 is a graph illustrating the data in the example table
of FIG. 3.
[0008] FIG. 5 is a block diagram of an example transaction
information provider that may be used to implement the example
merchant database proprietor of FIG. 1.
[0009] FIG. 6 is a flow diagram representative of example machine
readable instructions which may be executed to implement the
example impression-transaction analyzer of FIG. 2 to associate
media impressions to transaction information.
[0010] FIG. 7 is a flow diagram representative of example machine
readable instructions which may be executed to implement the
example impression-transaction analyzer of FIG. 2 to correlate
transactions involving a product to media impressions corresponding
to the product.
[0011] FIGS. 8A and 8B show a flow diagram representative of
example machine readable instructions which may be executed to
implement the example impression-transaction analyzer of FIG. 2 to
determine media and publisher effectiveness.
[0012] FIG. 9 is a flow diagram representative of example machine
readable instructions which may be executed to implement the
example transaction information provider of FIG. 5 to associate
device/user identifiers to merchant database proprietor
accounts.
[0013] FIG. 10 is a flow diagram representative of example machine
readable instructions which may be executed to implement the
example transaction information provider of FIG. 5 to provide
transaction information.
[0014] FIG. 11 is a flow diagram representative of example machine
readable instructions which may be executed to implement the
example transaction information provider of FIG. 5 to provide
transaction information.
[0015] FIG. 12 is an example processor platform that may be used to
execute the example instructions of FIGS. 6-11 to implement example
apparatus and systems disclosed herein.
DETAILED DESCRIPTION
[0016] Techniques for monitoring user access to Internet resources
such as web pages, advertisements and/or other media have evolved
significantly over the years. At one point in the past, such
monitoring was done primarily through server logs. In particular,
entities serving media on the Internet would log the number of
requests received for their media at their server. Basing Internet
usage research on server logs is problematic for several reasons.
For example, server logs can be tampered with either directly or
via zombie programs which repeatedly request media from servers to
increase the server log counts corresponding to the requested
media. Secondly, media is sometimes retrieved once, cached locally
and then repeatedly viewed from the local cache without involving
the server in the repeat viewings. Server logs cannot track these
views of cached media because reproducing locally cached media does
not require re-requesting the media from a server. Thus, server
logs are susceptible to both over-counting and under-counting
errors.
[0017] The inventions disclosed in Blumenau, U.S. Pat. No.
6,108,637, fundamentally changed the way Internet monitoring is
performed and overcame the limitations of the server side log
monitoring techniques described above. For example, Blumenau
disclosed a technique wherein Internet media to be tracked is
tagged with beacon instructions. In particular, monitoring
instructions are associated with the Hypertext Markup Language
(HTML) of the media to be tracked. When a client requests the
media, both the media and the beacon instructions are downloaded to
the client. The beacon instructions are, thus, executed whenever
the media is accessed, be it from a server or from a cache.
[0018] The beacon instructions cause monitoring data reflecting
information about the access to the media to be sent from the
client that downloaded the media to a monitoring entity. Typically,
the monitoring entity is an audience measurement entity (AME)
(e.g., any entity interested in measuring or tracking audience
exposures to advertisements, media, and/or any other media) that
did not provide the media to the client and who is a trusted third
party for providing accurate usage statistics (e.g., The Nielsen
Company, LLC). Advantageously, because the beaconing instructions
are associated with the media and executed by the client browser
whenever the media is accessed, the monitoring information is
provided to the AME irrespective of whether the client is a
panelist of the AME.
[0019] It is useful, however, to link demographics and/or other
user information to the monitoring information. To address this
issue, the AME establishes a panel of users who have agreed to
provide their demographic information and to have their Internet
browsing activities monitored. When an individual joins the panel,
they provide detailed information concerning their identity and
demographics (e.g., gender, race, income, home location,
occupation, etc.) to the AME. The AME sets a cookie on the panelist
computer that enables the AME to identify the panelist whenever the
panelist accesses tagged media and, thus, sends monitoring
information to the AME.
[0020] Since most of the clients providing monitoring information
from the tagged pages are not panelists and, thus, are unknown to
the AME, it is necessary to use statistical methods to impute
demographic information based on the data collected for panelists
to the larger population of users providing data for the tagged
media. However, panel sizes of AMEs remain small compared to the
general population of users. Thus, a problem is presented as to how
to increase panel sizes while ensuring the demographics data of the
panel is accurate.
[0021] There are many database proprietors operating on the
Internet. These database proprietors provide services (e.g., social
networking services, email services, media access services, etc.)
to large numbers of subscribers. In exchange for the provision of
such services, the subscribers register with the proprietors. As
part of this registration, the subscribers provide detailed
demographic information. Examples of such database proprietors
include social network providers such as Facebook, Myspace,
Twitter, etc. These database proprietors set cookies on the
computers of their subscribers to enable the database proprietors
to recognize registered users when such registered users visit
their websites.
[0022] Traditionally, AMEs (also referred to herein as "ratings
entities") determine reach for advertising and media programming
based on registered panel members. That is, an AME enrolls people
that consent to being monitored into a panel. During enrollment,
the AME receives information from the enrolling people so that
subsequent correlations may be made between advertisement/media
exposure to those panelists and different demographic markets.
Unlike traditional techniques in which AMEs rely solely on their
own panel member data to collect demographics-based audience
measurement, example methods, apparatus, and/or articles of
manufacture disclosed herein enable an AME to share information
with other entities that operate based on user registration models.
As used herein, a user registration model is a model in which users
subscribe to services of those entities by creating an account and
providing information about themselves. Sharing of information
associated with registered users of database proprietors enables an
AME to extend or supplement their panel data with substantially
reliable information from external sources (e.g., database
proprietors), thus extending the coverage, accuracy, and/or
completeness of their audience measurements. Such access also
enables the AME to monitor persons who would not otherwise have
joined an AME panel. Any entity having a database identifying
characteristics of a set of individuals may cooperate with the AME.
Such entities may be referred to as "database proprietors" and
include entities such as wireless service carriers, mobile
software/service providers, social medium sites (e.g., Facebook,
Twitter, Google, etc.), and/or any other Internet sites such as
Yahoo!, MSN, Apple iTunes, Experian, etc. that collect demographic
data of users which may be in exchange for a service.
[0023] Examples disclosed herein may be implemented by an AME
(e.g., any entity interested in measuring or tracking audience
exposures to advertisements, media, and/or any other media) in
cooperation with any number of database proprietors such as online
web services providers to develop online media exposure metrics.
Such database proprietors/online web services providers may be
wireless service carriers, mobile software/service providers,
social network sites (e.g., Facebook, Twitter, MySpace, etc.),
multi-service sites (e.g., Yahoo!, Google, Experian, etc.), online
retailer sites (e.g., Amazon.com, Buy.com, etc.), and/or any other
web service(s) site that maintains user registration records.
[0024] An impression corresponds to a home or individual having
been exposed to the corresponding media and/or advertisement. Thus,
an impression represents a home or an individual having been
exposed to an advertisement or media or group of advertisements or
media. In Internet advertising, a quantity of impressions or
impression count is the total number of times an advertisement or
advertisement campaign has been accessed by a web population (e.g.,
including number of times accessed as decreased by, for example,
pop-up blockers and/or increased by, for example, retrieval from
local cache memory).
[0025] As used herein, the term "product" is expressly defined to
refer to any type of purchasable item, whether tangible or
intangible. In particular, the term "product" is expressly defined
to include goods, services, combinations of goods and/or services,
and items that are part-good and part-service.
[0026] Examples methods and apparatus disclosed herein may be used
to correlate media impressions occurring on mobile devices to
subsequent commercial transactions. Example commercial transactions
include purchases of a product from an online merchant such as
Amazon.RTM., eBay.RTM., or any other online merchant, including
online merchants that also have physical locations at which
transactions may occur directly with consumers (e.g., brick and
mortar stores). Example methods and apparatus disclosed herein may
be used to measure the effectiveness of mobile advertising
campaigns by comparing sales of a product from a time period prior
to an advertising campaign to sales of the product from a time
period subsequent to an advertising campaign. Additionally or
alternatively, disclosed example methods and apparatus may be used
to compare the effectiveness of media between different publishers
(e.g., publisher effectiveness).
[0027] Significantly, example methods and apparatus disclosed
herein are capable of tracking the correlation of media impressions
to changes in purchase habits at the individual user account level
(e.g., an account kept with the merchant by a user, which is used
to purchase a product from that merchant). For example, a media
impression occurring at a device having a unique identifier may be
matched to the subsequent purchase of a product advertised in the
media impression. In response, examples disclosed herein may be
used to draw the inference that the media impression was related to
influencing the subsequent purchase. Additionally, the correlation
between media impressions and sales can be determined for devices
and/or user accounts with which the audience measurement entity
does not have any prior information or prior relationship.
[0028] To match media impressions to purchases, example methods and
apparatus disclosed herein utilize a user/device identifier and
media impression information collected from a mobile device. The
example media impression information represents media impressions
occurring at the mobile device. In example methods and apparatus,
commercial transaction information associated with the user/device
identifier is also obtained. Example commercial transaction
information includes data describing commercial transactions
conducted using an account that has been accessed by a device
associated with the user/device identifier. A user account may be
correlated to multiple unique identifiers. Example methods and
apparatus disclosed herein associate the media impression
information with the commercial transaction information to, for
example, determine a cause and effect relationship between the
impression and the commercial transaction. Examples disclosed
herein may match impressions occurring on one device with
transactions performed using a different device.
[0029] Examples of device types from which user/device identifiers
may be collected include smartphones (e.g., iPhones, Android
OS-based smartphones, Blackberry smartphones, Windows Mobile-based
smartphones, etc.), tablet computers (e.g., iPads, Android OS-based
tablet computers, etc.), portable media players (e.g., iPods,
etc.), and/or other device types. Such device types may be
cookie-based devices (e.g., devices that run cookie-based
applications/software) and/or non-cookie-based devices (e.g.,
devices such as Apple iOS devices that run applications/software
that do not employ cookies).
[0030] While examples disclosed herein are described with reference
to compensating or adjusting impression information obtained from
mobile devices, the examples are also applicable to non-mobile
devices such as desktop computers, televisions, video game
consoles, and/or other devices.
[0031] In contrast to prior art methods of evaluating the
effectiveness of media, example methods and apparatus disclosed
herein leverage the computing device-based and network-based
delivery of media impressions, as well as the use of online
transaction platforms, to evaluate the effectiveness of media at
actually driving (or inhibiting) sales activity. Some such example
methods and apparatus reduce the manual resources, computing
resources, and networking resources used to collect, analyze,
and/or correlate impression information and transaction information
to evaluate media effectiveness at driving product sales. Some
examples enable the conservation of computing and/or networking
resources by relating transactions to impressions via a unique
identifier, thereby reducing or eliminating computations and/or
communications previously required to determine a transaction from
the occurrence of an impression at a computing device (e.g.,
identifying the user, retrieving information about the user,
determining whether the user has an account at a merchant,
obtaining permission from the user to access his or her account
information, sorting through the transactions to identify the
products, etc.).
[0032] Furthermore, example methods and apparatus disclosed herein
provide more accurate measurements than prior methods of estimating
media effectiveness at driving product sales, because the
impression data and the transaction data more accurately reflect
the actual incidences of impressions and sales and because
impressions are linked directly to corresponding sales by relating
the impression data to the transaction data. This achieves a
significant improvement in the audience analytics and advertising
field. Such improvements can reduce the amount of network resources
used for delivering advertisements by enabling the quick
elimination of ineffective advertisements and/or ineffective
advertisement platforms. In a world of limited resources, this
elimination of waste has the beneficial effect of freeing resources
for other beneficial purposes.
[0033] FIG. 1 depicts an example system 100 to collect user
information (e.g., user information 102) from a database proprietor
104 for associating with impressions of media presented at a mobile
device 106. In the illustrated examples, user information 102 or
user data includes one or more of demographic data, purchase data,
and/or other data indicative of user activities, behaviors, and/or
preferences related to information accessed via the Internet,
purchases, media accessed on electronic devices, physical locations
(e.g., retail or commercial establishments, restaurants, venues,
etc.) visited by users, etc. Examples disclosed herein are
described in connection with a mobile device, which may be a mobile
phone, a mobile communication device, a tablet, a gaming device, a
portable media presentation device, etc. However, examples
disclosed herein may be implemented in connection with non-mobile
devices such as internet appliances, smart televisions, internet
terminals, computers, or any other device capable of presenting
media received via network communications.
[0034] In the illustrated example of FIG. 1, to track media
impressions on the mobile device 106, an audience measurement
entity (AME) 108 partners with or cooperates with an app publisher
110 to download and install a data collector 112 on the mobile
device 106. In the example of FIG. 1, the AME 108 provides the data
collector 112 to the app publisher 110 for inclusion of the data
collector 112 in apps downloaded by mobile devices from the app
publisher 110. The app publisher 110 of the illustrated example may
be a software app developer that develops and distributes apps to
mobile devices and/or a distributor that receives apps from
software app developers and distributes the apps to mobile devices.
The data collector 112 may be included in other software loaded
onto the mobile device 106, such as the operating system 114, an
application (or app) 116, a web browser 117, and/or any other
software.
[0035] Any of the example software 114-117 may present media 118
received from a media publisher 120. The media 118 may be an
advertisement, video, audio, text, a graphic, a web page, news,
educational media, entertainment media, or any other type of media.
In the illustrated example, a media ID 122 is provided in the media
118 to enable identifying the media 118 so that the AME 108 can
credit the media 118 with media impressions when the media 118 is
presented on the mobile device 106 or any other device that is
monitored by the AME 108.
