US20160063539A1 - Methods and apparatus to associate transactions with media impressions - Google Patents

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.

Description

FIELD OF THE DISCLOSURE
• The present disclosure relates generally to monitoring media and, more particularly, to methods and apparatus to associate transactions with media impressions.
BACKGROUND
• 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.
• 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
• 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.
• FIG. 2 is an example impression-transaction analyzer which may be implemented in the example audience measurement server ofFIG. 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.
• FIG. 3 illustrates an example table illustrating an example determination of publisher effectiveness.
• FIG. 4 is a graph illustrating the data in the example table ofFIG. 3.
• FIG. 5 is a block diagram of an example transaction information provider that may be used to implement the example merchant database proprietor ofFIG. 1.
• FIG. 6 is a flow diagram representative of example machine readable instructions which may be executed to implement the example impression-transaction analyzer ofFIG. 2 to associate media impressions to transaction information.
• FIG. 7 is a flow diagram representative of example machine readable instructions which may be executed to implement the example impression-transaction analyzer ofFIG. 2 to correlate transactions involving a product to media impressions corresponding to the product.
• 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 ofFIG. 2 to determine media and publisher effectiveness.
• FIG. 9 is a flow diagram representative of example machine readable instructions which may be executed to implement the example transaction information provider ofFIG. 5 to associate device/user identifiers to merchant database proprietor accounts.
• FIG. 10 is a flow diagram representative of example machine readable instructions which may be executed to implement the example transaction information provider ofFIG. 5 to provide transaction information.
• FIG. 11 is a flow diagram representative of example machine readable instructions which may be executed to implement the example transaction information provider ofFIG. 5 to provide transaction information.
• FIG. 12 is an example processor platform that may be used to execute the example instructions ofFIGS. 6-11 to implement example apparatus and systems disclosed herein.
DETAILED DESCRIPTION
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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.
• 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).
• 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.
• 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®, eBay®, 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).
• 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.
• 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.
• 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).
• 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.
• 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.).
• 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.
• FIG. 1 depicts anexample system100 to collect user information (e.g., user information102) from adatabase proprietor104 for associating with impressions of media presented at amobile device106. In the illustrated examples,user information102 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.
• In the illustrated example ofFIG. 1, to track media impressions on themobile device106, an audience measurement entity (AME)108 partners with or cooperates with anapp publisher110 to download and install adata collector112 on themobile device106. In the example ofFIG. 1, theAME108 provides thedata collector112 to theapp publisher110 for inclusion of thedata collector112 in apps downloaded by mobile devices from theapp publisher110. Theapp publisher110 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. Thedata collector112 may be included in other software loaded onto themobile device106, such as theoperating system114, an application (or app)116, aweb browser117, and/or any other software.
• Any of the example software114-117 may presentmedia118 received from amedia publisher120. Themedia118 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, amedia ID122 is provided in themedia118 to enable identifying themedia118 so that theAME108 can credit themedia118 with media impressions when themedia118 is presented on themobile device106 or any other device that is monitored by theAME108.
• Thedata collector112 of the illustrated example includes instructions (e.g., Java, java script, or any other computer language or script) that, when executed by themobile device106, cause themobile device106 to collect themedia ID122 of themedia118 presented by theapp program116 and/or themobile device106, and to collect one or more device/user identifier(s)124 stored in themobile device106. The device/user identifier(s)124 of the illustrated example include identifiers that can be used by thedemographic database proprietor104 to identify the user or users of themobile device106, and to locateuser information102 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 onedemographic database proprietor104 is shown inFIG. 1, theAME108 may partner with any number of demographic database proprietors to collect distributed user information (e.g., the user information102).
• In some examples, themobile device106 may not allow access to identification information stored in themobile device106. For such instances, the disclosed examples enable theAME108 to store an AME-provided identifier (e.g., an identifier managed and tracked by the AME108) in themobile device106 to track media impressions on themobile device106. For example, theAME108 may provide instructions in thedata collector112 to set an AME-provided identifier in memory space accessible by and/or allocated to theapp program116. In some such examples, thedata collector112 uses the identifier as a device/user identifier124. In such examples, the AME-provided identifier set by thedata collector112 persists in the memory space even when theapp program116 and thedata collector112 are not running. In this manner, the same AME-provided identifier can remain associated with themobile device106 for extended durations and/or be used across multiple apps. In some examples in which thedata collector112 sets an identifier in themobile device106, theAME108 may recruit a user of themobile device106 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 themobile device106 and/or any other device used by the user and monitored by theAME108. In this manner, theAME108 can associate user information of the user (from panelist data stored by the AME108) with media impressions attributed to the user on themobile device106.
• In the illustrated example, thedata collector112 sends themedia ID122 and the one or more device/user identifier(s)124 as collecteddata126 to theapp publisher110. Alternatively, thedata collector112 may be configured to send the collecteddata126 to another collection entity (other than the app publisher110) that has been contracted by theAME108 or is partnered with theAME108 to collect media ID's (e.g., the media ID122) and device/user identifiers (e.g., the device/user identifier(s)124) from mobile devices (e.g., the mobile device106).
• In the illustrated example, the app publisher110 (or a collection entity) sends themedia ID122 and the device/user identifier(s)124 asimpression data130 to aserver132 at theAME108. Theimpression data130 of the illustrated example may include onemedia ID122 and one or more device/user identifier(s)124 to report a single impression of themedia118, or it may include numerous media ID's122 and device/user identifier(s)124 based on numerous instances of collected data (e.g., the collected data126) received from themobile device106 and/or other mobile devices to report multiple impressions of media.
• In the illustrated example, theserver132 stores theimpression data130 in an AME media impressions store134 (e.g., a database or other data structure). Subsequently, theAME108 sends the device/user identifier(s)124 to thedemographic database proprietor104 to receiveuser information102 corresponding to the device/user identifier(s)124 from thedemographic database proprietor104 so that theAME108 can associate the user information with corresponding media impressions of media (e.g., the media118) presented at mobile devices (e.g., the mobile device106).
• In some examples, to protect the privacy of the user of themobile device106, themedia identifier122 and/or the device/user identifier(s)124 are encrypted before they are sent to theAME108 and/or to thedemographic database proprietor104. In other examples, themedia identifier122 and/or the device/user identifier(s)124 are not encrypted.
• After theAME108 receives the device/user identifier(s)124, theAME108 sends device/user identifier logs136 to thedemographic database proprietor104. In some examples, each of the device/user identifier logs136 may include a single device/user identifier124, or it may include numerous aggregate device/user identifiers124 received over time from one or more mobile devices. After receiving the device/user identifier logs136, thedemographic database proprietor104 looks up its users corresponding to the device/user identifiers124 in therespective logs136. In this manner, thedemographic database proprietor104 collectsuser information102 corresponding to users identified in the device/user identifier logs136 for sending to theAME108. For example, if thedemographic database proprietor104 is a wireless service provider and the device/user identifier log136 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 log136. When the users are identified, the wireless service provider copies the users' user information to theuser information102 for delivery to theAME108.
• In some other examples, thedata collector112 is configured to collect the device/user identifier(s)124 from themobile device106. Theexample data collector112 sends the device/user identifier(s)124 to theapp publisher110 in the collecteddata126, and it also sends the device/user identifier(s)124 to themedia publisher120. In some such other examples, thedata collector112 does not collect themedia ID122 from themedia118 at themobile device106 as thedata collector112 does in theexample system100 ofFIG. 1. Instead, themedia publisher120 that publishes themedia118 to themobile device106 retrieves themedia ID122 from themedia118 that it publishes. Themedia publisher120 then associates themedia ID122 to the device/user identifier(s)124 received from thedata collector112 executing in themobile device106, and sends collecteddata138 to theapp publisher110 that includes themedia ID122 and the associated device/user identifier(s)124 of themobile device106. For example, when themedia publisher120 sends themedia118 to themobile device106, it does so by identifying themobile device106 as a destination device for themedia118 using one or more of the device/user identifier(s)124 received from themobile device106. In this manner, themedia publisher120 can associate themedia ID122 of themedia118 with the device/user identifier(s)124 of themobile device106 indicating that themedia118 was sent to the particularmobile device106 for presentation (e.g., to generate an impression of the media118).
• In some other examples in which thedata collector112 is configured to send the device/user identifier(s)124 to themedia publisher120, thedata collector112 does not collect themedia ID122 from themedia118 at themobile device106. Instead, themedia publisher120 that publishes themedia118 to themobile device106 also retrieves themedia ID122 from themedia118 that it publishes. Themedia publisher120 then associates themedia ID122 with the device/user identifier(s)124 of themobile device106. Themedia publisher120 then sends theimpression data130, including themedia ID122 and the device/user identifier(s)124, to theAME108. For example, when themedia publisher120 sends themedia118 to themobile device106, it does so by identifying themobile device106 as a destination device for themedia118 using one or more of the device/user identifier(s)124. In this manner, themedia publisher120 can associate themedia ID122 of themedia118 with the device/user identifier(s)124 of themobile device106 indicating that themedia118 was sent to the particularmobile device106 for presentation (e.g., to generate an impression of the media118). In the illustrated example, after theAME108 receives theimpression data130 from themedia publisher120, theAME108 can then send the device/user identifier log136 to thedemographic database proprietor104 to request theuser information102 as described above in connection withFIG. 1.
