Patent Grant
11792016
The present disclosure relates generally to monitoring media and, more particularly, to methods and apparatus to collect distributed user information for media impressions and search terms.
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 programs (e.g., television programs or radio programs, movies, DVDs, etc.) exposed to those panel members. In this manner, the audience measurement entity can determine exposure measures for different media content based on the collected media measurement data.
Techniques for monitoring user access to Internet resources such as web pages, advertisements and/or other content has evolved significantly over the years. Some known systems perform such monitoring primarily through server logs. In particular, entities serving content on the Internet can use known techniques to log the number of requests received for their content at their server.
Techniques for monitoring user access to Internet resources such as web pages, advertisements and/or other content has evolved significantly over the years. At one point in the past, such monitoring was done primarily through server logs. In particular, entities serving content on the Internet would log the number of requests received for their content 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 content from the server to increase the server log counts. Secondly, content 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 content. 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 content to be tracked is tagged with beacon instructions. In particular, monitoring instructions are associated with the HTML of the content to be tracked. When a client requests the content, both the content and the beacon instructions are downloaded to the client. The beacon instructions are, thus, executed whenever the content is accessed, be it from a server or from a cache.
The beacon instructions cause monitoring data reflecting information about the access to the content to be sent from the client that downloaded the content to a monitoring entity. Typically, the monitoring entity is an audience measurement entity that did not provide the content 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 content and executed by the client browser whenever the content is accessed, the monitoring information is provided to the audience measurement company irrespective of whether the client is a panelist of the audience measurement company.
It is useful, however, to link demographics and/or other user information to the monitoring information. To address this issue, the audience measurement company 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 audience measurement company. The audience measurement entity sets a cookie on the panelist computer that enables the audience measurement entity to identify the panelist whenever the panelist accesses tagged content and, thus, sends monitoring information to the audience measurement entity.
Since most of the clients providing monitoring information from the tagged pages are not panelists and, thus, are unknown to the audience measurement entity, 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 content. However, panel sizes of audience measurement entities 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 to large numbers of subscribers. In exchange for the provision of the service, the subscribers register with the proprietor. As part of this registration, the subscribers provide detailed demographic information. Examples of such database proprietors include social network providers such as Facebook, Myspace, etc. These database proprietors set cookies on the computers of their subscribers to enable the database proprietor to recognize the user when they visit their website.
The protocols of the Internet make cookies inaccessible outside of the domain (e.g., Internet domain, domain name, etc.) on which they were set. Thus, a cookie set in the Amazon.com domain is accessible to servers in the Amazon.com domain, but not to servers outside that domain. Therefore, although an audience measurement entity might find it advantageous to access the cookies set by the database proprietors, they are unable to do so. In addition, apps that run on mobile device platforms do not use cookies in the same way as web browsers. Although apps do present media that is worthy of impression tracking, prior techniques that use cookie-based approaches for tracking such media impressions are unusable in the app environment context.
In view of the foregoing, an audience measurement company would like to leverage the existing databases of database proprietors to collect more extensive Internet usage and demographic data and/or user data for associating with media impressions tracked on devices that execute apps that do not employ cookies which are more commonly used in web browsers. However, the audience measurement entity is faced with several problems in accomplishing this end. For example, a problem is presented as to how to access the data of the database proprietors without compromising the privacy of the subscribers, the panelists, or the proprietors of the tracked content. Another problem is how to access this data given the technical restrictions imposed by app software platforms of mobile devices that do not employ cookies.
Example methods, apparatus and/or articles of manufacture disclosed herein enable tracking media impressions for media presented by mobile device apps that execute on mobile devices, without needing to rely on cookies to track such media impressions. In this manner, an audience measurement entity (AME) can track media impressions on mobile devices on which apps that do not employ cookies have higher usage rates than web browsers that do employ cookies. Examples disclosed herein also protect privacies of users by encrypting identification information in such a way that personally-identifying information is not revealed to the AME. Examples disclosed herein accomplish this by using an application campaign rating (ACR) identifier (ID) that includes one or more encrypted device and/or user identifier(s) (i.e., device/user identifier(s)) retrieved from a mobile device. The one or more encrypted device/user identifier(s) can then be used to retrieve user information for a user of the mobile device by sending the one or more encrypted device/user identifier(s) to one or more corresponding database proprietors that store user information for its registered users. In the illustrated examples, to protect users' privacies, the AME does not have keys to decrypt the encrypted device/user identifiers, and each database proprietor has only its respective key(s) useable to decrypt only device/user identifier(s) pertaining to its services (e.g., wireless carrier services, social networking services, email services, mobile phone ecosystem app or media services, etc.). In this manner, personally-identifying information for particular services will not be revealed to the AME or to just any database proprietor, but only to the database proprietor that provides the particular service.