[0036] The data collector 112 of the illustrated example includes
instructions (e.g., Java, java script, or any other computer
language or script) that, when executed by the mobile device 106,
cause the mobile device 106 to collect the media ID 122 of the
media 118 presented by the app program 116 and/or the mobile device
106, and to collect one or more device/user identifier(s) 124
stored in the mobile device 106. The device/user identifier(s) 124
of the illustrated example include identifiers that can be used by
the demographic database proprietor 104 to identify the user or
users of the mobile device 106, and to locate user information 102
corresponding to the user(s). For example, the device/user
identifier(s) 124 may include hardware identifiers (e.g., an
international mobile equipment identity (IMEI), a mobile equipment
identifier (MEID), a media access control (MAC) address, etc.), an
app store identifier (e.g., a Google Android ID, an Apple ID, an
Amazon ID, etc.), an open source unique device identifier
(OpenUDID), an open device identification number (ODIN), a login
identifier (e.g., a username), an email address, user agent data
(e.g., application type, operating system, software vendor,
software revision, etc.), third-party service identifiers (e.g., an
"Identifier for Advertising" (IDFA), advertising service
identifiers, device usage analytics service identifiers,
demographics collection service identifiers), web storage data,
document object model (DOM) storage data, local shared objects
(also referred to as "Flash cookies"), etc. In some examples, fewer
or more device/user identifier(s) 124 may be used. In addition,
although only one demographic database proprietor 104 is shown in
FIG. 1, the AME 108 may partner with any number of demographic
database proprietors to collect distributed user information (e.g.,
the user information 102).
[0037] In some examples, the mobile device 106 may not allow access
to identification information stored in the mobile device 106. For
such instances, the disclosed examples enable the AME 108 to store
an AME-provided identifier (e.g., an identifier managed and tracked
by the AME 108) in the mobile device 106 to track media impressions
on the mobile device 106. For example, the AME 108 may provide
instructions in the data collector 112 to set an AME-provided
identifier in memory space accessible by and/or allocated to the
app program 116. In some such examples, the data collector 112 uses
the identifier as a device/user identifier 124. In such examples,
the AME-provided identifier set by the data collector 112 persists
in the memory space even when the app program 116 and the data
collector 112 are not running. In this manner, the same
AME-provided identifier can remain associated with the mobile
device 106 for extended durations and/or be used across multiple
apps. In some examples in which the data collector 112 sets an
identifier in the mobile device 106, the AME 108 may recruit a user
of the mobile device 106 as a panelist, and may store user
information collected from the user during a panelist registration
process and/or collected by monitoring user activities/behavior via
the mobile device 106 and/or any other device used by the user and
monitored by the AME 108. In this manner, the AME 108 can associate
user information of the user (from panelist data stored by the AME
108) with media impressions attributed to the user on the mobile
device 106.
[0038] In the illustrated example, the data collector 112 sends the
media ID 122 and the one or more device/user identifier(s) 124 as
collected data 126 to the app publisher 110. Alternatively, the
data collector 112 may be configured to send the collected data 126
to another collection entity (other than the app publisher 110)
that has been contracted by the AME 108 or is partnered with the
AME 108 to collect media ID's (e.g., the media ID 122) and
device/user identifiers (e.g., the device/user identifier(s) 124)
from mobile devices (e.g., the mobile device 106).
[0039] In the illustrated example, the app publisher 110 (or a
collection entity) sends the media ID 122 and the device/user
identifier(s) 124 as impression data 130 to a server 132 at the AME
108. The impression data 130 of the illustrated example may include
one media ID 122 and one or more device/user identifier(s) 124 to
report a single impression of the media 118, or it may include
numerous media ID's 122 and device/user identifier(s) 124 based on
numerous instances of collected data (e.g., the collected data 126)
received from the mobile device 106 and/or other mobile devices to
report multiple impressions of media.
[0040] In the illustrated example, the server 132 stores the
impression data 130 in an AME media impressions store 134 (e.g., a
database or other data structure). Subsequently, the AME 108 sends
the device/user identifier(s) 124 to the demographic database
proprietor 104 to receive user information 102 corresponding to the
device/user identifier(s) 124 from the demographic database
proprietor 104 so that the AME 108 can associate the user
information with corresponding media impressions of media (e.g.,
the media 118) presented at mobile devices (e.g., the mobile device
106).
[0041] In some examples, to protect the privacy of the user of the
mobile device 106, the media identifier 122 and/or the device/user
identifier(s) 124 are encrypted before they are sent to the AME 108
and/or to the demographic database proprietor 104. In other
examples, the media identifier 122 and/or the device/user
identifier(s) 124 are not encrypted.
[0042] After the AME 108 receives the device/user identifier(s)
124, the AME 108 sends device/user identifier logs 136 to the
demographic database proprietor 104. In some examples, each of the
device/user identifier logs 136 may include a single device/user
identifier 124, or it may include numerous aggregate device/user
identifiers 124 received over time from one or more mobile devices.
After receiving the device/user identifier logs 136, the
demographic database proprietor 104 looks up its users
corresponding to the device/user identifiers 124 in the respective
logs 136. In this manner, the demographic database proprietor 104
collects user information 102 corresponding to users identified in
the device/user identifier logs 136 for sending to the AME 108. For
example, if the demographic database proprietor 104 is a wireless
service provider and the device/user identifier log 136 includes
IMEI numbers recognizable by the wireless service provider, the
wireless service provider accesses its subscriber records to find
users having IMEI numbers matching the IMEI numbers received in the
device/user identifier log 136. When the users are identified, the
wireless service provider copies the users' user information to the
user information 102 for delivery to the AME 108.
[0043] In some other examples, the data collector 112 is configured
to collect the device/user identifier(s) 124 from the mobile device
106. The example data collector 112 sends the device/user
identifier(s) 124 to the app publisher 110 in the collected data
126, and it also sends the device/user identifier(s) 124 to the
media publisher 120. In some such other examples, the data
collector 112 does not collect the media ID 122 from the media 118
at the mobile device 106 as the data collector 112 does in the
example system 100 of FIG. 1. Instead, the media publisher 120 that
publishes the media 118 to the mobile device 106 retrieves the
media ID 122 from the media 118 that it publishes. The media
publisher 120 then associates the media ID 122 to the device/user
identifier(s) 124 received from the data collector 112 executing in
the mobile device 106, and sends collected data 138 to the app
publisher 110 that includes the media ID 122 and the associated
device/user identifier(s) 124 of the mobile device 106. For
example, when the media publisher 120 sends the media 118 to the
mobile device 106, it does so by identifying the mobile device 106
as a destination device for the media 118 using one or more of the
device/user identifier(s) 124 received from the mobile device 106.
In this manner, the media publisher 120 can associate the media ID
122 of the media 118 with the device/user identifier(s) 124 of the
mobile device 106 indicating that the media 118 was sent to the
particular mobile device 106 for presentation (e.g., to generate an
impression of the media 118).
[0044] In some other examples in which the data collector 112 is
configured to send the device/user identifier(s) 124 to the media
publisher 120, the data collector 112 does not collect the media ID
122 from the media 118 at the mobile device 106. Instead, the media
publisher 120 that publishes the media 118 to the mobile device 106
also retrieves the media ID 122 from the media 118 that it
publishes. The media publisher 120 then associates the media ID 122
with the device/user identifier(s) 124 of the mobile device 106.
The media publisher 120 then sends the impression data 130,
including the media ID 122 and the device/user identifier(s) 124,
to the AME 108. For example, when the media publisher 120 sends the
media 118 to the mobile device 106, it does so by identifying the
mobile device 106 as a destination device for the media 118 using
one or more of the device/user identifier(s) 124. In this manner,
the media publisher 120 can associate the media ID 122 of the media
118 with the device/user identifier(s) 124 of the mobile device 106
indicating that the media 118 was sent to the particular mobile
device 106 for presentation (e.g., to generate an impression of the
media 118). In the illustrated example, after the AME 108 receives
the impression data 130 from the media publisher 120, the AME 108
can then send the device/user identifier log 136 to the demographic
database proprietor 104 to request the user information 102 as
described above in connection with FIG. 1.
[0045] Although the media publisher 120 is shown separate from the
app publisher 110 in FIG. 1, the app publisher 110 may implement at
least some of the operations of the media publisher 120 to send the
media 118 to the mobile device 106 for presentation. For example,
advertisement providers, media providers, or other information
providers may send media (e.g., the media 118) to the app publisher
110 for publishing to the mobile device 106 via, for example, the
app program 116 when it is executing on the mobile device 106. In
some such examples, the app publisher 110 implements the operations
described above as being performed by the media publisher 120.
[0046] Additionally or alternatively, in contrast with the examples
described above in which the mobile device 106 sends device/user
identifiers 124 to the audience measurement entity 108 (e.g., via
the application publisher 110, the media publisher 120, and/or
another entity), in other examples the mobile device 106 (e.g., the
data collector 112 installed on the mobile device 106) sends the
identifiers (e.g., the user/device identifier(s) 124) directly to
the database proprietor 104 (e.g., not via the AME 108). In some
such examples, the example mobile device 106 sends the media
identifier 122 to the audience measurement entity 108 (e.g.,
directly or through an intermediary such as via the application
publisher 110), but does not send the media identifier 122 to the
database proprietors 104.
[0047] As mentioned above, the example demographic database
proprietor 104 provides the user information 102 to the example AME
108 for matching with the media identifier 122 to form media
impression information. As also mentioned above, the database
proprietor 104 is not provided copies of the media identifier 122.
Instead, the mobile device 106 provides the database proprietor 104
with impression identifiers 140. An impression identifier 140
uniquely identifies an impression event relative to other
impression events of the mobile device 106 (and relative to the
impression events of other devices) so that an occurrence of an
impression at the mobile device 106 can be distinguished from other
occurrences of impressions. However, the impression identifier 140
does not itself identify the media associated with that impression
event. In such examples, the impression data 130 from the mobile
device 106 to the AME 108 also includes the impression identifier
140 and the corresponding media identifier 122.
[0048] To match the user information 102 with the media identifier
122, the example demographic database proprietor 104 provides the
user information 102 to the AME 108 in association with the
impression identifier 140 for the impression event that triggered
the collection of the user information 102. In this manner, the AME
108 can match the impression identifier 140 received from the
mobile device 106 to a corresponding impression identifier 140
received from the demographic database proprietor 104 to associate
the media identifier 122 received from the mobile device 106 with
demographic information in the user information 102 received from
the database proprietor 104. The impression identifier 140 can
additionally be used for reducing or avoiding duplication of
demographic information. For example, the example demographic
database proprietor 104 may provide the user information 102 and
the impression identifier 140 to the AME 108 on a per-impression
basis (e.g., each time a mobile device 106 sends a request
including a device/user identifier 124 and an impression identifier
140 to the demographic database proprietor 104) and/or on an
aggregated basis (e.g., send a set of user information 102, which
may include indications of multiple impressions at a mobile device
102 (e.g., multiple impression identifiers 140), to the AME 108
presented at the mobile device 106).
[0049] The above examples illustrate methods and apparatus for
collecting impression data at an audience measurement entity (or
other entity). The examples discussed above may be used to collect
impression information for any type of media, including static
media (e.g., advertising images), streaming media (e.g., streaming
video and/or audio, including content, advertising, and/or other
types of media), and/or other types of media. For static media
(e.g., media that does not have a time component such as images,
text, a webpage, etc.), in some examples the AME 108 records an
impression once for each occurrence of the media being presented,
delivered, or otherwise provided to the mobile device 106. For
streaming media (e.g., video, audio, etc.), in some examples the
example AME 108 measures demographics for media occurring over a
period of time. For example, the AME 108 (e.g., via the app
publisher 110 and/or the media publisher 120) provides beacon
instructions to a client application or client software (e.g., the
OS 114, the web browser 117, the app 116, etc.) executing on the
mobile device 106 when media is loaded at client
application/software 114-117. In some such examples, the beacon
instructions cause the client application/software 114-117 to
transmit a request (e.g., a pingback message) to an impression
monitoring server at regular and/or irregular intervals (e.g.,
every minute, every 30 seconds, every 2 minutes, etc.). The example
impression monitoring server 132 identifies the requests from the
web browser 117 and, in combination with one or more database
proprietors, matches the impression information for the media with
demographics of the user of the web browser 117.
[0050] In some examples, a user loads (e.g., via the browser 117) a
web page from a web site publisher (e.g., a web page corresponding
to a particular 60 minute video). An instruction which is a part of
or referred to by the example web page (e.g., a beacon instruction)
causes the browser 117 and/or the data collector 112 to send a
pingback message (e.g., a beacon request) to a beacon server 142.
For example, when the beacon instructions are executed by the
example browser 117, the beacon instructions cause the data
collector 112 to send pingback messages (e.g., beacon requests,
HTTP requests, pings) to the impression monitoring server 132 at
designated intervals (e.g., once every minute or any other suitable
interval). The example beacon instructions (or a redirect message
from, for example, the impression monitoring server 132 or the
database proprietor 104) further cause the browser 117 and/or the
data collector 112 to send pingback messages or beacon requests to
the database proprietor 104 that collect and/or maintain
demographic information about users.
[0051] The database proprietor 104 transmits demographic
information about the user associated with the data collector 112
and/or the browser 117 for combining or associating with the
impression determined by the impression monitoring server 132. If
the user closes the web page containing the video before the end of
the video, the beacon instructions are stopped, and the data
collector 112 stops sending the pingback messages to the impression
monitoring server 132. In some examples, the pingback messages
include timestamps and/or other information indicative of the
locations in the video to which the numerous pingback messages
correspond. By determining a number and/or content of the pingback
messages received at the impression monitoring server 132 from the
mobile device 106, the example impression monitoring server 132 can
determine that the user watched a particular length of the video
(e.g., a portion of the video for which pingback messages were
received at the impression monitoring server 132).