• Although themedia publisher120 is shown separate from theapp publisher110 inFIG. 1, theapp publisher110 may implement at least some of the operations of themedia publisher120 to send themedia118 to themobile device106 for presentation. For example, advertisement providers, media providers, or other information providers may send media (e.g., the media118) to theapp publisher110 for publishing to themobile device106 via, for example, theapp program116 when it is executing on themobile device106. In some such examples, theapp publisher110 implements the operations described above as being performed by themedia publisher120.
• Additionally or alternatively, in contrast with the examples described above in which themobile device106 sends device/user identifiers124 to the audience measurement entity108 (e.g., via theapplication publisher110, themedia publisher120, and/or another entity), in other examples the mobile device106 (e.g., thedata collector112 installed on the mobile device106) sends the identifiers (e.g., the user/device identifier(s)124) directly to the database proprietor104 (e.g., not via the AME108). In some such examples, the examplemobile device106 sends themedia identifier122 to the audience measurement entity108 (e.g., directly or through an intermediary such as via the application publisher110), but does not send themedia identifier122 to thedatabase proprietors104.
• As mentioned above, the exampledemographic database proprietor104 provides theuser information102 to theexample AME108 for matching with themedia identifier122 to form media impression information. As also mentioned above, thedatabase proprietor104 is not provided copies of themedia identifier122. Instead, themobile device106 provides thedatabase proprietor104 with impression identifiers140. An impression identifier140 uniquely identifies an impression event relative to other impression events of the mobile device106 (and relative to the impression events of other devices) so that an occurrence of an impression at themobile device106 can be distinguished from other occurrences of impressions. However, the impression identifier140 does not itself identify the media associated with that impression event. In such examples, theimpression data130 from themobile device106 to theAME108 also includes the impression identifier140 and thecorresponding media identifier122.
• To match theuser information102 with themedia identifier122, the exampledemographic database proprietor104 provides theuser information102 to theAME108 in association with the impression identifier140 for the impression event that triggered the collection of theuser information102. In this manner, theAME108 can match the impression identifier140 received from themobile device106 to a corresponding impression identifier140 received from thedemographic database proprietor104 to associate themedia identifier122 received from themobile device106 with demographic information in theuser information102 received from thedatabase proprietor104. The impression identifier140 can additionally be used for reducing or avoiding duplication of demographic information. For example, the exampledemographic database proprietor104 may provide theuser information102 and the impression identifier140 to theAME108 on a per-impression basis (e.g., each time amobile device106 sends a request including a device/user identifier124 and an impression identifier140 to the demographic database proprietor104) and/or on an aggregated basis (e.g., send a set ofuser information102, which may include indications of multiple impressions at a mobile device102 (e.g., multiple impression identifiers140), to theAME108 presented at the mobile device106).
• 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 theAME108 records an impression once for each occurrence of the media being presented, delivered, or otherwise provided to themobile device106. For streaming media (e.g., video, audio, etc.), in some examples theexample AME108 measures demographics for media occurring over a period of time. For example, the AME108 (e.g., via theapp publisher110 and/or the media publisher120) provides beacon instructions to a client application or client software (e.g., theOS114, theweb browser117, theapp116, etc.) executing on themobile device106 when media is loaded at client application/software114-117. In some such examples, the beacon instructions cause the client application/software114-117 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 exampleimpression monitoring server132 identifies the requests from theweb browser117 and, in combination with one or more database proprietors, matches the impression information for the media with demographics of the user of theweb browser117.
• In some examples, a user loads (e.g., via the browser117) 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 thebrowser117 and/or thedata collector112 to send a pingback message (e.g., a beacon request) to abeacon server142. For example, when the beacon instructions are executed by theexample browser117, the beacon instructions cause thedata collector112 to send pingback messages (e.g., beacon requests, HTTP requests, pings) to theimpression monitoring server132 at designated intervals (e.g., once every minute or any other suitable interval). The example beacon instructions (or a redirect message from, for example, theimpression monitoring server132 or the database proprietor104) further cause thebrowser117 and/or thedata collector112 to send pingback messages or beacon requests to thedatabase proprietor104 that collect and/or maintain demographic information about users.
• Thedatabase proprietor104 transmits demographic information about the user associated with thedata collector112 and/or thebrowser117 for combining or associating with the impression determined by theimpression monitoring server132. If the user closes the web page containing the video before the end of the video, the beacon instructions are stopped, and thedata collector112 stops sending the pingback messages to theimpression monitoring server132. 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 theimpression monitoring server132 from themobile device106, the exampleimpression monitoring server132 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 server132).
• Themobile device106 of the illustrated example executes a client application/software114-117 that retrieves data from a host website (e.g., www.acme.com) that provides (e.g., serves) the media118 (e.g., audio, video, interactive media, streaming media, etc.) is obtained for presenting via themobile device106. In the illustrated example, the media118 (e.g., advertisements and/or content) is tagged with identifier information (e.g., amedia ID122, a creative type ID, a placement ID, a publisher source URL, etc.) and a beacon instruction. The example beacon instruction causes the client application/software114-117 to request further beacon instructions from abeacon server142 that will instruct the client application/software114-117 on how and where to send beacon requests to report impressions of themedia118. For example, the example client application/software114-117 transmits a request including an identification of the media118 (e.g., the media identifier122) to thebeacon server142. Thebeacon server142 generates and/or returnsbeacon instructions144 to the examplemobile device106. Although thebeacon server142 and theimpression monitoring server132 are shown separately, in some examples thebeacon server142 and theimpression monitoring server132 are combined. In the illustrated example,beacon instructions144 include a URL of the database proprietor (e.g., the demographic database proprietors104) or any other server to which themobile device106 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 taggedmedia118 include thebeacon instructions144. In such examples, the client application/software114-117 does not need to requestbeacon instructions144 from abeacon server142 because thebeacon instructions144 are already provided in the taggedmedia118.
• When thebeacon instructions144 are executed by themobile device106, thebeacon instructions144 cause themobile device106 to send beacon requests (e.g., repeatedly at designated intervals) to a remote server (e.g., theimpression monitoring server132, themedia publisher120, thedatabase proprietor104, or another server) specified in thebeacon instructions144. In the illustrated example, the specified server is a server of theaudience measurement entity108, such as theimpression monitoring server132. Thebeacon instructions144 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.
• While theexample system100 ofFIG. 1 is illustrated as having onedatabase proprietor104,multiple database proprietors104 may be used.
• 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® 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.
• Theexample system100 ofFIG. 1 includes amerchant database proprietor146. The examplemerchant database proprietor146 ofFIG. 1 stores account information for users who have registered with themerchant database proprietor146. In the example ofFIG. 1, users who register with themerchant database proprietor146 are then permitted to place orders for (e.g., purchase) products offered by themerchant database proprietor146 and/or offered by third parties using ordering services provided by themerchant database proprietor146. For example, themerchant database proprietor146 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.
• The examplemerchant database proprietor146 ofFIG. 1 provides an application (e.g., theapp116 ofFIG. 1) for download to themobile device106. For example, themobile device106 may download theapp116 from theapp publisher110 and/or directly from themerchant database proprietor146.
• When theapp116 is installed on themobile device106, the example user may login to an account with themerchant database proprietor146 and/or may register to create an account with themerchant database proprietor146. In either case, theexample app116 transmits merchant account information148 (e.g., a login name or other account identifier, a password, etc.) to themerchant database proprietor146, which identifies the user or account to themerchant database proprietor146.
• In addition to themerchant account information148, theexample app116 accesses the device/user identifier124 in themobile device106. Theapp116 of the illustrated example transmits the device/user identifier124 to themerchant database proprietor146.
• Upon receipt of themerchant account information148 and the device/user identifier124 and authentication of the corresponding user account, the examplemerchant database proprietor146 associates the user account with the device/user identifier124. As a result, the examplemerchant database proprietor146 can generatetransaction information150 for the user account, including transactions performed using the user account with the device/user identifier124.
• 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 examplemerchant database proprietor146 may associate multiple device/user identifiers124 with the user account such that media impressions occurring on any of the devices corresponding to the device/user identifiers124 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.