In examples disclosed herein, when an audience measurement entity receives an ACR ID including one or more encrypted device/user identifier(s), the audience measurement entity can request user information from one or more partnered database proprietors for the encrypted device/user identifier(s). In this manner, the partnered database proprietor(s) can provide user information to the audience measurement entity for the encrypted device/user identifier(s), and associate the user information with one or more media ID's of media presented by app(s) on one or more mobile device(s). Because the identification of users or client mobile devices is done with reference to enormous databases of users far beyond the quantity of persons present in a conventional audience measurement panel, the data developed from this process is extremely accurate, reliable and detailed. In some examples, by agreeing to participate in concerted audience measurement efforts, the partnered database proprietors are provided with audience user information and exposure information collected by other partnered database proprietors. In this manner, partnered database proprietors can supplement their own audience exposure metrics with information provided by other partnered database proprietors.
Example methods, apparatus, and articles of manufacture disclosed herein can be used to determine content impressions, advertisement impressions, content exposure, and/or advertisement exposure using user information, which is distributed across different databases (e.g., different website owners, service providers, etc.) on the Internet. Not only do example methods, apparatus, and articles of manufacture disclosed herein enable more accurate correlation of Internet media exposure to user information, but they also effectively extend panel sizes and compositions beyond persons participating in the panel of an audience measurement entity and/or a ratings entity to persons registered in other Internet databases such as the databases of 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. This extension effectively leverages the media impression tracking capabilities of the audience measurement entity and the use of databases of non-AME entities such as social media and other websites to create an enormous, demographically accurate panel that results in accurate, reliable measurements of exposures to Internet content such as advertising and/or programming.
Traditionally, audience measurement entities (also referred to herein as “ratings entities”) determine demographic reach for advertising and media programming based on registered panel members. That is, an audience measurement entity enrolls people that consent to being monitored into a panel. During enrollment, the audience measurement entity receives demographic 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 audience measurement entities 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 audience measurement entity to share demographic 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 demographic-related information about themselves. Sharing of demographic information associated with registered users of database proprietors enables an audience measurement entity to extend or supplement their panel data with substantially reliable demographics information from external sources (e.g., database proprietors), thus extending the coverage, accuracy, and/or completeness of their demographics-based audience measurements. Such access also enables the audience measurement entity to monitor persons who would not otherwise have joined an audience measurement panel. Any entity having a database identifying demographics of a set of individuals may cooperate with the audience measurement entity. 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.
Example methods, apparatus, and/or articles of manufacture disclosed herein may be implemented by an audience measurement entity (e.g., any entity interested in measuring or tracking audience exposures to advertisements, content, 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.
In some examples, to increase the likelihood that measured viewership is accurately attributed to the correct demographics, example methods, apparatus, and/or articles of manufacture disclosed herein use user information located in the audience measurement entity's records as well as user information located at one or more database proprietors (e.g., web service providers) that maintain records or profiles of users having accounts therewith. In this manner, example methods, apparatus, and/or articles of manufacture disclosed herein may be used to supplement user information maintained by a ratings entity (e.g., an audience measurement company such as The Nielsen Company of Schaumburg, Ill., United States of America, that collects media exposure measurements, demographics, and/or other user information) with user information from one or more different database proprietors (e.g., web service providers).
The use of demographic information from disparate data sources (e.g., high-quality demographic information from the panels of an audience measurement company and/or registered user data of web service providers) results in improved reporting effectiveness of metrics for both online and offline advertising campaigns. Example techniques disclosed herein use online registration data to identify demographics of users, and/or other user information, and use server impression counts, and/or other techniques to track quantities of impressions attributable to those users. Online web service providers such as 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.), etc. (collectively and individually referred to herein as online database proprietors) maintain detailed demographic information (e.g., age, gender, geographic location, race, income level, education level, religion, etc.) collected via user registration processes. An impression corresponds to a home or individual having been exposed to the corresponding media content and/or advertisement. Thus, an impression represents a home or an individual having been exposed to an advertisement or content or group of advertisements or content. 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).
In the illustrated example of
In the illustrated example, the app program 116 is a game entitled “Angry Bats” that presents media 118 received from a media publisher 120. The media 118 may be an advertisement, video, audio, text, a graphic, a web page, news, educational media, entertainment media, or any other type of media. In the illustrated example, a media ID 122 is provided in the media 118 to enable identifying the media 118 so that the AME 108 can credit the media 118 with media impressions when the media 118 is presented on the mobile device 106 or any other device that is monitored by the AME 108.