[0052] The mobile device 106 of the illustrated example executes a
client application/software 114-117 that retrieves data from a host
website (e.g., www.acme.com) that provides (e.g., serves) the media
118 (e.g., audio, video, interactive media, streaming media, etc.)
is obtained for presenting via the mobile device 106. In the
illustrated example, the media 118 (e.g., advertisements and/or
content) is tagged with identifier information (e.g., a media ID
122, a creative type ID, a placement ID, a publisher source URL,
etc.) and a beacon instruction. The example beacon instruction
causes the client application/software 114-117 to request further
beacon instructions from a beacon server 142 that will instruct the
client application/software 114-117 on how and where to send beacon
requests to report impressions of the media 118. For example, the
example client application/software 114-117 transmits a request
including an identification of the media 118 (e.g., the media
identifier 122) to the beacon server 142. The beacon server 142
generates and/or returns beacon instructions 144 to the example
mobile device 106. Although the beacon server 142 and the
impression monitoring server 132 are shown separately, in some
examples the beacon server 142 and the impression monitoring server
132 are combined. In the illustrated example, beacon instructions
144 include a URL of the database proprietor (e.g., the demographic
database proprietors 104) or any other server to which the mobile
device 106 should send beacon requests (e.g., impression requests).
In some examples, a pingback message or beacon request may be
implemented as an HTTP request. However, whereas a transmitted HTTP
request identifies a webpage or other resource to be downloaded,
the pingback message or beacon request includes audience
measurement information (e.g., ad campaign identification, content
identifier, and/or device/user identification information) as its
payload. The server to which the pingback message or beacon request
is directed is programmed to log the audience measurement data of
the pingback message or beacon request as an impression (e.g., an
ad and/or content impression depending on the nature of the media
tagged with the beaconing instructions). In some examples, the
tagged media 118 include the beacon instructions 144. In such
examples, the client application/software 114-117 does not need to
request beacon instructions 144 from a beacon server 142 because
the beacon instructions 144 are already provided in the tagged
media 118.
[0053] When the beacon instructions 144 are executed by the mobile
device 106, the beacon instructions 144 cause the mobile device 106
to send beacon requests (e.g., repeatedly at designated intervals)
to a remote server (e.g., the impression monitoring server 132, the
media publisher 120, the database proprietor 104, or another
server) specified in the beacon instructions 144. In the
illustrated example, the specified server is a server of the
audience measurement entity 108, such as the impression monitoring
server 132. The beacon instructions 144 may be implemented using
Javascript or any other types of instructions or script executable
via a client application (e.g., a web browser) including, for
example, Java, HTML, etc.
[0054] While the example system 100 of FIG. 1 is illustrated as
having one database proprietor 104, multiple database proprietors
104 may be used.
[0055] Many applications and websites are available that enable
users of mobile devices to perform commercial transactions with a
merchant (e.g., a retailer, an online merchant, a club store, a
wholesaler, or any other purveyor of goods or services). For
example, Amazon.RTM. provides an application for devices to enable
a user of the device to login to an Amazon account, browse and/or
search for items, add the items to a shopping cart, enter payment
information, configure shipping details, and/or finalize an order.
Amazon provides such an application for multiple different types of
devices (e.g., devices executing different operating systems). Many
other such applications are available for other merchants.
Merchants who also have physical locations at which transactions
can be performed often provide applications for performing
commercial transactions from electronic devices similar to the
transaction described above.
[0056] The example system 100 of FIG. 1 includes a merchant
database proprietor 146. The example merchant database proprietor
146 of FIG. 1 stores account information for users who have
registered with the merchant database proprietor 146. In the
example of FIG. 1, users who register with the merchant database
proprietor 146 are then permitted to place orders for (e.g.,
purchase) products offered by the merchant database proprietor 146
and/or offered by third parties using ordering services provided by
the merchant database proprietor 146. For example, the merchant
database proprietor 146 may list products offered by a third party,
facilitate payment by the user for a purchased product, and/or
facilitate shipping of the purchased product to the user.
[0057] The example merchant database proprietor 146 of FIG. 1
provides an application (e.g., the app 116 of FIG. 1) for download
to the mobile device 106. For example, the mobile device 106 may
download the app 116 from the app publisher 110 and/or directly
from the merchant database proprietor 146.
[0058] When the app 116 is installed on the mobile device 106, the
example user may login to an account with the merchant database
proprietor 146 and/or may register to create an account with the
merchant database proprietor 146. In either case, the example app
116 transmits merchant account information 148 (e.g., a login name
or other account identifier, a password, etc.) to the merchant
database proprietor 146, which identifies the user or account to
the merchant database proprietor 146.
[0059] In addition to the merchant account information 148, the
example app 116 accesses the device/user identifier 124 in the
mobile device 106. The app 116 of the illustrated example transmits
the device/user identifier 124 to the merchant database proprietor
146.
[0060] Upon receipt of the merchant account information 148 and the
device/user identifier 124 and authentication of the corresponding
user account, the example merchant database proprietor 146
associates the user account with the device/user identifier 124. As
a result, the example merchant database proprietor 146 can generate
transaction information 150 for the user account, including
transactions performed using the user account with the device/user
identifier 124.
[0061] In some cases, a user account is accessed via multiple
devices (e.g., a smartphone and a tablet computer that are both
owned by the owner of the user account). The example merchant
database proprietor 146 may associate multiple device/user
identifiers 124 with the user account such that media impressions
occurring on any of the devices corresponding to the device/user
identifiers 124 may be correlated to transactions occurring using
the user account. The transactions may be independent of the device
on which they were performed by the user. That is, in the
illustrated example, transactions are associated with the user
account.
[0062] As mentioned above, the example AME 108 receives the
impression data 130 and the device/user identifier 124 from the
example mobile device 106. The example AME 108 of FIG. 1 associates
transaction information 150 with impression information by matching
impressions to transactions using the device/user identifier 124.
For example, the AME 108 of FIG. 1 receives, from the merchant
database proprietor 146, transaction information associated with a
user account associated with a device/user identifier 124 of the
mobile device 106. The example AME 108 also receives the impression
data 130 (or impression information) including an indication of the
same device/user identifier 124. The example AME 108 of FIG. 1
correlates the transaction information to the impressions by
matching the device/user identifier 124 in a transaction request
152 (described below) to the device/user identifier 124 that
corresponds to a user account used to perform the transactions.
[0063] To obtain the transaction information, the example AME 108
transmits a transaction request 152 to the example merchant
database proprietor 146. The example transaction request 152
includes a device/user identifier 124. The AME 108 transmits the
device/user identifier 124 that is received in the impression data
130 to, for example, obtain transaction information to potentially
be correlated to a media impression.
[0064] The example merchant database proprietor 146 receives the
transaction request 152 including the device/user identifier 124.
The merchant database proprietor 146 looks up a user account that
was previously associated with the device/user identifier 124
(e.g., in a database). If the merchant database proprietor 146
locates a user account associated with the device/user identifier
124, the example merchant database proprietor 146 generates the
transaction information 150 (e.g., based on transaction data stored
in a database of the merchant database proprietor 146).
[0065] In the illustrated example, the merchant database proprietor
146 transmits the transaction information 150 to the example AME
108. In some examples, the merchant database proprietor 146
includes the device/user identifier 124 in its response to the AME
108 to enable the AME 108 to determine the device/user identifier
124 and/or the request 152 for which the transaction information
150 is being provided. The example AME 108 of the illustrated
example matches the transaction information 150 received from the
merchant database proprietor 146 to the impression data 130.
[0066] To match the impressions in the impression data 130 to the
transactions in the transaction information 150, the example AME
108 of FIG. 1 determines the product(s) represented in the
impression data 130. Examples of product(s) represented in media
include products represented in advertisements for those products
(e.g., a Coca-Cola.RTM. soft drink represented in an advertisement
for Coca-Cola) and/or intentionally-placed product(s) in
non-advertisement media such as television episodes, movies, and/or
other content-oriented media (e.g., a Rolex.RTM. watch worn by an
actor in a television show, a particular car brand used in a movie,
etc.). For example, the AME 108 may access a database that
specifies the products represented in each item of media 118.
Similarly, the example transaction information 150 of FIG. 1
provided by the merchant database proprietor 146 includes an
identification of the product(s) purchased in the transactions made
by the user account associated with the device/user identifier
124.
[0067] The example AME 108 compares the product(s) represented in
the impression data 130 to the product(s) in the transaction
information 150 to determine whether there are any matching
product(s). If the AME 108 identifies a product represented in an
impression that matches a product involved in a purchase
transaction, the example AME 108 determines whether the purchase
transaction occurred after the impression. For example, the
impression data 130 includes time and date information indicating
the time and date of the impression on the mobile device 106.
Similarly, the transaction information 150 includes time and date
information indicating the time and date of the transaction(s)
represented in the transaction information 150. The AME 108
compares the time and date information for the media impression to
the time and date information for the transaction to determine
which of the media impression or the transaction occurred
first.
[0068] When the AME 108 determines that the media impression
occurred before the transaction (e.g., the time and date of the
media impression occurred before the time and date of the
transaction), the example AME 108 correlates the media impression
to the purchase of the product(s) represented in the impression.
The example AME 108 determines whether such a correlation occurred
for the product(s) for multiple mobile devices 106 and/or user
accounts. For example, the AME 108 determines a percentage of a set
of mobile devices 106 and/or user accounts for which the media
impression of a product occurred before the purchase transaction of
that product. In some examples, the AME 108 determines percentages
of sets of mobile device 106 for different publishers and/or
different media to evaluate the effectiveness of publishers and/or
media for influencing purchasing behavior of the product.
[0069] In some examples, the merchant database proprietor 146
provides transaction information 150 to the AME 108 for all
transactions performed using a user account associated with the
device/user identifier 124, for all transactions performed within a
specified time period using the user account associated with the
device/user identifier 124, and/or for specified type(s) of
transaction(s) performed using a user account associated with the
device/user identifier 124. In some other examples, the AME 108
determines the product(s) represented in the media impressions
occurring at the mobile device 106, and transmits product
information 154 to the merchant database proprietor 146 in the
transaction request 152. Limiting the transaction request 152 to
product(s) of interest may enhance the privacy of the users of the
merchant database proprietor 146 by restricting the AME 108 to
information about specific product(s).
[0070] In some examples, the AME 108 may transmit the product
information 154 in the request 152 without transmitting the
device/user identifier 124. In such examples, the merchant database
proprietor 146 looks up the product information 154 to determine
which user accounts have purchased the product identified in the
product information 154. The example merchant database proprietor
146 may then return a list of device/user identifiers 124 that
correspond to user accounts that have purchased the product
identified in the product information 154. In some examples, the
transactions returned in response to a transaction request 152 are
limited to transactions occurring within a particular time period,
such as a period of time designated in the request 152, a period of
time determined based on the request 152, a predetermined time
period, and/or a standard time period.
[0071] When the example merchant database proprietor 146 receives a
transaction request 152 including the product information 154, the
example merchant database proprietor 146 determines whether the
product(s) specified in the product information 154 have been
purchased in any transactions performed using the user account
associated with the device/user identifier 124 specified in the
transaction request 152. If the product(s) specified in the product
information 154 have been purchased, the example merchant database
proprietor 146 returns the transaction information 150 for the
transactions in which the specified product(s) were purchased. For
any product(s) not purchased using the user account, the example
merchant database proprietor 146 does not respond or responds with
an indication that those product(s) were not purchased using the
user account. By requiring the AME 108 to specify the product
information 154, the example AME 108 does not receive transaction
information that is not relevant to media impressions occurring on
the mobile device 106.
[0072] The example AME 108 of FIG. 1 aggregates transaction
information and media impressions to measure effectiveness of the
media corresponding to the media impressions. As explained in more
detail below, the example AME 108 measures the effectiveness of an
item of media by using the transaction information (collected as
described above) to measure a change in purchases of a product
represented in the item of media from a time period prior to the
media impressions to a time period subsequent to the media
impressions. In some examples, the AME 108 creates a measurement
group that is determined to have been exposed to the item of media
and compares the change to a purchase change in a control group.
The control group is determined by the AME 108 to not have been
exposed to the item of media, according to the impression
information.
[0073] Examples that may be used to implement the system of FIG. 1
are disclosed in U.S. patent application Ser. No. 14/127,414, filed
on Aug. 28, 2013, U.S. patent application Ser. No. 14/261,085,
filed on Apr. 24, 2014, U.S. Provisional Patent Application Ser.
No. 61/952,726, filed on Mar. 13, 2014, U.S. Provisional Patent
Application Ser. No. 61/979,391, filed on Apr. 14, 2014, U.S.
Provisional Patent Application Ser. No. 61/986,784, filed on Apr.
30, 2014, U.S. Provisional Patent Application Ser. No. 61/991,286,
filed on May 9, 2014, and U.S. Provisional Patent Application Ser.
No. 62/014,659, filed Jun. 19, 2014. The entireties of U.S. patent
application Ser. No. 14/127,414, U.S. patent application Ser. No.
14/261,085, U.S. Provisional Patent Application Ser. No.
61/952,726, U.S. Provisional Patent Application Ser. No.
61/979,391, U.S. Provisional Patent Application Ser. No.
61/986,784, U.S. Provisional Patent Application Ser. No.
61/991,286, and U.S. Provisional Patent Application Ser. No.
62/014,659 are incorporated by reference herein.
[0074] FIG. 2 illustrates an example impression-transaction
analyzer 200 which may be implemented in the example audience
measurement server 132 of FIG. 1 to match impression information
associated with a mobile device (e.g., the mobile device 106 of
FIG. 1) to transaction information corresponding to a purchase made
using a user account accessed by the mobile device 106. The example
impression-transaction analyzer 200 of FIG. 2 includes an example
product checker 202, an example product database 204, an example
transaction requester 206, an example impression/transaction
matcher 208, an example group identifier 210, an example
transaction aggregator 212, and an example effectiveness calculator
214.