• As mentioned above, theexample AME108 receives theimpression data130 and the device/user identifier124 from the examplemobile device106. Theexample AME108 ofFIG. 1associates transaction information150 with impression information by matching impressions to transactions using the device/user identifier124. For example, theAME108 ofFIG. 1 receives, from themerchant database proprietor146, transaction information associated with a user account associated with a device/user identifier124 of themobile device106. Theexample AME108 also receives the impression data130 (or impression information) including an indication of the same device/user identifier124. Theexample AME108 ofFIG. 1 correlates the transaction information to the impressions by matching the device/user identifier124 in a transaction request152 (described below) to the device/user identifier124 that corresponds to a user account used to perform the transactions.
• To obtain the transaction information, theexample AME108 transmits atransaction request152 to the examplemerchant database proprietor146. Theexample transaction request152 includes a device/user identifier124. TheAME108 transmits the device/user identifier124 that is received in theimpression data130 to, for example, obtain transaction information to potentially be correlated to a media impression.
• The examplemerchant database proprietor146 receives thetransaction request152 including the device/user identifier124. Themerchant database proprietor146 looks up a user account that was previously associated with the device/user identifier124 (e.g., in a database). If themerchant database proprietor146 locates a user account associated with the device/user identifier124, the examplemerchant database proprietor146 generates the transaction information150 (e.g., based on transaction data stored in a database of the merchant database proprietor146).
• In the illustrated example, themerchant database proprietor146 transmits thetransaction information150 to theexample AME108. In some examples, themerchant database proprietor146 includes the device/user identifier124 in its response to theAME108 to enable theAME108 to determine the device/user identifier124 and/or therequest152 for which thetransaction information150 is being provided. Theexample AME108 of the illustrated example matches thetransaction information150 received from themerchant database proprietor146 to theimpression data130.
• To match the impressions in theimpression data130 to the transactions in thetransaction information150, theexample AME108 ofFIG. 1 determines the product(s) represented in theimpression data130. Examples of product(s) represented in media include products represented in advertisements for those products (e.g., a Coca-Cola® 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® watch worn by an actor in a television show, a particular car brand used in a movie, etc.). For example, theAME108 may access a database that specifies the products represented in each item ofmedia118. Similarly, theexample transaction information150 ofFIG. 1 provided by themerchant database proprietor146 includes an identification of the product(s) purchased in the transactions made by the user account associated with the device/user identifier124.
• Theexample AME108 compares the product(s) represented in theimpression data130 to the product(s) in thetransaction information150 to determine whether there are any matching product(s). If theAME108 identifies a product represented in an impression that matches a product involved in a purchase transaction, theexample AME108 determines whether the purchase transaction occurred after the impression. For example, theimpression data130 includes time and date information indicating the time and date of the impression on themobile device106. Similarly, thetransaction information150 includes time and date information indicating the time and date of the transaction(s) represented in thetransaction information150. TheAME108 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.
• When theAME108 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), theexample AME108 correlates the media impression to the purchase of the product(s) represented in the impression. Theexample AME108 determines whether such a correlation occurred for the product(s) for multiplemobile devices106 and/or user accounts. For example, theAME108 determines a percentage of a set ofmobile devices106 and/or user accounts for which the media impression of a product occurred before the purchase transaction of that product. In some examples, theAME108 determines percentages of sets ofmobile device106 for different publishers and/or different media to evaluate the effectiveness of publishers and/or media for influencing purchasing behavior of the product.
• In some examples, themerchant database proprietor146 providestransaction information150 to theAME108 for all transactions performed using a user account associated with the device/user identifier124, for all transactions performed within a specified time period using the user account associated with the device/user identifier124, and/or for specified type(s) of transaction(s) performed using a user account associated with the device/user identifier124. In some other examples, theAME108 determines the product(s) represented in the media impressions occurring at themobile device106, and transmitsproduct information154 to themerchant database proprietor146 in thetransaction request152. Limiting thetransaction request152 to product(s) of interest may enhance the privacy of the users of themerchant database proprietor146 by restricting theAME108 to information about specific product(s).
• In some examples, theAME108 may transmit theproduct information154 in therequest152 without transmitting the device/user identifier124. In such examples, themerchant database proprietor146 looks up theproduct information154 to determine which user accounts have purchased the product identified in theproduct information154. The examplemerchant database proprietor146 may then return a list of device/user identifiers124 that correspond to user accounts that have purchased the product identified in theproduct information154. In some examples, the transactions returned in response to atransaction request152 are limited to transactions occurring within a particular time period, such as a period of time designated in therequest152, a period of time determined based on therequest152, a predetermined time period, and/or a standard time period.
• When the examplemerchant database proprietor146 receives atransaction request152 including theproduct information154, the examplemerchant database proprietor146 determines whether the product(s) specified in theproduct information154 have been purchased in any transactions performed using the user account associated with the device/user identifier124 specified in thetransaction request152. If the product(s) specified in theproduct information154 have been purchased, the examplemerchant database proprietor146 returns thetransaction information150 for the transactions in which the specified product(s) were purchased. For any product(s) not purchased using the user account, the examplemerchant database proprietor146 does not respond or responds with an indication that those product(s) were not purchased using the user account. By requiring theAME108 to specify theproduct information154, theexample AME108 does not receive transaction information that is not relevant to media impressions occurring on themobile device106.
• Theexample AME108 ofFIG. 1 aggregates transaction information and media impressions to measure effectiveness of the media corresponding to the media impressions. As explained in more detail below, theexample AME108 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, theAME108 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 theAME108 to not have been exposed to the item of media, according to the impression information.
• Examples that may be used to implement the system ofFIG. 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.
• FIG. 2 illustrates an example impression-transaction analyzer200 which may be implemented in the exampleaudience measurement server132 ofFIG. 1 to match impression information associated with a mobile device (e.g., themobile device106 ofFIG. 1) to transaction information corresponding to a purchase made using a user account accessed by themobile device106. The example impression-transaction analyzer200 ofFIG. 2 includes anexample product checker202, anexample product database204, an example transaction requester206, an example impression/transaction matcher208, anexample group identifier210, anexample transaction aggregator212, and anexample effectiveness calculator214.
• Theexample product checker202 ofFIG. 2 identifies products associated with media impressions. For example, theproduct checker202 of the illustrated example receives impression data from mobile devices (e.g., theimpression data130 from themobile device106 ofFIG. 1). In this example, theimpression data130 includes amedia identifier122 formedia118 corresponding to an impression occurring at themobile device106. Theexample product checker202 queries theproduct database204, which stores indications of products represented in themedia118 that corresponds to themedia identifier122. Theproduct checker202 of the illustrated example looks up a product corresponding to themedia118 in theproduct database204 using themedia identifier122 as a key. In response to the query, theexample product database204 returns a product identifier of a product (e.g., theproduct information154 ofFIG. 1) to theexample product checker202. Over time, theexample product database204 may be updated with new associations of media to products. In the illustratedexample product database204, a media item may be associated with multiple products and/or a product may be represented by multiple media items.
• In addition to themedia identifier122, theexample impression data130 also includes the device/user identifier124. In the illustrated example, theexample product checker202 provides the device/user identifier124 and theproduct information154 corresponding to thetransaction request152 to thetransaction requester206.
• The example transaction requester206 ofFIG. 2 generates and sends atransaction request152 to one or more merchant database proprietors (e.g., themerchant database proprietor146 ofFIG. 1). In the example ofFIG. 2, thetransaction request152 includes the device/user identifier124 and theproduct information154. The example transaction requester206 sends thetransaction request152 to themerchant database proprietor146 to obtain transaction information from themerchant database proprietor146.
• If themerchant database proprietor146 hastransaction information150 corresponding to the device/user identifier124, the examplemerchant database proprietor146 sends thetransaction information150 to the impression-transaction analyzer200. In some examples, themerchant database proprietor146 limits thetransaction information150 that is returned to transactions that correspond to both the device/user identifier124 and theproduct information154. In other examples, the returned information is not so limited and/or theproduct information154 is not provided to themerchant database proprietor146.
• The example transaction requester206 ofFIG. 2 receives thetransaction information150 from the merchant database proprietor146 (e.g., in response to the transaction request152) and provides thetransaction information150 and theimpression data130 to the impression/transaction matcher208. The example impression/transaction matcher208 ofFIG. 2 matches impressions occurring at the mobile device106 (e.g., from the impression data130) to transactions of purchases performed using a user account associated with the mobile device106 (e.g., from the transaction information150). By matching the impressions to the transactions, the example impression/transaction matcher208 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 identifier124. This information can be used to credit the impression with driving the transaction.
• To match an impression to a transaction, the example impression/transaction matcher208 compares A) combinations of a device/user identifier124 andproduct information154 that are obtained from theimpression data130 to B) combinations of a device/user identifier124 andproduct information154 that correspond totransaction information150 obtained from themerchant database proprietor146. Combinations of the device/user identifier124 and theproduct information154 that are found in both theimpression data130 and in thetransaction information150 are considered to match.