In the illustrated example, the AME 108 provides the data collector 112 to the app publisher 110 for packaging with the app program 116 in the app install package 114. In some examples, the app publisher 110 provides the data collector 112 as a program separate from the app program 116. In other examples, the app publisher 110 compiles or otherwise includes the data collector 112 in the app program 116 rather than installing the data collector 112 as a program separate from the app program 116. The data collector 112 of the illustrated example includes instructions (e.g., Java, java script, or any other computer language or script) that, when executed by the mobile device 106, cause the mobile device 106 to collect the media ID 122 of the media 118 presented by the app program 116 and/or the mobile device 106, and to collect one or more device/user identifier(s) 124 stored in the mobile device 106. The device/user identifier(s) 124 of the illustrated example include identifiers that can be used by corresponding ones of the partner database proprietors 104a-b to identify the user or users of the mobile device 106, and to locate user information 102a-b 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., advertising service identifiers, device usage analytics service identifiers, demographics collection service identifiers), etc. In some examples, fewer or more device/user identifier(s) 124 may be used. In addition, although only two partner database proprietors 104a-b are shown in
In some examples, the types of device/user identifiers 124 are different from device to device depending on the type of device, the manufacturer of the device, the software installed on the device, etc. For example, a mobile device having cellular 2G, 3G, and/or 4G capabilities will have an assigned IMEI number. However, a mobile device capable of Wi-Fi, but not having cellular communication capabilities, will not have an IMEI number. As such, one or more other parameter(s) of the Wi-Fi mobile device may be used as the device/user identifiers 124. Such other parameters may include, for example, a MAC address, a login ID, or any other identifier or information available to the Wi-Fi capable device and that is not specific to cellular communications.
By being able to select or access multiple different types of device/user identifiers 124, the AME 108 increases the opportunities for collecting corresponding user information. For example, the AME 108 is not tied to requesting user information from a single source (e.g., only one of the partner database proprietors 104a-b). Instead, the AME 108 can leverage relationships with multiple partner database proprietors (e.g., the partner database proprietors 104a-b). If one or some partner database proprietors are unable or become unwilling to share user data, the AME 108 can request the user data from one or more other partner database proprietor(s).
In some examples, the mobile device 106 may not allow access to identification information stored in the mobile device 106. For such instances, the disclosed examples enable the AME 108 to store an AME-provided identifier (e.g., an identifier managed and tracked by the AME 108) in the mobile device 106 to track media impressions on the mobile device 106. For example, the AME 108 may provide instructions in the data collector 112 to set an AME-provided identifier in memory space accessible by and/or allocated to the app program 116, and the data collector 112 uses the identifier as a device/user identifier 124. In such examples, the AME-provided identifier set by the data collector 112 persists in the memory space even when the app program 116 and the data collector 112 are not running. In this manner, the same AME-provided identifier can remain associated with the mobile device 106 for extended durations. In some examples in which the data collector 112 sets an identifier in the mobile device 106, the AME 108 may recruit a user of the mobile device 106 as a panelist, and may store user information collected from the user during a panelist registration process and/or collected by monitoring user activities/behavior via the mobile device 106 and/or any other device used by the user and monitored by the AME 108. In this manner, the AME 108 can associate user information of the user (from panelist data stored by the AME 108) with media impressions attributed to the user on the mobile device 106.
In the illustrated example, the data collector 112 sends the media ID 122 and the one or more device/user identifier(s) 124 as collected data 126 to the app publisher 110. Alternatively, the data collector 112 may be configured to send the collected data 126 to another collection entity (other than the app publisher 110) that has been contracted by the AME 108 or is partnered with the AME 108 to collect media ID's (e.g., the media ID 122) and device/user identifiers (e.g., the device/user identifier(s) 124) from mobile devices (e.g., the mobile device 106). In the illustrated example, the app publisher 110 (or a collection entity) generates an ACR ID 128 that includes the device/user identifier(s) 124, and the app publisher (or a collection entity) sends the media ID 122 and the ACR ID 128 as impression data 130 to a server 132 at the AME 108. The impression data 130 of the illustrated example may include one media ID 122 and one ACR ID 128 to report a single impression of the media 118, or it may include numerous media ID's and ACR ID's based on numerous instances of collected data (e.g., the collected data 126) received from the mobile device 106 and/or other mobile devices to report multiple impressions of media. In the illustrated example, the server 130 of the illustrated example stores the impression data 130 in an AME media impressions store 134 (e.g., a database or other data structure). Subsequently, the AME 108 sends the device/user identifier(s) 124 from the ACR ID 128 to corresponding partner database proprietors (e.g., the partner database proprietors 104a-b) to receive user information (e.g., the user information 102a-b) corresponding to the device/user identifier(s) 124 from the partner database proprietors so that the AME 108 can associate the user information with corresponding media impressions of media (e.g., the media 118) presented at mobile devices (e.g., the mobile device 106).