[0075] The example product checker 202 of FIG. 2 identifies
products associated with media impressions. For example, the
product checker 202 of the illustrated example receives impression
data from mobile devices (e.g., the impression data 130 from the
mobile device 106 of FIG. 1). In this example, the impression data
130 includes a media identifier 122 for media 118 corresponding to
an impression occurring at the mobile device 106. The example
product checker 202 queries the product database 204, which stores
indications of products represented in the media 118 that
corresponds to the media identifier 122. The product checker 202 of
the illustrated example looks up a product corresponding to the
media 118 in the product database 204 using the media identifier
122 as a key. In response to the query, the example product
database 204 returns a product identifier of a product (e.g., the
product information 154 of FIG. 1) to the example product checker
202. Over time, the example product database 204 may be updated
with new associations of media to products. In the illustrated
example product database 204, a media item may be associated with
multiple products and/or a product may be represented by multiple
media items.
[0076] In addition to the media identifier 122, the example
impression data 130 also includes the device/user identifier 124.
In the illustrated example, the example product checker 202
provides the device/user identifier 124 and the product information
154 corresponding to the transaction request 152 to the transaction
requester 206.
[0077] The example transaction requester 206 of FIG. 2 generates
and sends a transaction request 152 to one or more merchant
database proprietors (e.g., the merchant database proprietor 146 of
FIG. 1). In the example of FIG. 2, the transaction request 152
includes the device/user identifier 124 and the product information
154. The example transaction requester 206 sends the transaction
request 152 to the merchant database proprietor 146 to obtain
transaction information from the merchant database proprietor
146.
[0078] If the merchant database proprietor 146 has transaction
information 150 corresponding to the device/user identifier 124,
the example merchant database proprietor 146 sends the transaction
information 150 to the impression-transaction analyzer 200. In some
examples, the merchant database proprietor 146 limits the
transaction information 150 that is returned to transactions that
correspond to both the device/user identifier 124 and the product
information 154. In other examples, the returned information is not
so limited and/or the product information 154 is not provided to
the merchant database proprietor 146.
[0079] The example transaction requester 206 of FIG. 2 receives the
transaction information 150 from the merchant database proprietor
146 (e.g., in response to the transaction request 152) and provides
the transaction information 150 and the impression data 130 to the
impression/transaction matcher 208. The example
impression/transaction matcher 208 of FIG. 2 matches impressions
occurring at the mobile device 106 (e.g., from the impression data
130) to transactions of purchases performed using a user account
associated with the mobile device 106 (e.g., from the transaction
information 150). By matching the impressions to the transactions,
the example impression/transaction matcher 208 may determine
instances in which an impression corresponding to a product
occurred prior to a transaction in which the product was purchased,
where both the impression and the transaction correspond to a same
device/user identifier 124. This information can be used to credit
the impression with driving the transaction.
[0080] To match an impression to a transaction, the example
impression/transaction matcher 208 compares A) combinations of a
device/user identifier 124 and product information 154 that are
obtained from the impression data 130 to B) combinations of a
device/user identifier 124 and product information 154 that
correspond to transaction information 150 obtained from the
merchant database proprietor 146. Combinations of the device/user
identifier 124 and the product information 154 that are found in
both the impression data 130 and in the transaction information 150
are considered to match.
As an example, Table 1 below includes a set of example combinations
of device/user identifiers 124 (e.g., Device/User ID) and product
information 154 (e.g., Product ID) obtained from impression data
130 (e.g., Impression ID) (e.g., by the example product checker
202) collected at a mobile device 106.
TABLE-US-00001 TABLE 1 EXAMPLE COMBINATIONS OF DEVICE/USER
IDENTIFIERS AND PRODUCT IDENTIFIERS FROM IMPRESSION DATA Impression
ID Device/User ID Product ID Imp. Time/Date 11 HOI35JGETR
R9ANT20EJY 2014-07-08:09:15:00 12 HOI35JGETR 7ZFF46F77Z
2014-07-08:13:05:00 13 B8PE8JH26N NB2EYZ4YOG
2014-07-08:16:10:00
[0081] Table 2 below includes a set of example combinations of
device/user identifiers 124 (e.g., Device/User ID) and product
information 154 (e.g., Product ID) corresponding to transaction
information 150 (e.g., Transaction ID) received by the transaction
requester 206 from a merchant database proprietor 146. The
combinations in Table 2 may be returned in the transaction
information 150 from a merchant database proprietor 146 and/or may
be associated with the transaction information 150 by the
transaction requester 206 when the transaction information 150 is
identified as occurring in response to a transaction request
152.
TABLE-US-00002 TABLE 2 EXAMPLE COMBINATIONS OF DEVICE/USER
IDENTIFIERS AND PRODUCT IDENTIFIERS FROM TRANSACTION DATA
Transaction ID Device/User ID Product ID Trans. Time/Date 21
HOI35JGETR R9ANT20EJY 2014-07-09:19:12:00 22 HOI35JGETR I9DBW9RC8R
2014-07-09:19:12:00 23 OBU2434KTL R9ANT20EJY 2014-07-08:11:49:00 24
B8PE8JH26N NB2EYZ4YOG 2014-07-07:04:42:00
[0082] By comparing the combinations in Table 1 above (e.g.,
records, impressions) to the combinations in Table 2 above (e.g.,
records, transactions), in this example the example
impression/transaction matcher 208 of FIG. 2 will identify the
impression data 130 having impression ID 11 as having the same
combination of device/user identifier 124 (e.g., Device/User ID of
HOI35JGETR) and product information 154 (e.g., Product ID of
R9ANT20EJY) as transaction information 150 having transaction ID
21. In this example, the impression/transaction matcher 208 of FIG.
2 also identifies the impression data 130 having impression ID 13
in Table 1 above as having the same combination of device/user
identifier 124 (e.g., Device/User ID of B8PE8JH26N) and product
information 154 (e.g., Product ID of NB2EYZ4YOG) as transaction
information 150 having transaction ID 24.
[0083] While Table 1 above shows that additional impressions data
130 associated with the device/user identifier 124 of HOI35JGETR
(Device/User ID) was received (e.g., data with an impression ID of
12), there are no corresponding transactions in Table 2 above for
that device/user identifier 124 that are also associated with the
product having a Product ID of 7ZFF46F77Z (i.e., the Product ID
associated with impression ID 12). Therefore, the
impression/transaction matcher 208 does not identify a match for
impression ID 12.
[0084] Similarly, Table 2 above shows that the device/user ID
HOI35JGETR was used to perform a transaction for the purchase of a
product having a Product ID of I9DBW9RC8R (see transaction ID 22 in
Table 2). However, Table 1 does not indicate that an impression of
media representing that product (i.e., I9DBW9RC8R) occurred on a
mobile device 106 that corresponds to the device/user ID
HOI35JGETR. Therefore, the impression/transaction matcher 208 of
this example does not identify a match for transaction ID 22.
[0085] The example Table 1 above also includes information
indicating the times and dates at which the impressions occurred
(Imp. Time/Date). The example Table 2 above also includes
information indicating the times and dates at which the
transactions occurred. When the example impression/transaction
matcher 208 of FIG. 2 identifies a transaction (e.g., from Table 2
above) that has a device/user identifier 124 and product
information 154 combination that matches the device/user identifier
124 and product information 154 combination of an impression (e.g.,
from Table 1 above), the impression/transaction matcher 208 of the
illustrated example determines whether the impression occurred
prior to the transaction based on the respective times and dates of
the matching impression ID and transaction ID. In the example of
FIG. 2, the impression/transaction matcher 208 determines that the
matching impression and transaction are related (e.g., that the
impression may have resulted in the transaction) when the
impression occurred prior to the transaction (according to the
respective times and dates).
[0086] In the example of Tables 1 and 2 above, the
impression/transaction matcher 208 would determine that the
impression having impression ID 11 is related to the matching
transaction having transaction ID 21 because the impression has a
time and date (Jul. 8, 2014, at 09:15:00) that occurred before the
time and date of the transaction (Jul. 9, 2014, at 19:12:00). For
example, where the media associated with the impression having
impression ID 11 is an advertisement for a product, and the
transaction corresponding to transaction ID 21 is a subsequent
purchase of that product using a user account associated with the
device on which the impression occurred, it is possible or even
likely that the impression had an influence on the purchase of the
product. Therefore, in view of the time sequence of this example
(i.e., the impression occurring before the transaction), the
impression is credited with driving the transaction.
[0087] Conversely, in the example of Tables 1 and 2 above, the
impression/transaction matcher 208 would determine that the
impression having impression ID 13 is not related to the matching
transaction having transaction ID 24 because the impression has a
time and date (Jul. 8, 2014, at 16:10:00) that occurred after the
time and date of the transaction (Jul. 7, 2014, at 04:42:00). For
example, where a person purchases a product and then is
subsequently exposed to an advertisement for the product, that
particular exposure of the person to the advertisement would not be
considered to have influenced the prior purchase of that product
and, thus, is not credited with driving a transaction.
[0088] The example group identifier 210 of FIG. 2 assigns
device/user identifiers 124 to groups based on whether the
device/user identifier 124 is associated with an impression of
media of interest (e.g., media corresponding to a product of
interest). For example, the group identifier 210 of FIG. 2 assigns
device/user identifiers 124 that correspond to impressions of the
media to an "exposed" group, and assigns device/user identifiers
124 that do not correspond to the media of interest to a "control"
group. In some examples, the group identifier 210 further
sub-divides the control group and/or the exposed group based on
other factors such as time periods during which the impressions of
the media of interest occurred for the exposed group.
[0089] The example impression/transaction matcher 208 of FIG. 2
provides the group identifier 210 of FIG. 2 with the impression
information (e.g., the impression information of Table 1). The
example group identifier 210 determines, for each device/user
identifier 124 represented in the impressions, whether the
device/user identifier 124 has been exposed to media representing a
product of interest. For example, the group identifier 210 is
provided with product information 154 for a product of interest,
such as a product for which a media campaign is to be evaluated for
effectiveness.
[0090] In some examples, the group identifier 210 is provided with
a media identifier 122 instead of product information 154. A media
identifier 122 may be used when, for example, a measurement of the
effectiveness of a particular item of media is desired when there
are multiple items of media representing a product. In such
examples, the group identifier 210 may obtain impression data 130
from the product checker 202. Using the impression data 130, the
group identifier 210 determines the device/user identifiers 124
corresponding to impressions of the media 118 having the media
identifier 122.
[0091] The example group identifier 210 of FIG. 2 sorts the
device/user identifiers 124 (e.g., device/user IDs of Tables 1
and/or 2 above) into two groups. The first group is an "exposed
group," which includes the device/identifiers 124 corresponding to
impressions of media representing the product of interest. For
example, the group identifier 210 may populate a table or other
data structure corresponding to the exposed group with device/user
identifiers 124 that are present in combination with the product ID
of interest in an impressions table (e.g., Table 1 above). The
second group is a "control group," which includes the
device/identifiers 124 for which impressions of media representing
the product of interest did not occur. Using the example Table 1
above, if the group identifier 210 receives the Product ID
R9ANT20EJY as the product of interest, the example group identifier
210 would place the device/user identifier 124 (device/user ID) of
HOI35JGETR in the exposed group because the device/user identifier
124 of HOI35JGETR reported an impression of media corresponding to
Product ID R9ANT20EJY. In this example, the group identifier 210
would place the device/user identifier 124 (device/user ID) of
B8PE8JH26N in a table or other data structure corresponding to the
control group because the device/user identifier 124 of B8PE8JH26N
did not report an impression of media corresponding to Product ID
R9ANT20EJY. Therefore, in this example, the exposed group would
have a count of one device/user identifier 124 and the control
group would have a count of one device/user identifier 124.
[0092] The example impression/transaction matcher 208 of FIG. 2
provides the transactions (e.g., the transactions of Table 2 above)
to the transaction aggregator 212. Additionally, the example group
identifier 210 provides the list of device/user identifiers 124
that belong to each of the groups (e.g., the control group and the
exposed group) to the transaction aggregator 212. For example, the
group identifier 210 may provide a first list of device/user
identifiers 124 that have been determined to be in the control
group and a second list of device/user identifiers 124 that have
been determined to be in the exposed group. These lists correspond
to the data structure for the exposed group and the control group
mentioned above.
[0093] The example transaction aggregator 212 of FIG. 2 determines
up to four separate sets of purchases or transactions based on the
transactions obtained from the impression/transaction matcher 208
and based on the groups identified by the group identifier 210. In
the illustrated example, the transaction aggregator 212 determines
1) the number of the products purchased by user accounts
corresponding to device/user identifiers 124 in the control group
during a first time period; 2) the number of the products purchased
by user accounts corresponding to device/user identifiers 124 in
the control group during a second time period occurring after the
first time period; 3) the number of the products purchased by user
accounts corresponding to device/user identifiers 124 in the
exposed group during the first time period; and 4) the number of
the products purchased by user accounts corresponding to
device/user identifiers 124 in the exposed group during the second
time period.
[0094] In the illustrated example, the first time period is a time
period prior to (e.g., ending at) the commencement of a media
campaign including media (e.g., the media of interest) representing
the products of interest. Thus, the purchases of the products by
the control group and the exposed group may provide a basis for
calculating purchase growth attributable to the media. In
particular, differences in purchases or purchase rate by the
exposed group as compared to the purchases or purchase rate of the
control group provides a measure of the effectiveness of the media
in driving and/or slowing sales.