• As an example, Table 1 below includes a set of example combinations of device/user identifiers124 (e.g., Device/User ID) and product information154 (e.g., Product ID) obtained from impression data130 (e.g., Impression ID) (e.g., by the example product checker202) collected at amobile device106.

• 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

• Table 2 below includes a set of example combinations of device/user identifiers124 (e.g., Device/User ID) and product information154 (e.g., Product ID) corresponding to transaction information150 (e.g., Transaction ID) received by the transaction requester206 from amerchant database proprietor146. The combinations in Table 2 may be returned in thetransaction information150 from amerchant database proprietor146 and/or may be associated with thetransaction information150 by thetransaction requester206 when thetransaction information150 is identified as occurring in response to atransaction request152.

• 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

• 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 matcher208 ofFIG. 2 will identify theimpression data130 having impression ID11 as having the same combination of device/user identifier124 (e.g., Device/User ID of HOI35JGETR) and product information154 (e.g., Product ID of R9ANT20EJY) astransaction information150 having transaction ID21. In this example, the impression/transaction matcher208 ofFIG. 2 also identifies theimpression data130 having impression ID13 in Table 1 above as having the same combination of device/user identifier124 (e.g., Device/User ID of B8PE8JH26N) and product information154 (e.g., Product ID of NB2EYZ4YOG) astransaction information150 having transaction ID24.
• While Table 1 above shows thatadditional impressions data130 associated with the device/user identifier124 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 identifier124 that are also associated with the product having a Product ID of 7ZFF46F77Z (i.e., the Product ID associated with impression ID12). Therefore, the impression/transaction matcher208 does not identify a match for impression ID12.
• 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 ID22 in Table 2). However, Table 1 does not indicate that an impression of media representing that product (i.e., I9DBW9RC8R) occurred on amobile device106 that corresponds to the device/user ID HOI35JGETR. Therefore, the impression/transaction matcher208 of this example does not identify a match for transaction ID22.
• 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 matcher208 ofFIG. 2 identifies a transaction (e.g., from Table 2 above) that has a device/user identifier124 andproduct information154 combination that matches the device/user identifier124 andproduct information154 combination of an impression (e.g., from Table 1 above), the impression/transaction matcher208 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 ofFIG. 2, the impression/transaction matcher208 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).
• In the example of Tables 1 and 2 above, the impression/transaction matcher208 would determine that the impression having impression ID11 is related to the matching transaction having transaction ID21 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 ID11 is an advertisement for a product, and the transaction corresponding to transaction ID21 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.
• Conversely, in the example of Tables 1 and 2 above, the impression/transaction matcher208 would determine that the impression having impression ID13 is not related to the matching transaction having transaction ID24 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.
• Theexample group identifier210 ofFIG. 2 assigns device/user identifiers124 to groups based on whether the device/user identifier124 is associated with an impression of media of interest (e.g., media corresponding to a product of interest). For example, thegroup identifier210 ofFIG. 2 assigns device/user identifiers124 that correspond to impressions of the media to an “exposed” group, and assigns device/user identifiers124 that do not correspond to the media of interest to a “control” group. In some examples, thegroup identifier210 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.
• The example impression/transaction matcher208 ofFIG. 2 provides thegroup identifier210 ofFIG. 2 with the impression information (e.g., the impression information of Table 1). Theexample group identifier210 determines, for each device/user identifier124 represented in the impressions, whether the device/user identifier124 has been exposed to media representing a product of interest. For example, thegroup identifier210 is provided withproduct information154 for a product of interest, such as a product for which a media campaign is to be evaluated for effectiveness.
• In some examples, thegroup identifier210 is provided with amedia identifier122 instead ofproduct information154. Amedia identifier122 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, thegroup identifier210 may obtainimpression data130 from theproduct checker202. Using theimpression data130, thegroup identifier210 determines the device/user identifiers124 corresponding to impressions of themedia118 having themedia identifier122.
• Theexample group identifier210 ofFIG. 2 sorts the device/user identifiers124 (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/identifiers124 corresponding to impressions of media representing the product of interest. For example, thegroup identifier210 may populate a table or other data structure corresponding to the exposed group with device/user identifiers124 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/identifiers124 for which impressions of media representing the product of interest did not occur. Using the example Table 1 above, if thegroup identifier210 receives the Product ID R9ANT20EJY as the product of interest, theexample group identifier210 would place the device/user identifier124 (device/user ID) of HOI35JGETR in the exposed group because the device/user identifier124 of HOI35JGETR reported an impression of media corresponding to Product ID R9ANT20EJY. In this example, thegroup identifier210 would place the device/user identifier124 (device/user ID) of B8PE8JH26N in a table or other data structure corresponding to the control group because the device/user identifier124 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 identifier124 and the control group would have a count of one device/user identifier124.
• The example impression/transaction matcher208 ofFIG. 2 provides the transactions (e.g., the transactions of Table 2 above) to thetransaction aggregator212. Additionally, theexample group identifier210 provides the list of device/user identifiers124 that belong to each of the groups (e.g., the control group and the exposed group) to thetransaction aggregator212. For example, thegroup identifier210 may provide a first list of device/user identifiers124 that have been determined to be in the control group and a second list of device/user identifiers124 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.
• Theexample transaction aggregator212 ofFIG. 2 determines up to four separate sets of purchases or transactions based on the transactions obtained from the impression/transaction matcher208 and based on the groups identified by thegroup identifier210. In the illustrated example, thetransaction aggregator212 determines 1) the number of the products purchased by user accounts corresponding to device/user identifiers124 in the control group during a first time period; 2) the number of the products purchased by user accounts corresponding to device/user identifiers124 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 identifiers124 in the exposed group during the first time period; and 4) the number of the products purchased by user accounts corresponding to device/user identifiers124 in the exposed group during the second time period.
• 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.
• 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.
• To determine the number of the products purchased via user accounts corresponding to device/user identifiers124 in the control group during a first time period (e.g., the first example set of purchases determined by the transaction aggregator212), theexample transaction aggregator212 identifies transactions (e.g., transactions from Table 2 above) that have a time and date within the first period and have a device/user identifier124 assigned to the control group by thegroup identifier210. 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 identifiers124 in the control group during the first time period, theexample transaction aggregator212 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.
• To determine the number of the products purchased via user accounts corresponding to device/user identifiers124 in the control group during a second time period (e.g., the second example set of purchases determined by the transaction aggregator212), theexample transaction aggregator212 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 identifier124 assigned to the control group by thegroup identifier210. 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 identifiers124 assigned to the control group during the second time period, theexample transaction aggregator212 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.
• To determine the number of the products purchased via user accounts corresponding to device/user identifiers124 in the exposed group during the first time period (e.g., the third example set of purchases determined by the transaction aggregator212), theexample transaction aggregator212 identifies transactions (e.g., transactions from Table 2 above) that have a time and date within the first period and have a device/user identifier124 assigned to the exposed group by thegroup identifier210. In other words, to determine the number of the products purchased via user accounts corresponding to device/user identifiers124 assigned to the exposed group during the first time period, theexample transaction aggregator212 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.
• To determine the number of the products purchased via user accounts corresponding to device/user identifiers124 in the exposed group during the second time period (e.g., the fourth example set of purchases determined by the transaction aggregator212), theexample transaction aggregator212 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 identifier124 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 identifiers124 in the exposed group during the second time period, theexample transaction aggregator212 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.
• Theexample effectiveness calculator214 ofFIG. 2 calculates the effectiveness of the media and/or the effectiveness of the publishers (e.g., the delivery methods for the media). For example, theeffectiveness calculator214 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. Theexample effectiveness calculator214 calculates the sales using the sets of purchases determined by thetransaction aggregator212 for the control and exposed groups during the first and second time periods.
• In some examples, theeffectiveness calculator214 calculates a publisher effectiveness (e.g., for anapp publisher110, for amedia publisher120, 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 thetransaction aggregator212 as described above (e.g., the number of the products purchased via user accounts corresponding to device/user identifiers124 in the exposed group during the second time period) determined using device/user identifiers124 associated with impressions delivered via the first publisher (e.g., delivered via an app and/or a website associated with theapp publisher110, delivered in association with media published by themedia publisher120, etc.). Similarly, the exposed group for the second publisher is the fourth example group calculated by thetransaction aggregator212 as described above (e.g., the number of the products purchased via user accounts corresponding to device/user identifiers124 in the exposed group during the second time period) determined using device/user identifiers124 associated with impressions delivered via the second publisher (e.g., delivered via an app and/or a website associated with theapp publisher110, delivered in association with media published by themedia publisher120, etc.).
• Additionally or alternatively, theexample effectiveness calculator214 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, theeffectiveness calculator214 may determine the media effectiveness metric using the four example sets of purchases determined by thetransaction aggregator212 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)).
• FIG. 3 illustrates an example table300 illustrating an example determination of an effectiveness of media impressions.FIG. 4 is agraph400 illustrating the data in the example table300 ofFIG. 3. The example table300 and/or theexample graph400 may be generated by the example impression-transaction analyzer200 ofFIG. 2 based onimpression data130 obtained from themobile device106,user information102 obtained from the exampledemographic database proprietor104, and/ortransaction information150 obtained from themerchant database proprietor146 ofFIG. 1.
• In the examples ofFIGS. 3 and 4, the impression-transaction analyzer200 does not calculate the transactions occurring prior to the media impressions (as in the examples described above with reference toFIG. 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 themerchant database proprietor146 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.
• The example table300 ofFIG. 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, assumePublisher A302 publishes a first application (e.g., theapp116 ofFIG. 1) andPublisher B304 publishes a second application (e.g., thebrowser117 ofFIG. 1). Theexample media publisher120 ofFIG. 1 may choose to have themedia118 ofFIG. 1 delivered to themobile device106 via either or both of theapp116 and/or thebrowser117 ofFIG. 1.
• For each of thepublishers302,304 of the example table300 ofFIG. 3, theexample group identifier210 ofFIG. 2 determines a number of user accounts (or persons associated with the user accounts) belonging to thecontrol group306 as described above (e.g., during a time period following the commencement of media impressions atmobile devices106 via thepublishers302,304). Thegroup identifier210 also determines a number of user accounts belonging to the exposedgroup308 as described above.
• In the example ofFIGS. 3 and 4, thegroup identifier210 identifies (e.g., based on theimpression data130 from those mobile devices106) 12,200 user accounts in the control group for publisher A302 (e.g., associated withmobile devices106 using theapp116 from thepublisher A302 that have not had an impression of the media). Similarly, thegroup identifier210 identifies (e.g., based on theimpression data130 from those mobile devices106) 17,500 user accounts in the control group for publisher B304 (e.g., associated withmobile devices106 using thebrowser117 from thepublisher B304 that have not had an impression of the media).
• Continuing the example, thegroup identifier210 identifies (e.g., based on theimpression data130 from those mobile devices106) 35,400 user accounts in the exposed group for publisher A302 (e.g., associated withmobile devices106 using theapp116 from thepublisher A302 that have had an impression of the media). Similarly, thegroup identifier210 identifies (e.g., based on theimpression data130 from those mobile devices106) 30,100 user accounts in the exposed group for publisher B304 (e.g., associated withmobile devices106 using thebrowser117 from thepublisher B304 that have had an impression of the media).
• Theexample transaction aggregator212 ofFIG. 2 determines a number of control group sales310 (e.g., transactions involving the product, of a quantity of units of the product, etc.) and a number of exposedgroup sales312 of the respective control groups of theexample publishers302,304. The examplecontrol group sales310 may be the first or the second example groups of purchases determined by thetransaction aggregator212 as described above. The example exposedgroup sales312 may be the third or the fourth example groups of purchases determined by thetransaction aggregator212 as described above. Thetransaction aggregator212 determines a number of transactions for the product corresponding to the members of each of thegroups306,308 identified by thegroup identifier210. In the example ofFIGS. 3 and 4,Publisher A302 is determined to have 4,200control group sales310 and 22,100 exposedgroup sales312 of the example product. Therefore, 34.4% (e.g., 4,200/12,200) of theexample control group306 of thepublisher A302 purchased the example product of interest during the measured time period, while 62.4% (e.g., 22,100/35,400) of the exposedgroup308 of thepublisher A302 purchased the example product during the measured time period. Therefore, the media impressions delivered via the app116 (e.g., via Publisher A) resulted in asales lift314 of 81.3% (e.g., (62.4%−34.4%)/34.4%) for the product in the exposedgroup308 relative to thecontrol group306.
• Publisher B304 is determined to have 5,600control group sales310 and 10,600 exposedgroup sales312 of the example product. Therefore, 32% (e.g., 5,600/17,500) of theexample control group306 of thepublisher B304 purchased the example product of interest during the measured time period, while 35.2% (e.g., 10,600/30,100)) of the exposedgroup308 of thepublisher B304 purchased the example product during the measured time period. Therefore, the media impressions delivered via the browser117 (e.g., via Publisher B) resulted in asales lift314 of 10.0% (e.g., (35.2%-32%)/32%) for the product in the exposedgroup308 relative to thecontrol group306.
• By comparing theexample sales lifts314 for thepublishers302,304 ofFIGS. 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 app116 (e.g., via Publisher A302) than through the browser117 (e.g., via Publisher B304) (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 tomobile devices106 via the app116 (provided by Publisher A302) and fewer via the browser117 (provided by Publisher B304). Additionally or alternatively, the manufacturer (and/or its advertising agent) replace thebrowser117 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 byPublisher A302 ofFIG. 3.
• FIG. 5 is a block diagram of an exampletransaction information provider500 that may be used to implement the examplemerchant database proprietor146 ofFIG. 1. The exampletransaction information provider500 includes anexample user authenticator502, an example account-identifier correlator504, anexample transaction engine506, an exampletransaction query generator508, and anexample transaction reporter510. The exampletransaction information provider500 further includes databases including an exampleuser account database512, anexample product database514, and anexample transaction database516.
• Theexample user authenticator502 ofFIG. 5 receives user login requests (e.g., from themobile device106, theapp116 ofFIG. 1). In the example ofFIG. 5, the user login requests include the examplemerchant account information148 ofFIG. 1. Themerchant account information148 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, theexample user authenticator502 verifies the merchant account information148 (e.g., the account identifier and/or the authenticator(s)) in theuser account database512, which stores themerchant account information148 for authentication purposes.
• As mentioned above with reference toFIG. 1, the example user login request that is authenticated by theuser authenticator502 also includes a device/user identifier124 corresponding to the mobile device106 (e.g., the device/user identifier124 ofFIG. 1). In the example ofFIG. 5, the device/user identifier124 is an identifier (e.g., an IMEI number, an IDFA number, etc.) that is not set by either of themerchant database proprietor146 ofFIG. 1 or thetransaction information provider500 ofFIG. 5. Because the device/user identifier124 is not set by thetransaction information provider500, thetransaction information provider500 is required to obtain the device/user identifier124 from themobile device106.
• The example account-identifier correlator504 ofFIG. 5 matches themerchant account information148 to the device/user identifier124 included in the request. For example, the account-identifier correlator504 stores the device/user identifier124 in theuser account database512 in association with themerchant account information148 so that the device/user identifier124 is associated with the user account at the merchant. Because a user may log in to themerchant database proprietor146 from multiple devices, the example account-identifier correlator504 may correlate multiple device/user identifiers504 to the same merchant account information148 (e.g., to a same user account).
• Theexample transaction engine506 enables users to conduct transactions, such as purchasing products from the merchant database proprietor146 (e.g., an organization such as a commercial merchant). When a user (e.g., a user having a user account with the merchant database proprietor146) purchases a product via thetransaction engine506, theexample transaction engine506 accesses theproduct database514 to determine product identifier(s) of the product(s) and/or service(s) purchased in the transaction. Theexample transaction engine506 stores transaction information (e.g., thetransaction information150 ofFIG. 1) in thetransaction database516. 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 identifiers124 from themobile device106 may then be matched to the transactions in thetransaction database516 based on the mapping of user accounts to the device/user identifier124 in theuser account database512.
• Theexample product database514 may store the same information as theproduct database204 ofFIG. 2. In some examples, theproduct database204 ofFIG. 2 includes a subset of the product identifiers included in theproduct database514 ofFIG. 5 (e.g., when theproduct database204 ofFIG. 2 includes product identifiers only for products of interest to the audience measurement entity108). In some other examples, theproduct database514 ofFIG. 5 includes a subset of the product identifiers included in theproduct database204 ofFIG. 2 (e.g., when there are multiplemerchant database proprietors146 having different products for purchase).
• The exampletransaction query generator508 ofFIG. 5 receives requests for transaction information (e.g., from theaudience measurement entity108 of FIG.1). For example, thetransaction query generator508 may receive arequest152 for transactions that have been performed using an account corresponding to the device/user identifier124 and that includeproduct information154.
• Upon receipt of such arequest152, the exampletransaction query generator508 queries theuser account database512 to determine a user account (e.g., an account identifier, a user name, etc.) that corresponds to the device/user identifier124 in therequest152. The exampleuser account database512 determines the user account that matches the device/user identifier124 (e.g., the account previously correlated to the device/user identifier124 by the account-identifier correlator504). Theuser account database512 returns the account identifier to the exampletransaction query generator508.
• Using the account identifier, the exampletransaction query generator508 queries theproduct database514 using theproduct information154 in therequest152 to determine a product identifier used by thetransaction information provider500 to identify the product (e.g., an internal reference number for the product that is used within thetransaction information provider500, 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 thetransaction information provider500. The exampletransaction query generator508 then queries thetransaction database516 using the account identifier (e.g., obtained by querying the user account database512) and the product identifier (e.g., obtained by querying the product database514) to identify transactions involving the product that were conducted using the specified account.