[0095] In the illustrated example, the second time period is a time
period subsequent to (e.g., starting at the end of or consecutive
to) the first period. For example, the second time period may begin
at the end of the first time period, the end of a time period
during which a media campaign runs, and/or at any other event.
[0096] To determine the number of the products purchased via user
accounts corresponding to device/user identifiers 124 in the
control group during a first time period (e.g., the first example
set of purchases determined by the transaction aggregator 212), the
example transaction aggregator 212 identifies transactions (e.g.,
transactions from Table 2 above) that have a time and date within
the first period and have a device/user identifier 124 assigned to
the control group by the group identifier 210. The control group
will not have a matching impression (e.g., in Table 1). In other
words, to determine the number of the products purchased via user
accounts corresponding to device/user identifiers 124 in the
control group during the first time period, the example transaction
aggregator 212 determines a number of transactions performed using
devices corresponding to the control group prior to, for example,
the beginning of a media campaign (e.g., a coordinated set of
impressions of one or more media items, including audio, video,
and/or still media) for the product of interest.
[0097] To determine the number of the products purchased via user
accounts corresponding to device/user identifiers 124 in the
control group during a second time period (e.g., the second example
set of purchases determined by the transaction aggregator 212), the
example transaction aggregator 212 identifies transactions (e.g.,
transactions from Table 2 above) that: 1) have a time and date
within the second period and have a device/user identifier 124
assigned to the control group by the group identifier 210. The
control group will not have a matching impression (e.g., in Table
1). In other words, to determine the number of the products
purchased via user accounts corresponding to device/user
identifiers 124 assigned to the control group during the second
time period, the example transaction aggregator 212 determines a
number of transactions performed using devices corresponding to the
control group after the beginning of the media campaign (e.g.,
during and/or after the media campaign) for the product of
interest.
[0098] To determine the number of the products purchased via user
accounts corresponding to device/user identifiers 124 in the
exposed group during the first time period (e.g., the third example
set of purchases determined by the transaction aggregator 212), the
example transaction aggregator 212 identifies transactions (e.g.,
transactions from Table 2 above) that have a time and date within
the first period and have a device/user identifier 124 assigned to
the exposed group by the group identifier 210. In other words, to
determine the number of the products purchased via user accounts
corresponding to device/user identifiers 124 assigned to the
exposed group during the first time period, the example transaction
aggregator 212 determines a number of transactions performed using
devices corresponding to the exposed group prior to the beginning
of the media campaign for the product of interest.
[0099] To determine the number of the products purchased via user
accounts corresponding to device/user identifiers 124 in the
exposed group during the second time period (e.g., the fourth
example set of purchases determined by the transaction aggregator
212), the example transaction aggregator 212 identifies
transactions (e.g., transactions from Table 2 above) that: 1) have
a time and date within the second period and have a device/user
identifier 124 assigned to the exposed group, and 2) have a related
matching impression (e.g., an impression in Table 1 above that has
a same device/user ID and a same Product ID as the transaction, and
where the impression has a time and date that is prior to the time
and date of the transaction). In other words, to determine the
number of the products purchased via user accounts corresponding to
device/user identifiers 124 in the exposed group during the second
time period, the example transaction aggregator 212 determines a
number of transactions performed using devices corresponding to the
exposed group after the beginning of the media campaign for the
product of interest.
[0100] The example effectiveness calculator 214 of FIG. 2
calculates the effectiveness of the media and/or the effectiveness
of the publishers (e.g., the delivery methods for the media). For
example, the effectiveness calculator 214 calculates the
effectiveness of the media and/or the publishers based on the sales
of the product represented in the media that occurred in the
aggregated transactions. The example effectiveness calculator 214
calculates the sales using the sets of purchases determined by the
transaction aggregator 212 for the control and exposed groups
during the first and second time periods.
[0101] In some examples, the effectiveness calculator 214
calculates a publisher effectiveness (e.g., for an app publisher
110, for a media publisher 120, etc.) by, for example, dividing the
sales lift in an exposed group for a first publisher by the sales
lift in an exposed group for a second publisher. The exposed group
for the first publisher is the fourth example group calculated by
the transaction aggregator 212 as described above (e.g., the number
of the products purchased via user accounts corresponding to
device/user identifiers 124 in the exposed group during the second
time period) determined using device/user identifiers 124
associated with impressions delivered via the first publisher
(e.g., delivered via an app and/or a website associated with the
app publisher 110, delivered in association with media published by
the media publisher 120, etc.). Similarly, the exposed group for
the second publisher is the fourth example group calculated by the
transaction aggregator 212 as described above (e.g., the number of
the products purchased via user accounts corresponding to
device/user identifiers 124 in the exposed group during the second
time period) determined using device/user identifiers 124
associated with impressions delivered via the second publisher
(e.g., delivered via an app and/or a website associated with the
app publisher 110, delivered in association with media published by
the media publisher 120, etc.).
[0102] Additionally or alternatively, the example effectiveness
calculator 214 calculates the effectiveness of media by, for
example, dividing a sales lift from the first time period to the
second time period for an exposed group by the sales lift from the
first time period to the second time period for a control group.
The media effectiveness measures, for example, the effect of the
media of interest on driving sales by determining the difference in
sales rates after the media of interest was presented relative to
sales rates before the media was presented. For example, the
effectiveness calculator 214 may determine the media effectiveness
metric using the four example sets of purchases determined by the
transaction aggregator 212 as described above to be: ((sales in
fourth example set of purchases/sales in third example set of
purchases)/(sales in second example set of purchases/sales in first
example set of purchases)) or ((sales in fourth example set of
purchases/sales in third example set of purchases)-(sales in second
example set of purchases/sales in first example set of
purchases)/(sales in second example set of purchases/sales in first
example set of purchases)).
[0103] FIG. 3 illustrates an example table 300 illustrating an
example determination of an effectiveness of media impressions.
FIG. 4 is a graph 400 illustrating the data in the example table
300 of FIG. 3. The example table 300 and/or the example graph 400
may be generated by the example impression-transaction analyzer 200
of FIG. 2 based on impression data 130 obtained from the mobile
device 106, user information 102 obtained from the example
demographic database proprietor 104, and/or transaction information
150 obtained from the merchant database proprietor 146 of FIG.
1.
[0104] In the examples of FIGS. 3 and 4, the impression-transaction
analyzer 200 does not calculate the transactions occurring prior to
the media impressions (as in the examples described above with
reference to FIG. 2). Instead, in this example the media
effectiveness is determined by comparing sales of the product to
the control group with sales of the product to the exposed group to
determine a sales lift. Omitting the measurement of different time
periods increases the privacy of users of the merchant database
proprietor 146 and decreases computational resource requirements,
but may also fail to control the measurement for external events,
such as media impressions occurring via other media presentation
platforms such as television, radio, and/or outdoor
advertising.
[0105] The example table 300 of FIG. 3 illustrates a comparison of
transactions for a product corresponding to impressions delivered
through two different mobile application publishers (e.g., via two
different applications that may be installed on a mobile device).
For this example, assume Publisher A 302 publishes a first
application (e.g., the app 116 of FIG. 1) and Publisher B 304
publishes a second application (e.g., the browser 117 of FIG. 1).
The example media publisher 120 of FIG. 1 may choose to have the
media 118 of FIG. 1 delivered to the mobile device 106 via either
or both of the app 116 and/or the browser 117 of FIG. 1.
[0106] For each of the publishers 302, 304 of the example table 300
of FIG. 3, the example group identifier 210 of FIG. 2 determines a
number of user accounts (or persons associated with the user
accounts) belonging to the control group 306 as described above
(e.g., during a time period following the commencement of media
impressions at mobile devices 106 via the publishers 302, 304). The
group identifier 210 also determines a number of user accounts
belonging to the exposed group 308 as described above.
[0107] In the example of FIGS. 3 and 4, the group identifier 210
identifies (e.g., based on the impression data 130 from those
mobile devices 106) 12,200 user accounts in the control group for
publisher A 302 (e.g., associated with mobile devices 106 using the
app 116 from the publisher A 302 that have not had an impression of
the media). Similarly, the group identifier 210 identifies (e.g.,
based on the impression data 130 from those mobile devices 106)
17,500 user accounts in the control group for publisher B 304
(e.g., associated with mobile devices 106 using the browser 117
from the publisher B 304 that have not had an impression of the
media).
[0108] Continuing the example, the group identifier 210 identifies
(e.g., based on the impression data 130 from those mobile devices
106) 35,400 user accounts in the exposed group for publisher A 302
(e.g., associated with mobile devices 106 using the app 116 from
the publisher A 302 that have had an impression of the media).
Similarly, the group identifier 210 identifies (e.g., based on the
impression data 130 from those mobile devices 106) 30,100 user
accounts in the exposed group for publisher B 304 (e.g., associated
with mobile devices 106 using the browser 117 from the publisher B
304 that have had an impression of the media).
[0109] The example transaction aggregator 212 of FIG. 2 determines
a number of control group sales 310 (e.g., transactions involving
the product, of a quantity of units of the product, etc.) and a
number of exposed group sales 312 of the respective control groups
of the example publishers 302, 304. The example control group sales
310 may be the first or the second example groups of purchases
determined by the transaction aggregator 212 as described above.
The example exposed group sales 312 may be the third or the fourth
example groups of purchases determined by the transaction
aggregator 212 as described above. The transaction aggregator 212
determines a number of transactions for the product corresponding
to the members of each of the groups 306, 308 identified by the
group identifier 210. In the example of FIGS. 3 and 4, Publisher A
302 is determined to have 4,200 control group sales 310 and 22,100
exposed group sales 312 of the example product. Therefore, 34.4%
(e.g., 4,200/12,200) of the example control group 306 of the
publisher A 302 purchased the example product of interest during
the measured time period, while 62.4% (e.g., 22,100/35,400) of the
exposed group 308 of the publisher A 302 purchased the example
product during the measured time period. Therefore, the media
impressions delivered via the app 116 (e.g., via Publisher A)
resulted in a sales lift 314 of 81.3% (e.g., (62.4%-34.4%)/34.4%)
for the product in the exposed group 308 relative to the control
group 306.
[0110] Publisher B 304 is determined to have 5,600 control group
sales 310 and 10,600 exposed group sales 312 of the example
product. Therefore, 32% (e.g., 5,600/17,500) of the example control
group 306 of the publisher B 304 purchased the example product of
interest during the measured time period, while 35.2% (e.g.,
10,600/30,100)) of the exposed group 308 of the publisher B 304
purchased the example product during the measured time period.
Therefore, the media impressions delivered via the browser 117
(e.g., via Publisher B) resulted in a sales lift 314 of 10.0%
(e.g., (35.2%-32%)/32%) for the product in the exposed group 308
relative to the control group 306.
[0111] By comparing the example sales lifts 314 for the publishers
302, 304 of FIGS. 3 and 4, a manufacturer of a product associated
with the media of interest (or, for example, the manufacturer's
advertising agent) may determine that impressions of the media
corresponding to the product are more effective when occurring
through the app 116 (e.g., via Publisher A 302) than through the
browser 117 (e.g., via Publisher B 304) (or, in some other
examples, more effective through a first app than through a second
app). The example manufacturer (and/or its advertising agent) may
respond to this determination by channeling more of the media
impressions to mobile devices 106 via the app 116 (provided by
Publisher A 302) and fewer via the browser 117 (provided by
Publisher B 304). Additionally or alternatively, the manufacturer
(and/or its advertising agent) replace the browser 117 with another
app (e.g., via Publisher C) for delivery of media impressions to
mobile devices. For example, the replacement app (e.g., Publisher
C) may be selected to be one that has substantially similar or
identical lift performance as the app provided by Publisher A 302
of FIG. 3.
[0112] FIG. 5 is a block diagram of an example transaction
information provider 500 that may be used to implement the example
merchant database proprietor 146 of FIG. 1. The example transaction
information provider 500 includes an example user authenticator
502, an example account-identifier correlator 504, an example
transaction engine 506, an example transaction query generator 508,
and an example transaction reporter 510. The example transaction
information provider 500 further includes databases including an
example user account database 512, an example product database 514,
and an example transaction database 516.
[0113] The example user authenticator 502 of FIG. 5 receives user
login requests (e.g., from the mobile device 106, the app 116 of
FIG. 1). In the example of FIG. 5, the user login requests include
the example merchant account information 148 of FIG. 1. The
merchant account information 148 may include a unique account
identifier (e.g., a user name, an account number, etc.) and one or
more authenticators (e.g., passwords, pass codes, authentication
keys, etc.). In the illustrated example, the example user
authenticator 502 verifies the merchant account information 148
(e.g., the account identifier and/or the authenticator(s)) in the
user account database 512, which stores the merchant account
information 148 for authentication purposes.
[0114] As mentioned above with reference to FIG. 1, the example
user login request that is authenticated by the user authenticator
502 also includes a device/user identifier 124 corresponding to the
mobile device 106 (e.g., the device/user identifier 124 of FIG. 1).
In the example of FIG. 5, the device/user identifier 124 is an
identifier (e.g., an IMEI number, an IDFA number, etc.) that is not
set by either of the merchant database proprietor 146 of FIG. 1 or
the transaction information provider 500 of FIG. 5. Because the
device/user identifier 124 is not set by the transaction
information provider 500, the transaction information provider 500
is required to obtain the device/user identifier 124 from the
mobile device 106.
[0115] The example account-identifier correlator 504 of FIG. 5
matches the merchant account information 148 to the device/user
identifier 124 included in the request. For example, the
account-identifier correlator 504 stores the device/user identifier
124 in the user account database 512 in association with the
merchant account information 148 so that the device/user identifier
124 is associated with the user account at the merchant. Because a
user may log in to the merchant database proprietor 146 from
multiple devices, the example account-identifier correlator 504 may
correlate multiple device/user identifiers 504 to the same merchant
account information 148 (e.g., to a same user account).