• Thetransaction database516 returns information describing the identified transactions, including the account identifier, the device identifiers, and the date and time of the transaction. The exampletransaction query generator508 provides the transaction information returned from the transaction database to thetransaction reporter510. Theexample transaction reporter510 ofFIG. 5returns transaction information150 to theAME108 ofFIG. 1 (e.g., in response to a corresponding transaction request152). In the example ofFIG. 5, thetransaction reporter510 converts the information received from thetransaction database516 to information usable by theAME108. For example, thetransaction reporter510 may convert an account identifier associated with a transaction in thetransaction database516 to a device/user identifier124 recognizable by the AME108 (e.g., to the device/user identifier124 included in thetransaction request152 and obtained from the transaction query generator508). Additionally or alternatively, thetransaction reporter510 may convert a product identifier (e.g., a UPC code, a service code, etc.) used by thetransaction information provider500 to corresponding product information154 (e.g., the product information included in thetransaction request152 and obtained from the transaction query generator508).
• Theexample transaction reporter510 ofFIG. 5 sends thetransaction information150 to theexample AME108. TheAME108 receives thetransaction information150 and determines the effectiveness of media impressions as described above.
• While example manners of implementing the example impression-transaction analyzer200 and the transaction information provider have been illustrated inFIGS. 2 and 5, one or more of the elements, processes and/or devices illustrated inFIGS. 2 and 5 may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, theexample product checker202, theexample product database204, the example transaction requester206, the example impression/transaction matcher208, theexample group identifier210, theexample transaction aggregator212, theexample effectiveness calculator214, theexample user authenticator502, the example account-identifier correlator504, theexample transaction engine506, the exampletransaction query generator508, theexample transaction reporter510, the exampleuser account database512, theexample product database514, theexample transaction database516 and/or, more generally, the example impression-transaction analyzer200 ofFIG. 2, and/or the exampletransaction information provider500 ofFIG. 5 may be implemented using hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of theexample product checker202, theexample product database204, the example transaction requester206, the example impression/transaction matcher208, theexample group identifier210, theexample transaction aggregator212, theexample effectiveness calculator214, theexample user authenticator502, the example account-identifier correlator504, theexample transaction engine506, the exampletransaction query generator508, theexample transaction reporter510, the exampleuser account database512, theexample product database514, the example transaction database and/or, more generally, the example impression-transaction analyzer200, and/or the exampletransaction information provider500 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 theexample product checker202, theexample product database204, the example transaction requester206, the example impression/transaction matcher208, theexample group identifier210, theexample transaction aggregator212, theexample effectiveness calculator214, theexample user authenticator502, the example account-identifier correlator504, theexample transaction engine506, the exampletransaction query generator508, theexample transaction reporter510, the exampleuser account database512, theexample product database514, and/or theexample transaction database516 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 analyzer200 ofFIG. 2 and/or the exampletransaction information provider500 ofFIG. 5 may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated inFIGS. 2 and/or5, and/or may include more than one of any or all of the illustrated elements, processes and devices.
• Flowcharts representative of example machine readable instructions for implementing the exampleaudience measurement entity108, theaudience measurement server132, and/or the examplemerchant database proprietor146 ofFIG. 1, the example impression-transaction analyzer200 ofFIG. 2, and/or the exampletransaction information provider500 ofFIG. 5 are shown inFIGS. 6-11. In these examples, the machine readable instructions comprise one or more programs for execution by a processor such as theprocessor1212 shown in theexample processor platform1200 discussed below in connection withFIG. 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 theprocessor1212, but the entire program(s) and/or parts thereof could alternatively be executed by a device other than theprocessor1212 and/or embodied in firmware or dedicated hardware. Further, although the example one or more programs are described with reference to the flowcharts illustrated inFIGS. 6-11, many other methods of implementing the example impression data compensator200 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.
• As mentioned above, the example processes ofFIGS. 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 ofFIGS. 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.
• FIG. 6 is a flow diagram representative of example machinereadable instructions600 which may be executed to implement the exampleaudience measurement server132 ofFIG. 1 and/or the example impression-transaction analyzer200 ofFIG. 2 to associate media impressions to transaction information. Theexample instructions600 ofFIG. 6 will be described with reference to the example impression-transaction analyzer200 ofFIG. 2.
• Theexample product checker202 ofFIG. 2 receives media impression information from mobile devices (e.g., themobile device106 ofFIG. 1) (block602). In the illustrated example, the received media impression information includes a device/user identifier such as the device/user identifier124 ofFIG. 1. Example types of the device/user identifier124 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.
• Theexample product checker202 determines product information associated with the media impression information (block604). For example, theproduct checker202 may access (e.g., query) theproduct database204 ofFIG. 2 to determine an identifier of a product that is represented in a media impression at themobile device106 and which resulted in receiving the media impression information inblock602.
• The example transaction requester206 requests transaction information from a merchant database proprietor (e.g., themerchant database proprietor146 ofFIG. 1) based on the device/user identifier124 (e.g., determined in block602) and/or based on the product information (e.g., determined in block604) (block606). For example, thetransaction requester206 may generate atransaction request152 ofFIG. 1 including the device/user identifier124 and/or theproduct information154, and send thetransaction request152 to themerchant database proprietor146.
• The example transaction requester206 receivestransaction information150 from the merchant database proprietor146 (block608). Thetransaction information150 may include, for example, a unique transaction identifier, a device/user identifier124, a product identifier, and/or a time/date at which the transaction occurred.Example transaction information150 is shown in Table 2 above. If a transaction performed at themerchant database proprietor146 involved multiple products, the example transaction requester206 may receive multiple records, each representing one product involved in the transaction.
• The example impression/transaction matcher208 associates transactions involving a product with media impressions corresponding to the product (block610). For example, the impression/transaction matcher208 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 identifier124 as a transaction and that the media impression represents a product involved in the transaction. In some examples, the impression/transaction matcher208 matches media impressions to transactions. For example, the impression/transaction matcher208 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 block610 are described below with reference toFIG. 7.
• When the appropriate media impressions and transactions have been associated (block610), theexample effectiveness calculator214 ofFIG. 2 determines a media effectiveness and/or a publisher effectiveness (block612). For example, theeffectiveness calculator214 may determine whether media impressions delivered via a first publisher (e.g., theapp publisher110, the media publisher120) result in a higher sales lift (e.g., a larger sales increase). Additionally or alternatively, theexample effectiveness calculator214 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. Theexample instructions600 ofFIG. 6 end.
• FIG. 7 is a flow diagram representative of example machinereadable instructions700 which may be executed to implement the exampleaudience measurement server132 ofFIG. 1 and/or the example impression-transaction analyzer200 ofFIG. 2 to correlate transactions involving a product to media impressions corresponding to the product. In some examples, theexample instructions700 ofFIG. 7 may be performed to implement block610 ofFIG. 6. Theexample instructions700 ofFIG. 7 will be described with reference to the example impression-transaction analyzer200 ofFIG. 2.
• Theexample instructions700 begin afterblock608 ofFIG. 6 (e.g., receiving transaction information). The example impression/transaction matcher208 ofFIG. 2 selects a media impression from the media impression information (block702). For example, the impression/transaction matcher208 may select a media impression record from the records of Table 1 above. In this example, the impression/transaction matcher208 selects the first example record of Table 1 above (e.g., Impression ID11).
• The example impression/transaction matcher208 determines a product represented by the media corresponding to the selected media impression (block704). For example, the impression/transaction matcher208 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.
• The example impression/transaction matcher208 ofFIG. 2 also determines a device/user identifier124 corresponding to the selected media impression (block706). For example, the impression/transaction matcher208 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.
• The example impression/transaction matcher208 selects a transaction from the transaction information (block708). For example, the impression/transaction matcher208 may select a transaction record from the records of Table 2 above. In this example, the impression/transaction matcher208 selects the first example record of Table 2 above (e.g., Transaction ID21).
• The example impression/transaction matcher208 determines a product purchased in the transaction corresponding to the selected transaction (block710). For example, the impression/transaction matcher208 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.
• The example impression/transaction matcher208 ofFIG. 2 also determines a device/user identifier124 corresponding to an account used to perform the selected transaction (block712). For example, the impression/transaction matcher208 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.
• The example impression/transaction matcher208 determines whether the selected media impression matches the selected transaction based on the respective products and the respective device/user identifiers (block714). For example, the impression/transaction matcher208 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).
• If the selected media impression matches the selected transaction (block714), the example impression/transaction matcher208 ofFIG. 2 determines whether a time/date of the selected media impression occurred prior to the time/date of the selected transaction (block716). For example, the impression/transaction matcher208 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 (block716), the example impression/transaction matcher208 associates the selected transaction to the selected media impression (block718). By associating the selected transaction to the selected media impression (block718), the example impression/transaction matcher208 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).
• If the time/date of the selected media impression does not occur prior to the time/date of the selected transaction (block716), or if the selected media impression does not match the selected transaction (block714), the example impression/transaction matcher208 determines whether there are additional transactions to compare to the selected media impression (block720). If there are additional transactions to compare to the selected media impression (block720), control returns to block708 to select another transaction (e.g., to select another transaction record from Table 2).
• If there are no more transactions to compare to the selected media impression (block720), or after associating the selected transaction to the selected media impression (block718), the example impression/transaction matcher208 determines whether there are additional media impressions (block722). If there are additional media impressions (block722), control returns to block702 to select another media impression. When there are no more media impressions (block722), theexample instructions700 ofFIG. 7 end and control returns to a calling function or process such as the example instructions ofFIG. 6.
• FIGS. 8A and 8B show a flow diagram representative of example machinereadable instructions800 which may be executed to implement the exampleaudience measurement server132 ofFIG. 1 and/or the example impression-transaction analyzer200 ofFIG. 2 to determine media and publisher effectiveness. In some examples, theexample instructions800 ofFIGS. 8A and 8B may be performed to implement block612 ofFIG. 6. Theexample instructions800 ofFIGS. 8A and 8B will be described with reference to the example impression-transaction analyzer200 ofFIG. 2.
• Theexample group identifier210 ofFIG. 2 selects a publisher (block802). For example, thegroup identifier210 may select an app publisher (e.g., a publisher of theapp116 ofFIG. 1, a publisher of thebrowser117 ofFIG. 1, etc.) and/or a media publisher (e.g., a publisher ofmedia118 presented on themobile device106 ofFIG. 1 via theapp116 and/or via the browser117).
• Theexample group identifier210 assigns device/user identifiers124 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 (block804). The exposed group for the selected publisher therefore includes device/user identifiers124 of thosemobile devices106 from whichimpression data130, specifying the media of interest and the selected publisher, has been received. For example, if the selected publisher is a publisher of theapp116, the exposed group for the selected publisher includes the device/user identifiers124 formobile devices106 on which media impressions have occurred using the app116 (e.g., according to theimpression data130 reporting the media impressions to the AME108).
• Theexample transaction aggregator212 determines a number of transactions that correspond to the device/user identifiers124 in the exposed group for the selected publisher (block806). For example, thetransaction aggregator212 may determine a number of transactions that match the device/user identifiers124. The identification of matching transactions may be performed prior to executing the instructions800 (e.g., by the impression/transaction matcher208), such as by executingblock610 ofFIG. 6 and/or by executing theinstructions700 ofFIG. 7.
• Theexample transaction aggregator212 calculates a proportion of the exposed group for the selected publisher that purchased the product represented in the media of interest (block808). For example, thetransaction aggregator212 determines the number of the device/user identifiers124 that were associated with a media impression that matched a transaction, as a percentage of the total number of device/user identifiers124 in the exposed group. Theexample transaction aggregator212 may calculate the proportion the first and/or second time periods, individually and/or together as a single time period.
• Theexample transaction aggregator212 ofFIG. 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 (block810). 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.
• Theexample group identifier210 determines a set of device/user identifiers124 that are not associated with media impressions for the media of interest (block812). For example, thegroup identifier210 may use device/user identifiers124 associated with media impressions for media other than the media of interest, where the impression-transaction analyzer200 has not receivedimpression data130 indicating an impression of the media of interest occurring in association with the device/user identifier124. In some examples, thegroup identifier210 may use device/user identifiers124 and/orimpression data130 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 identifiers124 have not had a media impression of the media of interest.
• Theexample group identifier210 assigns the set of device/user identifiers124 to a “control group” corresponding to the selected publisher (block814). The control group represents device/user identifiers124 and/ormobile devices106 that have not been exposed to the media of interest.
• The example transaction requester206 requests transaction information for the device/user identifiers in the control group from the merchant database proprietor146 (block816). For example, thetransaction requester206 may send one ormore transaction requests152 including the device/user identifiers124 in the control group andproduct information154 for a product represented in the media of interest (e.g., the same product used in block808).
• Theexample transaction aggregator212 ofFIG. 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 (block818). 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 block810 (e.g., to facilitate comparison of control group and the exposed group during the same time periods).
• Based ontransaction information150 received from the merchant database proprietor146 (e.g., in response to the request of block814), theexample transaction aggregator212 ofFIG. 2 calculates a proportion of the control group for the selected publisher that purchased the product represented in the media of interest (block820). For example, thetransaction aggregator212 determines a number of the device/user identifiers124 in the control group for which transactions including the product were received from themerchant database proprietor146 in response to the request ofblock816. Theexample transaction aggregator212 may calculate the proportion for the first and/or second time periods, individually and/or together as a single time period.
• Theexample group identifier210 determines whether there are any additional publishers (block822). If there are additional publishers (block822), control returns to block802 to select another publisher.
• When there are no more publishers, control is passed to block824 ofFIG. 8B, where theexample effectiveness calculator214 ofFIG. 2 compares proportions of sales for each of the publishers to determine a publisher effectiveness by sales differences. Using the table300 and theexample publishers302,304 described above with reference toFIG. 3, theexample effectiveness calculator214 may compare the exposedgroup sales312 of Publisher A302 (e.g., 22,100 sales from 35,400 device/user identifiers, or 62.4% of the exposed group) to exposedgroup sales312 of Publisher B304 (e.g., 10,600 sales from 30,100 device/user identifiers, or 35.2% of the exposed group).
• Theexample effectiveness calculator214 ofFIG. 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 (block826). For example, using the example ofFIG. 3 described above, thesales lift314 forPublisher A302 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 forpublisher A302 divided by the percentage of sales in the control group for publisher A302 (62.4%/34.4%)). Similarly, thesales lift314 forPublisher B304 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 forpublisher B304 divided by the percentage of sales in the control group for publisher B304 (35.2%/32%)).
• Theexample effectiveness calculator214 compares the sales lift for each of theexample publishers302,304 to determine a publisher effectiveness by the sales lift difference (block828). For example, theeffectiveness calculator214 compares the sales lift314 of the Publisher A302 (e.g., 81.3%) to the sales lift314 of the Publisher B304 (e.g., 10%). In this example, theeffectiveness calculator214 may determine thatPublisher A302 is more effective thanPublisher B304 for the media of interest.Publisher A302 may be more effective thanPublisher B304 because, for example,Publisher A302 may reach an audience that is more likely to be influenced by the media of interest.
• Theexample effectiveness calculator214 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 (block830). For example, theeffectiveness calculator214 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, theexample effectiveness calculator214 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.
• Theexample instructions800 ofFIGS. 8A and 8B then end and, for example, control returns to a calling function or process such as the example instructions ofFIG. 6.
• FIG. 9 is a flow diagram representative of example machinereadable instructions900 which may be executed to implement the examplemerchant database proprietor146 ofFIG. 1 and/or the exampletransaction information provider500 ofFIG. 5 to associate device/user identifiers to merchant database proprietor accounts. Theexample instructions900 are described with reference to the exampletransaction information provider500 ofFIG. 5.
• Theexample user authenticator502 ofFIG. 5 receives a request from a mobile device (e.g.,merchant account information148 from themobile device106 ofFIG. 1, theapp116 ofFIG. 1) to access an account at the merchant database proprietor for performing a transaction (block902). For example, thetransaction information provider500 may enable authenticated users to view and/or purchase products from thetransaction information provider500 and/or through the systems of thetransaction information provider500.
• Theexample user authenticator502 determines whether the request is authenticated (block904). For example, theuser authenticator502 may use any past, present, or future authentication techniques to authenticate themerchant account information148 included in the request.
• If the request is authenticated (block904), the example account-identifier correlator504 ofFIG. 5 extracts a device/user identifier (e.g., the device/user identifier124 ofFIG. 1) from the request (block906). Example types of a device/user identifier124 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, thetransaction information provider500 agrees with theAME108 ahead of time on a same type of device/user identifier124 that is accessible to both entities.
• The example account-identifier correlator504 determines whether the extracted device/user identifier124 is stored in association with any accounts in theuser account database512 ofFIG. 5 (block908). For example, theuser account database512 stores associations of device/user identifiers124 and user accounts.
• When the extracted device/user identifier124 is not yet stored in association with any accounts in theuser account database512 ofFIG. 5 (block908), the example account-identifier correlator504 stores the extracted device/user identifier124 in association with the authenticated account (block910). For example, the account-identifier correlator504 stores the extracted device/user identifier124 in theuser account database512 and indicates that the extracted device/user identifier124 corresponds to the user account.
• After storing the device/user identifier124 (block910), if the extracted device/user identifier124 is associated with an accounts in theuser account database512 ofFIG. 5 (block908), or if the request to access the account is not authenticated (block904), theexample instructions900 ofFIG. 9 end.