[0116] The example transaction engine 506 enables users to conduct
transactions, such as purchasing products from the merchant
database proprietor 146 (e.g., an organization such as a commercial
merchant). When a user (e.g., a user having a user account with the
merchant database proprietor 146) purchases a product via the
transaction engine 506, the example transaction engine 506 accesses
the product database 514 to determine product identifier(s) of the
product(s) and/or service(s) purchased in the transaction. The
example transaction engine 506 stores transaction information
(e.g., the transaction information 150 of FIG. 1) in the
transaction database 516. The stored transaction information may
include, for example, the product identifiers involved in the
transaction, the time and/or date of the transaction, and the user
account associated with the transaction. As discussed below, the
device/user identifiers 124 from the mobile device 106 may then be
matched to the transactions in the transaction database 516 based
on the mapping of user accounts to the device/user identifier 124
in the user account database 512.
[0117] The example product database 514 may store the same
information as the product database 204 of FIG. 2. In some
examples, the product database 204 of FIG. 2 includes a subset of
the product identifiers included in the product database 514 of
FIG. 5 (e.g., when the product database 204 of FIG. 2 includes
product identifiers only for products of interest to the audience
measurement entity 108). In some other examples, the product
database 514 of FIG. 5 includes a subset of the product identifiers
included in the product database 204 of FIG. 2 (e.g., when there
are multiple merchant database proprietors 146 having different
products for purchase).
[0118] The example transaction query generator 508 of FIG. 5
receives requests for transaction information (e.g., from the
audience measurement entity 108 of FIG. 1). For example, the
transaction query generator 508 may receive a request 152 for
transactions that have been performed using an account
corresponding to the device/user identifier 124 and that include
product information 154.
[0119] Upon receipt of such a request 152, the example transaction
query generator 508 queries the user account database 512 to
determine a user account (e.g., an account identifier, a user name,
etc.) that corresponds to the device/user identifier 124 in the
request 152. The example user account database 512 determines the
user account that matches the device/user identifier 124 (e.g., the
account previously correlated to the device/user identifier 124 by
the account-identifier correlator 504). The user account database
512 returns the account identifier to the example transaction query
generator 508.
[0120] Using the account identifier, the example transaction query
generator 508 queries the product database 514 using the product
information 154 in the request 152 to determine a product
identifier used by the transaction information provider 500 to
identify the product (e.g., an internal reference number for the
product that is used within the transaction information provider
500, a universal product code (UPC), an international article
number (EAN), a global trade item number (GTIN), a bar code, etc.).
For example, a UPC code uniquely identifies a trade item and/or a
variant or specific configuration of a trade item, and may be used
by the transaction information provider 500. The example
transaction query generator 508 then queries the transaction
database 516 using the account identifier (e.g., obtained by
querying the user account database 512) and the product identifier
(e.g., obtained by querying the product database 514) to identify
transactions involving the product that were conducted using the
specified account.
[0121] The transaction database 516 returns information describing
the identified transactions, including the account identifier, the
device identifiers, and the date and time of the transaction. The
example transaction query generator 508 provides the transaction
information returned from the transaction database to the
transaction reporter 510. The example transaction reporter 510 of
FIG. 5 returns transaction information 150 to the AME 108 of FIG. 1
(e.g., in response to a corresponding transaction request 152). In
the example of FIG. 5, the transaction reporter 510 converts the
information received from the transaction database 516 to
information usable by the AME 108. For example, the transaction
reporter 510 may convert an account identifier associated with a
transaction in the transaction database 516 to a device/user
identifier 124 recognizable by the AME 108 (e.g., to the
device/user identifier 124 included in the transaction request 152
and obtained from the transaction query generator 508).
Additionally or alternatively, the transaction reporter 510 may
convert a product identifier (e.g., a UPC code, a service code,
etc.) used by the transaction information provider 500 to
corresponding product information 154 (e.g., the product
information included in the transaction request 152 and obtained
from the transaction query generator 508).
[0122] The example transaction reporter 510 of FIG. 5 sends the
transaction information 150 to the example AME 108. The AME 108
receives the transaction information 150 and determines the
effectiveness of media impressions as described above.
[0123] While example manners of implementing the example
impression-transaction analyzer 200 and the transaction information
provider have been illustrated in FIGS. 2 and 5, one or more of the
elements, processes and/or devices illustrated in FIGS. 2 and 5 may
be combined, divided, re-arranged, omitted, eliminated and/or
implemented in any other way. Further, the example product checker
202, the example product database 204, the example transaction
requester 206, the example impression/transaction matcher 208, the
example group identifier 210, the example transaction aggregator
212, the example effectiveness calculator 214, the example user
authenticator 502, the example account-identifier correlator 504,
the example transaction engine 506, the example transaction query
generator 508, the example transaction reporter 510, the example
user account database 512, the example product database 514, the
example transaction database 516 and/or, more generally, the
example impression-transaction analyzer 200 of FIG. 2, and/or the
example transaction information provider 500 of FIG. 5 may be
implemented using hardware, software, firmware and/or any
combination of hardware, software and/or firmware. Thus, for
example, any of the example product checker 202, the example
product database 204, the example transaction requester 206, the
example impression/transaction matcher 208, the example group
identifier 210, the example transaction aggregator 212, the example
effectiveness calculator 214, the example user authenticator 502,
the example account-identifier correlator 504, the example
transaction engine 506, the example transaction query generator
508, the example transaction reporter 510, the example user account
database 512, the example product database 514, the example
transaction database and/or, more generally, the example
impression-transaction analyzer 200, and/or the example transaction
information provider 500 could be implemented using one or more
analog or digital circuit(s), logical circuit(s), programmable
processor(s), application specific integrated circuit(s) (ASIC(s)),
programmable logic device(s) (PLD(s)) and/or field programmable
logic device(s) (FPLD(s)), etc. When reading any of the apparatus
or system claims of this patent to cover a purely software and/or
firmware implementation, at least one of the example product
checker 202, the example product database 204, the example
transaction requester 206, the example impression/transaction
matcher 208, the example group identifier 210, the example
transaction aggregator 212, the example effectiveness calculator
214, the example user authenticator 502, the example
account-identifier correlator 504, the example transaction engine
506, the example transaction query generator 508, the example
transaction reporter 510, the example user account database 512,
the example product database 514, and/or the example transaction
database 516 is/are hereby expressly defined to include a tangible
computer readable storage device or storage disk such as a memory,
a digital versatile disk (DVD), a compact disk (CD), a Blu-ray
disk, etc. storing the software and/or firmware. Further still, the
example the example impression-transaction analyzer 200 of FIG. 2
and/or the example transaction information provider 500 of FIG. 5
may include one or more elements, processes and/or devices in
addition to, or instead of, those illustrated in FIGS. 2 and/or 5,
and/or may include more than one of any or all of the illustrated
elements, processes and devices.
[0124] Flowcharts representative of example machine readable
instructions for implementing the example audience measurement
entity 108, the audience measurement server 132, and/or the example
merchant database proprietor 146 of FIG. 1, the example
impression-transaction analyzer 200 of FIG. 2, and/or the example
transaction information provider 500 of FIG. 5 are shown in FIGS.
6-11. In these examples, the machine readable instructions comprise
one or more programs for execution by a processor such as the
processor 1212 shown in the example processor platform 1200
discussed below in connection with FIG. 12. The program(s) may be
embodied in software stored on a tangible computer readable storage
medium such as a CD-ROM, a floppy disk, a hard drive, a digital
versatile disk (DVD), a Blu-ray disk, or a memory associated with
the processor 1212, but the entire program(s) and/or parts thereof
could alternatively be executed by a device other than the
processor 1212 and/or embodied in firmware or dedicated hardware.
Further, although the example one or more programs are described
with reference to the flowcharts illustrated in FIGS. 6-11, many
other methods of implementing the example impression data
compensator 200 may alternatively be used. For example, the order
of execution of the blocks may be changed, and/or some of the
blocks described may be changed, eliminated, or combined.
[0125] As mentioned above, the example processes of FIGS. 6-11 may
be implemented using coded instructions (e.g., computer and/or
machine readable instructions) stored on a tangible computer
readable storage medium such as a hard disk drive, a flash memory,
a read-only memory (ROM), a compact disk (CD), a digital versatile
disk (DVD), a cache, a random-access memory (RAM) and/or any other
storage device or storage disk in which information is stored for
any duration (e.g., for extended time periods, permanently, for
brief instances, for temporarily buffering, and/or for caching of
the information). As used herein, the term tangible computer
readable storage medium is expressly defined to include any type of
computer readable storage device and/or storage disk and to exclude
propagating signals and transmission media. As used herein,
"tangible computer readable storage medium" and "tangible machine
readable storage medium" are used interchangeably. Additionally or
alternatively, the example processes of FIGS. 6-11 may be
implemented using coded instructions (e.g., computer and/or machine
readable instructions) stored on a non-transitory computer and/or
machine readable medium such as a hard disk drive, a flash memory,
a read-only memory, a compact disk, a digital versatile disk, a
cache, a random-access memory and/or any other storage device or
storage disk in which information is stored for any duration (e.g.,
for extended time periods, permanently, for brief instances, for
temporarily buffering, and/or for caching of the information). As
used herein, the term non-transitory computer readable medium is
expressly defined to include any type of computer readable storage
device and/or storage disk and to exclude propagating signals and
transmission media. As used herein, when the phrase "at least" is
used as the transition term in a preamble of a claim, it is
open-ended in the same manner as the term "comprising" is open
ended.
[0126] FIG. 6 is a flow diagram representative of example machine
readable instructions 600 which may be executed to implement the
example audience measurement server 132 of FIG. 1 and/or the
example impression-transaction analyzer 200 of FIG. 2 to associate
media impressions to transaction information. The example
instructions 600 of FIG. 6 will be described with reference to the
example impression-transaction analyzer 200 of FIG. 2.
[0127] The example product checker 202 of FIG. 2 receives media
impression information from mobile devices (e.g., the mobile device
106 of FIG. 1) (block 602). In the illustrated example, the
received media impression information includes a device/user
identifier such as the device/user identifier 124 of FIG. 1.
Example types of the device/user identifier 124 received in the
media impression information include hardware identifiers (e.g., an
international mobile equipment identity (IMEI), a mobile equipment
identifier (MEID), a media access control (MAC) address, etc.), an
app store identifier (e.g., a Google Android ID, an Apple ID, an
Amazon ID, etc.), an open source unique device identifier
(OpenUDID), an open device identification number (ODIN), a login
identifier (e.g., a username), an email address, user agent data
(e.g., application type, operating system, software vendor,
software revision, etc.), third-party service identifiers (e.g., an
"Identifier for Advertising" (IDFA), advertising service
identifiers, device usage analytics service identifiers,
demographics collection service identifiers), web storage data,
document object model (DOM) storage data, local shared objects
(also referred to as "Flash cookies"), etc.
[0128] The example product checker 202 determines product
information associated with the media impression information (block
604). For example, the product checker 202 may access (e.g., query)
the product database 204 of FIG. 2 to determine an identifier of a
product that is represented in a media impression at the mobile
device 106 and which resulted in receiving the media impression
information in block 602.
[0129] The example transaction requester 206 requests transaction
information from a merchant database proprietor (e.g., the merchant
database proprietor 146 of FIG. 1) based on the device/user
identifier 124 (e.g., determined in block 602) and/or based on the
product information (e.g., determined in block 604) (block 606).
For example, the transaction requester 206 may generate a
transaction request 152 of FIG. 1 including the device/user
identifier 124 and/or the product information 154, and send the
transaction request 152 to the merchant database proprietor
146.
[0130] The example transaction requester 206 receives transaction
information 150 from the merchant database proprietor 146 (block
608). The transaction information 150 may include, for example, a
unique transaction identifier, a device/user identifier 124, a
product identifier, and/or a time/date at which the transaction
occurred. Example transaction information 150 is shown in Table 2
above. If a transaction performed at the merchant database
proprietor 146 involved multiple products, the example transaction
requester 206 may receive multiple records, each representing one
product involved in the transaction.
[0131] The example impression/transaction matcher 208 associates
transactions involving a product with media impressions
corresponding to the product (block 610). For example, the
impression/transaction matcher 208 may match impression information
(e.g., impression records such as those illustrated in Table 1
above) to transaction information (e.g., transaction records such
as those illustrated in Table 2 above) by determining that a media
impression corresponds to a same device/user identifier 124 as a
transaction and that the media impression represents a product
involved in the transaction. In some examples, the
impression/transaction matcher 208 matches media impressions to
transactions. For example, the impression/transaction matcher 208
may determine that an impression occurred prior to a transaction
based on respective times/dates of the impression and the
transaction. Example instructions that may be used to implement
block 610 are described below with reference to FIG. 7.
[0132] When the appropriate media impressions and transactions have
been associated (block 610), the example effectiveness calculator
214 of FIG. 2 determines a media effectiveness and/or a publisher
effectiveness (block 612). For example, the effectiveness
calculator 214 may determine whether media impressions delivered
via a first publisher (e.g., the app publisher 110, the media
publisher 120) result in a higher sales lift (e.g., a larger sales
increase). Additionally or alternatively, the example effectiveness
calculator 214 may determine a media effectiveness of the media
corresponding to the impressions by calculating a sales lift from a
first time period prior to beginning a media campaign to a second
time period subsequent to beginning the media campaign to determine
an effect of the media on sales of the represented product. The
example instructions 600 of FIG. 6 end.