• FIG. 10 is a flow diagram representative of example machinereadable instructions1000 which may be executed to implement the examplemerchant database proprietor146 ofFIG. 1 and/or the exampletransaction information provider500 ofFIG. 5 to provide transaction information. Theexample instructions1000 are described with reference to the exampletransaction information provider500 ofFIG. 5.
• The exampletransaction query generator508 ofFIG. 5 receives a transaction request including a device/user identifier124 (block1002). For example, thetransaction query generator508 may receive atransaction request152 from theAME108 ofFIG. 1.
• The exampletransaction query generator508 retrieves account information corresponding to the device/user identifier124 in the request152 (block1004). For example, thetransaction query generator508 may query theuser account database512 ofFIG. 5 using the device/user identifier124, and theuser account database512 determines whether the device/user identifier124 corresponds to a user account stored in theuser account database512.
• The exampletransaction query generator508 determines whether the device/user identifier124 is associated with an account identifier (block1006). For example, the device/user identifier124 may have been previously stored in association with an account identifier in theuser account database512 using theexample instructions900 ofFIG. 9.
• When the device/user identifier124 is associated with an account identifier (block1006), the exampletransaction query generator508 ofFIG. 5 retrieves transactions performed using the account corresponding to the account identifier (e.g., the account identifier determined in block1006) (block1008). For example, thetransaction query generator508 may query thetransaction database516 ofFIG. 5 using the account identifier to determine the transactions performed using the account identifier. Thetransaction database516 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.
• The exampletransaction query generator508 determines whether thetransaction request152 includes a time/date range (block1010). For example, thetransaction request152 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 (block1010), the exampletransaction query generator508 filters the retrieved transactions (e.g., the transactions from block1008) to remove transactions falling outside the time/date range specified in thetransaction request152.
• After filtering the retrieved transactions (block1012), or if thetransaction request152 does not include a time/date range (block1010), the exampletransaction query generator508 determines whether thetransaction request152 includes product information (e.g., theproduct information154 ofFIG. 1) (block1014).Example product information154 specifies a product of interest to the AME108 (e.g., a product that is represented in media corresponding to a media impression at a mobile device106).
• If the transaction request includes product information154 (block1014), the exampletransaction query generator508 retrieves a product identifier based on the product information154 (block1016). For example, thetransaction query generator508 may query theproduct database514 ofFIG. 5 to determine a product identifier that corresponds to theproduct information154 specified by theAME108 in therequest152. The exampletransaction query generator508 filters the retrieved transactions to remove transactions that do not include the product identifier (block1018).
• After filtering the retrieved transactions (block1018), or if thetransaction request152 does not include product information154 (block1014), theexample transaction reporter510 returns the transaction information150 (e.g., the transaction information remaining after filtering inblock1012 and/or block1018) to theAME108 in response to the transaction request152 (block1020). For example, thetransaction reporter510 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 theexample AME108 as a response to thetransaction request152.
• After returning the transaction information (block1020), or if the device/user identifier124 is not associated with an account identifier (block1006), theexample instructions1000 ofFIG. 10 end.
• FIG. 11 is a flow diagram representative of example machinereadable instructions1100 which may be executed to implement the examplemerchant database proprietor146 ofFIG. 1 and/or the exampletransaction information provider500 ofFIG. 5 to provide transaction information. In contrast to theexample instructions1000 ofFIG. 10 described above, theinstructions1100 ofFIG. 11 may be executed when, for example, atransaction request152 from theAME108 ofFIG. 1 does not include a device/user identifier124. Theexample instructions1100 are described with reference to the exampletransaction information provider500 ofFIG. 5.
• The exampletransaction query generator508 ofFIG. 5 receives a transaction request (e.g., atransaction request152 from the AME108) that includes product information (e.g., theproduct information154 ofFIG. 1) (block1102).
• The exampletransaction query generator508 retrieves a product identifier based on the product information154 (block1104). For example, thetransaction query generator508 may query theproduct database514 ofFIG. 5 to determine a product identifier that corresponds to theproduct information154 specified by theAME108 in therequest152.
• The exampletransaction query generator508 ofFIG. 5 retrieves transaction records that include the product identifier (e.g., the product retrieved in block1104) (block1106). For example, thetransaction query generator508 may query thetransaction database516 ofFIG. 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, thetransaction database516 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.
• The exampletransaction query generator508 selects a transaction from the retrieved transactions (block1108). The exampletransaction query generator508 looks up an account used to perform the selected transaction in an account database to identify a device/user identifier124 corresponding to the account (block1110). For example, thetransaction query generator508 may look up an account specified in the selected transaction record, which is used to query theuser account database512 to determine whether any device/user identifiers correspond to the account.
• Thetransaction query generator508 determines whether the account used to perform the selected transaction is associated with a device/user identifier124 (block1112). If the account used to perform the selected transaction is associated with a device/user identifier124 (block1112), the exampletransaction query generator508 determines whether thetransaction request152 includes a time/date range (block1114). For example, thetransaction request152 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 thetransaction request152 includes a time/date range (block1114), the exampletransaction query generator508 determines whether the time/date of the selected transaction falls within the time/date range (block1116). If the time/date of the selected transaction does not fall within the time/date range (block1116), or if the account used to perform the selected transaction is not associated with a device/user identifier124 (block1112), the exampletransaction query generator508 removes the selected transaction from the retrieved transactions (e.g., the transactions from block1106).
• After removing the selected transaction (block1118), or if 1) the account used to perform the selected transaction is associated with a device/user identifier124 (block1112) and 2) either A) the time/date of the selected transaction falls within the time/date range (block1116) or B) thetransaction request152 does not include a time/date range (block1114), the exampletransaction query generator508 determines whether there are additional retrieved transactions (block1120). If there are additional retrieved transactions (block1120), control returns to block1108 to select another transaction.
• When there are no more retrieved transactions (block1120), theexample transaction reporter510 returns the transaction information150 (e.g., the transaction information remaining after filtering in blocks1110-1118) to theexample AME108 in response to the transaction request152 (block1122). For example, thetransaction reporter510 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 theAME108. Theexample instructions1100 ofFIG. 11 then end.
• FIG. 12 is a block diagram of anexample processor platform1200 capable of executing the instructions ofFIGS. 6,7,8,9,10, and/or11 to implement theexample product checker202, theexample product database204, the example transaction requester206, the example impression/transaction matcher208, theexample group identifier210, theexample transaction aggregator212, theexample effectiveness calculator214, theexample user authenticator502, the example account-identifier correlator504, theexample transaction engine506, the exampletransaction query generator508, theexample transaction reporter510, the exampleuser account database512, theexample product database514, theexample transaction database516 and/or, more generally, the exampleaudience measurement entity108, the exampleaudience measurement server132, and/or the examplemerchant database proprietor146 ofFIG. 1, the example impression-transaction analyzer200 ofFIG. 2, and/or the exampletransaction information provider500 ofFIG. 5. Theprocessor platform1200 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™ tablet), an Internet appliance, or any other type of computing device.
• Theprocessor platform1200 of the illustrated example includes aprocessor1212. Theprocessor1212 of the illustrated example is hardware. For example, theprocessor1212 can be implemented by one or more integrated circuits, logic circuits, microprocessors or controllers from any desired family or manufacturer.
• Theprocessor1212 of the illustrated example includes a local memory1213 (e.g., a cache). Theprocessor1212 of the illustrated example is in communication with a main memory including avolatile memory1214 and anon-volatile memory1216 via abus1218. Thevolatile memory1214 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. Thenon-volatile memory1216 may be implemented by flash memory and/or any other desired type of memory device. Access to themain memory1214,1216 is controlled by a memory controller.
• Theprocessor platform1200 of the illustrated example also includes aninterface circuit1220. Theinterface circuit1220 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.
• In the illustrated example, one ormore input devices1222 are connected to theinterface circuit1220. The input device(s)1222 permit(s) a user to enter data and commands into theprocessor1212. 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.
• One ormore output devices1224 are also connected to theinterface circuit1220 of the illustrated example. Theoutput devices1224 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). Theinterface circuit1220 of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip or a graphics driver processor.
• Theinterface circuit1220 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 network1226 (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, coaxial cable, a cellular telephone system, etc.).
• Theprocessor platform1200 of the illustrated example also includes one or moremass storage devices1228 for storing software and/or data. Examples of suchmass storage devices1228 include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, RAID systems, and digital versatile disk (DVD) drives.
• Coded instructions1232 to implement the example machine readable instructions ofFIGS. 6,7,8,9,10, and/or11 may be stored in themass storage device1228, in thevolatile memory1214, in thenon-volatile memory1216, and/or on a removable tangible computer readable storage medium such as a CD or DVD.
• 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.

Claims (23)

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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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 inclaim 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)

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