[0133] FIG. 7 is a flow diagram representative of example machine
readable instructions 700 which may be executed to implement the
example audience measurement server 132 of FIG. 1 and/or the
example impression-transaction analyzer 200 of FIG. 2 to correlate
transactions involving a product to media impressions corresponding
to the product. In some examples, the example instructions 700 of
FIG. 7 may be performed to implement block 610 of FIG. 6. The
example instructions 700 of FIG. 7 will be described with reference
to the example impression-transaction analyzer 200 of FIG. 2.
[0134] The example instructions 700 begin after block 608 of FIG. 6
(e.g., receiving transaction information). The example
impression/transaction matcher 208 of FIG. 2 selects a media
impression from the media impression information (block 702). For
example, the impression/transaction matcher 208 may select a media
impression record from the records of Table 1 above. In this
example, the impression/transaction matcher 208 selects the first
example record of Table 1 above (e.g., Impression ID 11).
[0135] The example impression/transaction matcher 208 determines a
product represented by the media corresponding to the selected
media impression (block 704). For example, the
impression/transaction matcher 208 may determine the Product ID,
from Table 1 above, that corresponds to the selected impression ID.
In this example, the determined Product ID is R9ANT20EJY.
[0136] The example impression/transaction matcher 208 of FIG. 2
also determines a device/user identifier 124 corresponding to the
selected media impression (block 706). For example, the
impression/transaction matcher 208 may determine the Device/User
ID, from Table 1 above, that corresponds to the selected impression
ID. In this example, the determined Device/User ID is
HOI35JGETR.
[0137] The example impression/transaction matcher 208 selects a
transaction from the transaction information (block 708). For
example, the impression/transaction matcher 208 may select a
transaction record from the records of Table 2 above. In this
example, the impression/transaction matcher 208 selects the first
example record of Table 2 above (e.g., Transaction ID 21).
[0138] The example impression/transaction matcher 208 determines a
product purchased in the transaction corresponding to the selected
transaction (block 710). For example, the impression/transaction
matcher 208 may determine the Product ID, from Table 2 above, that
corresponds to the selected Transaction ID. In this example, the
determined Product ID is R9ANT20EJY.
[0139] The example impression/transaction matcher 208 of FIG. 2
also determines a device/user identifier 124 corresponding to an
account used to perform the selected transaction (block 712). For
example, the impression/transaction matcher 208 may determine the
Device/User ID, from Table 1 above, that corresponds to the
selected Transaction ID. In this example, the determined
Device/User ID is HOI35JGETR.
[0140] The example impression/transaction matcher 208 determines
whether the selected media impression matches the selected
transaction based on the respective products and the respective
device/user identifiers (block 714). For example, the
impression/transaction matcher 208 compares the Device/User ID of
the selected impression (e.g., Device/User ID HOI35JGETR) to the
Device/User ID of the selected transaction (e.g., Device/User ID
HOI35JGETR) and compares the Product ID of the selected impression
(e.g., Product ID R9ANT20EJY) to the Product ID of the selected
transaction (e.g., Product ID R9ANT20EJY).
[0141] If the selected media impression matches the selected
transaction (block 714), the example impression/transaction matcher
208 of FIG. 2 determines whether a time/date of the selected media
impression occurred prior to the time/date of the selected
transaction (block 716). For example, the impression/transaction
matcher 208 compares the time/date of the selected impression
(e.g., 2014-07-08:09:15:00) to the time/date of the selected
transaction (block 2014-07-09:19:12:00). If the time/date of the
selected media impression occurred prior to the time/date of the
selected transaction (block 716), the example
impression/transaction matcher 208 associates the selected
transaction to the selected media impression (block 718). By
associating the selected transaction to the selected media
impression (block 718), the example impression/transaction matcher
208 may infer that the media impression may have contributed or did
actually contribute to the occurrence of the transaction (e.g.,
media corresponding to the media impression influenced a user to
make the transaction).
[0142] If the time/date of the selected media impression does not
occur prior to the time/date of the selected transaction (block
716), or if the selected media impression does not match the
selected transaction (block 714), the example
impression/transaction matcher 208 determines whether there are
additional transactions to compare to the selected media impression
(block 720). If there are additional transactions to compare to the
selected media impression (block 720), control returns to block 708
to select another transaction (e.g., to select another transaction
record from Table 2).
[0143] If there are no more transactions to compare to the selected
media impression (block 720), or after associating the selected
transaction to the selected media impression (block 718), the
example impression/transaction matcher 208 determines whether there
are additional media impressions (block 722). If there are
additional media impressions (block 722), control returns to block
702 to select another media impression. When there are no more
media impressions (block 722), the example instructions 700 of FIG.
7 end and control returns to a calling function or process such as
the example instructions of FIG. 6.
[0144] FIGS. 8A and 8B show a flow diagram representative of
example machine readable instructions 800 which may be executed to
implement the example audience measurement server 132 of FIG. 1
and/or the example impression-transaction analyzer 200 of FIG. 2 to
determine media and publisher effectiveness. In some examples, the
example instructions 800 of FIGS. 8A and 8B may be performed to
implement block 612 of FIG. 6. The example instructions 800 of
FIGS. 8A and 8B will be described with reference to the example
impression-transaction analyzer 200 of FIG. 2.
[0145] The example group identifier 210 of FIG. 2 selects a
publisher (block 802). For example, the group identifier 210 may
select an app publisher (e.g., a publisher of the app 116 of FIG.
1, a publisher of the browser 117 of FIG. 1, etc.) and/or a media
publisher (e.g., a publisher of media 118 presented on the mobile
device 106 of FIG. 1 via the app 116 and/or via the browser
117).
[0146] The example group identifier 210 assigns device/user
identifiers 124 that correspond to media impressions for media of
interest and that are presented by the selected publisher to an
"exposed group" that corresponds to the selected publisher (block
804). The exposed group for the selected publisher therefore
includes device/user identifiers 124 of those mobile devices 106
from which impression data 130, specifying the media of interest
and the selected publisher, has been received. For example, if the
selected publisher is a publisher of the app 116, the exposed group
for the selected publisher includes the device/user identifiers 124
for mobile devices 106 on which media impressions have occurred
using the app 116 (e.g., according to the impression data 130
reporting the media impressions to the AME 108).
[0147] The example transaction aggregator 212 determines a number
of transactions that correspond to the device/user identifiers 124
in the exposed group for the selected publisher (block 806). For
example, the transaction aggregator 212 may determine a number of
transactions that match the device/user identifiers 124. The
identification of matching transactions may be performed prior to
executing the instructions 800 (e.g., by the impression/transaction
matcher 208), such as by executing block 610 of FIG. 6 and/or by
executing the instructions 700 of FIG. 7.
[0148] The example transaction aggregator 212 calculates a
proportion of the exposed group for the selected publisher that
purchased the product represented in the media of interest (block
808). For example, the transaction aggregator 212 determines the
number of the device/user identifiers 124 that were associated with
a media impression that matched a transaction, as a percentage of
the total number of device/user identifiers 124 in the exposed
group. The example transaction aggregator 212 may calculate the
proportion the first and/or second time periods, individually
and/or together as a single time period.
[0149] The example transaction aggregator 212 of FIG. 2 assigns
transactions associated with the exposed group for the selected
publisher to first and second time periods, based on the
times/dates of the transactions (block 810). The example first and
second time periods may be used to divide transactions into 1)
transactions occurring prior to media impressions corresponding to
the media of interest (e.g., prior to a media campaign in which the
media is to be delivered to mobile devices to cause media
impressions) and, therefore, not having any effect on sales of the
product represented in the media and 2) transactions occurring
after media impressions corresponding to the media of interest have
begun (e.g., subsequent to the initiation of the media campaign,
such as during and/or after the media campaign) and, therefore,
potentially having an effect on sales of the product.
[0150] The example group identifier 210 determines a set of
device/user identifiers 124 that are not associated with media
impressions for the media of interest (block 812). For example, the
group identifier 210 may use device/user identifiers 124 associated
with media impressions for media other than the media of interest,
where the impression-transaction analyzer 200 has not received
impression data 130 indicating an impression of the media of
interest occurring in association with the device/user identifier
124. In some examples, the group identifier 210 may use device/user
identifiers 124 and/or impression data 130 from other media
campaigns (e.g., media campaigns not associated with the media of
interest, in which other media is presented at the mobile devices)
and verify that the device/user identifiers 124 have not had a
media impression of the media of interest.
[0151] The example group identifier 210 assigns the set of
device/user identifiers 124 to a "control group" corresponding to
the selected publisher (block 814). The control group represents
device/user identifiers 124 and/or mobile devices 106 that have not
been exposed to the media of interest.
[0152] The example transaction requester 206 requests transaction
information for the device/user identifiers in the control group
from the merchant database proprietor 146 (block 816). For example,
the transaction requester 206 may send one or more transaction
requests 152 including the device/user identifiers 124 in the
control group and product information 154 for a product represented
in the media of interest (e.g., the same product used in block
808).
[0153] The example transaction aggregator 212 of FIG. 2 assigns
transactions associated with the control group for the selected
publisher to first and second time periods, based on the
times/dates of the transactions (block 818). The example first and
second time periods may be used to divide transactions into the
first and second time periods described above with reference to
block 810 (e.g., to facilitate comparison of control group and the
exposed group during the same time periods).
[0154] Based on transaction information 150 received from the
merchant database proprietor 146 (e.g., in response to the request
of block 814), the example transaction aggregator 212 of FIG. 2
calculates a proportion of the control group for the selected
publisher that purchased the product represented in the media of
interest (block 820). For example, the transaction aggregator 212
determines a number of the device/user identifiers 124 in the
control group for which transactions including the product were
received from the merchant database proprietor 146 in response to
the request of block 816. The example transaction aggregator 212
may calculate the proportion for the first and/or second time
periods, individually and/or together as a single time period.
[0155] The example group identifier 210 determines whether there
are any additional publishers (block 822). If there are additional
publishers (block 822), control returns to block 802 to select
another publisher.
[0156] When there are no more publishers, control is passed to
block 824 of FIG. 8B, where the example effectiveness calculator
214 of FIG. 2 compares proportions of sales for each of the
publishers to determine a publisher effectiveness by sales
differences. Using the table 300 and the example publishers 302,
304 described above with reference to FIG. 3, the example
effectiveness calculator 214 may compare the exposed group sales
312 of Publisher A 302 (e.g., 22,100 sales from 35,400 device/user
identifiers, or 62.4% of the exposed group) to exposed group sales
312 of Publisher B 304 (e.g., 10,600 sales from 30,100 device/user
identifiers, or 35.2% of the exposed group).
[0157] The example effectiveness calculator 214 of FIG. 2
determines a sales lift, for each of the example publishers,
between the control group and the exposed group and between the
first time period and the second time period (block 826). For
example, using the example of FIG. 3 described above, the sales
lift 314 for Publisher A 302 is the increase in the sales
proportion between the control group (e.g., 34.4%) and the exposed
group (e.g., 62.4%), or 81.3% (e.g., the percentage of sales in the
exposed group for publisher A 302 divided by the percentage of
sales in the control group for publisher A 302 (62.4%/34.4%)).
Similarly, the sales lift 314 for Publisher B 304 is the increase
in the sales proportion between the control group (e.g., 32%) and
the exposed group (e.g., 35.2%), or 10% (e.g., the percentage of
sales in the exposed group for publisher B 304 divided by the
percentage of sales in the control group for publisher B 304
(35.2%/32%)).
[0158] The example effectiveness calculator 214 compares the sales
lift for each of the example publishers 302, 304 to determine a
publisher effectiveness by the sales lift difference (block 828).
For example, the effectiveness calculator 214 compares the sales
lift 314 of the Publisher A 302 (e.g., 81.3%) to the sales lift 314
of the Publisher B 304 (e.g., 10%). In this example, the
effectiveness calculator 214 may determine that Publisher A 302 is
more effective than Publisher B 304 for the media of interest.
Publisher A 302 may be more effective than Publisher B 304 because,
for example, Publisher A 302 may reach an audience that is more
likely to be influenced by the media of interest.
[0159] The example effectiveness calculator 214 determines a media
effectiveness for the media of interest based on a difference in
the changes in sales between the first time period and the second
time period for each of the control group and the exposed group
(block 830). For example, the effectiveness calculator 214 may
compare A) the change in sales for the control group between the
first time period (e.g., 10% of the device/user identifiers in the
control group purchased the product of interest during the first
time period) and the second time period (e.g., 12% of the
device/user identifiers in the control group purchased the product
of interest during the second time period) to B) the change in
sales for the exposed group between the first time period (e.g.,
16% of the device/user identifiers in the exposed group purchased
the product of interest during the first time period) and the
second time period (e.g., 46% of the device/user identifiers in the
exposed group purchased the product of interest during the second
time period). By comparing the changes in sales across the time
periods between the groups, the example effectiveness calculator
214 controls for extraneous influences (e.g., non-mobile device
media impressions for the same product) to more accurately capture
the effect of the media of interest.
[0160] The example instructions 800 of FIGS. 8A and 8B then end
and, for example, control returns to a calling function or process
such as the example instructions of FIG. 6.
[0161] FIG. 9 is a flow diagram representative of example machine
readable instructions 900 which may be executed to implement the
example merchant database proprietor 146 of FIG. 1 and/or the
example transaction information provider 500 of FIG. 5 to associate
device/user identifiers to merchant database proprietor accounts.
The example instructions 900 are described with reference to the
example transaction information provider 500 of FIG. 5.
[0162] The example user authenticator 502 of FIG. 5 receives a
request from a mobile device (e.g., merchant account information
148 from the mobile device 106 of FIG. 1, the app 116 of FIG. 1) to
access an account at the merchant database proprietor for
performing a transaction (block 902). For example, the transaction
information provider 500 may enable authenticated users to view
and/or purchase products from the transaction information provider
500 and/or through the systems of the transaction information
provider 500.
[0163] The example user authenticator 502 determines whether the
request is authenticated (block 904). For example, the user
authenticator 502 may use any past, present, or future
authentication techniques to authenticate the merchant account
information 148 included in the request.
[0164] If the request is authenticated (block 904), the example
account-identifier correlator 504 of FIG. 5 extracts a device/user
identifier (e.g., the device/user identifier 124 of FIG. 1) from
the request (block 906). Example types of a device/user identifier
124 that may be extracted include hardware identifiers (e.g., an
international mobile equipment identity (IMEI), a mobile equipment
identifier (MEID), a media access control (MAC) address, etc.), an
app store identifier (e.g., a Google Android ID, an Apple ID, an
Amazon ID, etc.), an open source unique device identifier
(OpenUDID), an open device identification number (ODIN), a login
identifier (e.g., a username), an email address, user agent data
(e.g., application type, operating system, software vendor,
software revision, etc.), third-party service identifiers (e.g., an
"Identifier for Advertising" (IDFA), advertising service
identifiers, device usage analytics service identifiers,
demographics collection service identifiers), web storage data,
document object model (DOM) storage data, local shared objects
(also referred to as "Flash cookies"), etc. In some examples, the
transaction information provider 500 agrees with the AME 108 ahead
of time on a same type of device/user identifier 124 that is
accessible to both entities.
[0165] The example account-identifier correlator 504 determines
whether the extracted device/user identifier 124 is stored in
association with any accounts in the user account database 512 of
FIG. 5 (block 908). For example, the user account database 512
stores associations of device/user identifiers 124 and user
accounts.
[0166] When the extracted device/user identifier 124 is not yet
stored in association with any accounts in the user account
database 512 of FIG. 5 (block 908), the example account-identifier
correlator 504 stores the extracted device/user identifier 124 in
association with the authenticated account (block 910). For
example, the account-identifier correlator 504 stores the extracted
device/user identifier 124 in the user account database 512 and
indicates that the extracted device/user identifier 124 corresponds
to the user account.
[0167] After storing the device/user identifier 124 (block 910), if
the extracted device/user identifier 124 is associated with an
accounts in the user account database 512 of FIG. 5 (block 908), or
if the request to access the account is not authenticated (block
904), the example instructions 900 of FIG. 9 end.
[0168] FIG. 10 is a flow diagram representative of example machine
readable instructions 1000 which may be executed to implement the
example merchant database proprietor 146 of FIG. 1 and/or the
example transaction information provider 500 of FIG. 5 to provide
transaction information. The example instructions 1000 are
described with reference to the example transaction information
provider 500 of FIG. 5.
[0169] The example transaction query generator 508 of FIG. 5
receives a transaction request including a device/user identifier
124 (block 1002). For example, the transaction query generator 508
may receive a transaction request 152 from the AME 108 of FIG.
1.
[0170] The example transaction query generator 508 retrieves
account information corresponding to the device/user identifier 124
in the request 152 (block 1004). For example, the transaction query
generator 508 may query the user account database 512 of FIG. 5
using the device/user identifier 124, and the user account database
512 determines whether the device/user identifier 124 corresponds
to a user account stored in the user account database 512.
[0171] The example transaction query generator 508 determines
whether the device/user identifier 124 is associated with an
account identifier (block 1006). For example, the device/user
identifier 124 may have been previously stored in association with
an account identifier in the user account database 512 using the
example instructions 900 of FIG. 9.
[0172] When the device/user identifier 124 is associated with an
account identifier (block 1006), the example transaction query
generator 508 of FIG. 5 retrieves transactions performed using the
account corresponding to the account identifier (e.g., the account
identifier determined in block 1006) (block 1008). For example, the
transaction query generator 508 may query the transaction database
516 of FIG. 5 using the account identifier to determine the
transactions performed using the account identifier. The
transaction database 516 provides transaction information for each
retrieved transaction, such as a device/user identifier, a
transaction identifier, products purchased in the transaction, and
a time/date the transaction occurred.
[0173] The example transaction query generator 508 determines
whether the transaction request 152 includes a time/date range
(block 1010). For example, the transaction request 152 may specify
a time/date range of interest (e.g., a time/date prior to which
transactions are not desired). The time/date range may be closed or
open-ended. If the transaction request includes a time/date range
(block 1010), the example transaction query generator 508 filters
the retrieved transactions (e.g., the transactions from block 1008)
to remove transactions falling outside the time/date range
specified in the transaction request 152.
[0174] After filtering the retrieved transactions (block 1012), or
if the transaction request 152 does not include a time/date range
(block 1010), the example transaction query generator 508
determines whether the transaction request 152 includes product
information (e.g., the product information 154 of FIG. 1) (block
1014). Example product information 154 specifies a product of
interest to the AME 108 (e.g., a product that is represented in
media corresponding to a media impression at a mobile device
106).
[0175] If the transaction request includes product information 154
(block 1014), the example transaction query generator 508 retrieves
a product identifier based on the product information 154 (block
1016). For example, the transaction query generator 508 may query
the product database 514 of FIG. 5 to determine a product
identifier that corresponds to the product information 154
specified by the AME 108 in the request 152. The example
transaction query generator 508 filters the retrieved transactions
to remove transactions that do not include the product identifier
(block 1018).
[0176] After filtering the retrieved transactions (block 1018), or
if the transaction request 152 does not include product information
154 (block 1014), the example transaction reporter 510 returns the
transaction information 150 (e.g., the transaction information
remaining after filtering in block 1012 and/or block 1018) to the
AME 108 in response to the transaction request 152 (block 1020).
For example, the transaction reporter 510 may send one or more
transaction records (e.g., the example records illustrated in Table
2 above), including a Transaction ID, a Product ID, a Device/User
ID, and/or a Time/Date, to the example AME 108 as a response to the
transaction request 152.
[0177] After returning the transaction information (block 1020), or
if the device/user identifier 124 is not associated with an account
identifier (block 1006), the example instructions 1000 of FIG. 10
end.
[0178] FIG. 11 is a flow diagram representative of example machine
readable instructions 1100 which may be executed to implement the
example merchant database proprietor 146 of FIG. 1 and/or the
example transaction information provider 500 of FIG. 5 to provide
transaction information. In contrast to the example instructions
1000 of FIG. 10 described above, the instructions 1100 of FIG. 11
may be executed when, for example, a transaction request 152 from
the AME 108 of FIG. 1 does not include a device/user identifier
124. The example instructions 1100 are described with reference to
the example transaction information provider 500 of FIG. 5.
[0179] The example transaction query generator 508 of FIG. 5
receives a transaction request (e.g., a transaction request 152
from the AME 108) that includes product information (e.g., the
product information 154 of FIG. 1) (block 1102).
[0180] The example transaction query generator 508 retrieves a
product identifier based on the product information 154 (block
1104). For example, the transaction query generator 508 may query
the product database 514 of FIG. 5 to determine a product
identifier that corresponds to the product information 154
specified by the AME 108 in the request 152.
[0181] The example transaction query generator 508 of FIG. 5
retrieves transaction records that include the product identifier
(e.g., the product retrieved in block 1104) (block 1106). For
example, the transaction query generator 508 may query the
transaction database 516 of FIG. 5 using the product identifier to
determine all of the performed transactions involving the product
corresponding to the product identifier. In response to the query,
the transaction database 516 provides transaction information for
each identified transaction, such as a device/user identifier, a
transaction identifier, products purchased in the transaction, and
a time/date the transaction occurred.
[0182] The example transaction query generator 508 selects a
transaction from the retrieved transactions (block 1108). The
example transaction query generator 508 looks up an account used to
perform the selected transaction in an account database to identify
a device/user identifier 124 corresponding to the account (block
1110). For example, the transaction query generator 508 may look up
an account specified in the selected transaction record, which is
used to query the user account database 512 to determine whether
any device/user identifiers correspond to the account.
[0183] The transaction query generator 508 determines whether the
account used to perform the selected transaction is associated with
a device/user identifier 124 (block 1112). If the account used to
perform the selected transaction is associated with a device/user
identifier 124 (block 1112), the example transaction query
generator 508 determines whether the transaction request 152
includes a time/date range (block 1114). For example, the
transaction request 152 may specify a time/date range of interest
(e.g., a time/date prior to which transactions are not desired).
The time/date range may be closed or open-ended.
[0184] If the transaction request 152 includes a time/date range
(block 1114), the example transaction query generator 508
determines whether the time/date of the selected transaction falls
within the time/date range (block 1116). If the time/date of the
selected transaction does not fall within the time/date range
(block 1116), or if the account used to perform the selected
transaction is not associated with a device/user identifier 124
(block 1112), the example transaction query generator 508 removes
the selected transaction from the retrieved transactions (e.g., the
transactions from block 1106).
[0185] After removing the selected transaction (block 1118), or if
1) the account used to perform the selected transaction is
associated with a device/user identifier 124 (block 1112) and 2)
either A) the time/date of the selected transaction falls within
the time/date range (block 1116) or B) the transaction request 152
does not include a time/date range (block 1114), the example
transaction query generator 508 determines whether there are
additional retrieved transactions (block 1120). If there are
additional retrieved transactions (block 1120), control returns to
block 1108 to select another transaction.
[0186] When there are no more retrieved transactions (block 1120),
the example transaction reporter 510 returns the transaction
information 150 (e.g., the transaction information remaining after
filtering in blocks 1110-1118) to the example AME 108 in response
to the transaction request 152 (block 1122). For example, the
transaction reporter 510 may return one or more transaction records
(e.g., the example records illustrated in Table 2 above), including
a Transaction ID, a Product ID, a Device/User ID, and/or a
Time/Date, to the AME 108. The example instructions 1100 of FIG. 11
then end.
[0187] FIG. 12 is a block diagram of an example processor platform
1200 capable of executing the instructions of FIGS. 6, 7, 8, 9, 10,
and/or 11 to implement the example product checker 202, the example
product database 204, the example transaction requester 206, the
example impression/transaction matcher 208, the example group
identifier 210, the example transaction aggregator 212, the example
effectiveness calculator 214, the example user authenticator 502,
the example account-identifier correlator 504, the example
transaction engine 506, the example transaction query generator
508, the example transaction reporter 510, the example user account
database 512, the example product database 514, the example
transaction database 516 and/or, more generally, the example
audience measurement entity 108, the example audience measurement
server 132, and/or the example merchant database proprietor 146 of
FIG. 1, the example impression-transaction analyzer 200 of FIG. 2,
and/or the example transaction information provider 500 of FIG. 5.
The processor platform 1200 can be, for example, a server, a
personal computer, a mobile device (e.g., a cell phone, a smart
phone, a tablet such as an iPad.TM. tablet), an Internet appliance,
or any other type of computing device.
[0188] The processor platform 1200 of the illustrated example
includes a processor 1212. The processor 1212 of the illustrated
example is hardware. For example, the processor 1212 can be
implemented by one or more integrated circuits, logic circuits,
microprocessors or controllers from any desired family or
manufacturer.
[0189] The processor 1212 of the illustrated example includes a
local memory 1213 (e.g., a cache). The processor 1212 of the
illustrated example is in communication with a main memory
including a volatile memory 1214 and a non-volatile memory 1216 via
a bus 1218. The volatile memory 1214 may be implemented by
Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random
Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)
and/or any other type of random access memory device. The
non-volatile memory 1216 may be implemented by flash memory and/or
any other desired type of memory device. Access to the main memory
1214, 1216 is controlled by a memory controller.
[0190] The processor platform 1200 of the illustrated example also
includes an interface circuit 1220. The interface circuit 1220 may
be implemented by any type of interface standard, such as an
Ethernet interface, a universal serial bus (USB), and/or a PCI
express interface.
[0191] In the illustrated example, one or more input devices 1222
are connected to the interface circuit 1220. The input device(s)
1222 permit(s) a user to enter data and commands into the processor
1212. The input device(s) can be implemented by, for example, an
audio sensor, a microphone, a camera (still or video), a keyboard,
a button, a mouse, a touchscreen, a track-pad, a trackball,
isopoint and/or a voice recognition system.
[0192] One or more output devices 1224 are also connected to the
interface circuit 1220 of the illustrated example. The output
devices 1224 can be implemented, for example, by display devices
(e.g., a light emitting diode (LED), an organic light emitting
diode (OLED), a liquid crystal display, a cathode ray tube display
(CRT), a touchscreen, a tactile output device, a light emitting
diode (LED), a printer and/or speakers). The interface circuit 1220
of the illustrated example, thus, typically includes a graphics
driver card, a graphics driver chip or a graphics driver
processor.
[0193] The interface circuit 1220 of the illustrated example also
includes a communication device such as a transmitter, a receiver,
a transceiver, a modem and/or network interface card to facilitate
exchange of data with external machines (e.g., computing devices of
any kind) via a network 1226 (e.g., an Ethernet connection, a
digital subscriber line (DSL), a telephone line, coaxial cable, a
cellular telephone system, etc.).
[0194] The processor platform 1200 of the illustrated example also
includes one or more mass storage devices 1228 for storing software
and/or data. Examples of such mass storage devices 1228 include
floppy disk drives, hard drive disks, compact disk drives, Blu-ray
disk drives, RAID systems, and digital versatile disk (DVD)
drives.
[0195] Coded instructions 1232 to implement the example machine
readable instructions of FIGS. 6, 7, 8, 9, 10, and/or 11 may be
stored in the mass storage device 1228, in the volatile memory
1214, in the non-volatile memory 1216, and/or on a removable
tangible computer readable storage medium such as a CD or DVD.
[0196] Although certain example methods, apparatus and articles of
manufacture have been disclosed herein, the scope of coverage of
this patent is not limited thereto. On the contrary, this patent
covers all methods, apparatus and articles of manufacture fairly
falling within the scope of the claims of this patent.
* * * * *
References