Although the above description describes the app publisher 110 (or other collection entity) as generating the ACR ID 128, in other examples, the data collector 112 at the mobile device 106 generates the ACR ID 128 that includes the device/user identifier(s) 124. In such examples, the data collector 112 sends the ACR ID 128 to the app publisher 110 (or other collection entity) in the collected data 126.
In the illustrated example, to protect the privacy of the user of the mobile device 106, the device/user identifier(s) 124 is/are encrypted before sending it/them to the AME 108 in the ACR ID 128. In the illustrated examples, the encryption process is performed so that neither the app publisher (110) (or other collection entity) nor the AME 108, or any other intermediate entity, can access the device/user identifier(s) 124 before they are sent to corresponding partner database proprietors (e.g., the partner database proprietors 104a-b). To encrypt the device/user identifier(s) 124, each partner database proprietor (e.g., the partner database proprietors 104a-b) for which identification information can be retrieved from the mobile device 106 is provided with one or more encryption keys specific to that partner database proprietor. In this manner, each partner database proprietor has a different set of keys so that each partner database proprietor can only recover one or more of the device/user identifier(s) 124 that pertain(s) to it. For example, a wireless service carrier can only retrieve an IMEI or MEID number, a social network site can only retrieve a login username corresponding to its social network services, etc. Copies of the one or more encryption keys can be provided to the app publisher 110 in an encryption algorithm (e.g., an SSH-1 encryption algorithm). In the illustrated example, the AME 108 provides the encryption algorithm and the encryption keys to the app publisher 110 as an encryption software package or bundle (e.g., an encryptor 202 of
In the illustrated examples, the encryption algorithm is also provided with partner database proprietor identifiers along with corresponding ones of the encryption keys for each of the partner database proprietors (e.g., the partner database proprietors 104a-b). When encrypting the device/user identifier(s) 124, the encryption algorithm can append, prepend, concatenate, or otherwise associate corresponding partner database proprietor identifiers to or with the encrypted device/user identifier(s) (e.g., encrypted device/user identifier(s) 208a-b of
In some examples, the app publisher 110 can run the encryption software at one of its servers or computers that receives the collected data 126 from the mobile device 106. In such examples, the media ID 122 and the device/user identifier(s) 124 are sent by the mobile device 106 as the collected data 126 via a secure connection between the encryption software running at the app publisher 110 and the mobile device 106. In this manner, the device/user identifier(s) 124 is/are not intercepted by the app publisher 110 before they are encrypted using the encryption keys corresponding to the different database proprietors.
In other examples, the encryption software to encrypt the device/user identifier(s) 124 is provided in the data collector 112 so that the data collector 112 can encrypt the device/user identifier(s) 124 at the mobile device 106 before sending encrypted device/user identifier(s) to the app publisher 110 (or other collection entity). In some examples in which the data collector 112 encrypts the device/user identifier(s) 124, the data collector 112 also encodes the encrypted device/user identifier(s) into an ACR ID (e.g., the ACR ID 128). In such examples, the data collector 112 sends the ACR ID 128 and the media ID 122 to the app publisher 110 (or other collection entity) in the collected data 126.
After the AME 108 receives the ACR ID 128 including the device/user identifier(s) 124 in encrypted format, the AME 108 sends encrypted device/user identifier logs 136a-b to corresponding partner database proprietors (e.g., the partner database proprietors 104a-b). In the illustrated example, each of the encrypted device/user identifier logs 136a-b may include a single encrypted device/user identifier, or it may include numerous aggregate encrypted device/user identifiers received over time from one or more mobile devices. After receiving the encrypted device/user identifier logs 136a-b, each of the partner database proprietors 104a-b decrypts its respective encrypted device/user identifiers using its copy(ies) of the encryption key(s). The partner database proprietors 104a-b then look up their users corresponding to the decrypted device/user identifiers, and collect corresponding user information 102a-b for those users for sending to the AME 108. For example, if the partner database proprietor 104a is a wireless service provider, the encrypted device/user identifier log 136a includes IMEI numbers, and the wireless service provider accesses its subscriber records to find users having IMEI numbers matching the IMEI numbers received in the encrypted device/user identifier log 136a. When the users are identified, the wireless service provider copies the users' user information to the user information 102a for delivery to the AME 108.
In the illustrated example of
In the illustrated example, the app publisher 110 matches the device/user identifier(s) 124 from the collected data 902 to the device/user identifier(s) 124 from the collected data 126 to determine that the media ID 122 corresponds to media (e.g., the media 118) presented on the mobile device 106 associated with the device/user identifier(s) 124. The app publisher 110 of the illustrated example also generates an ACR ID 128 based on the device/user identifier(s) 124 as disclosed herein. The app publisher 110 then sends the impression data 130, including the media ID 122 and the associated ACR ID 128, to the AME 108. The AME 108 can then send the encrypted device/user identifier logs 136a-b to the partner database proprietors 104a-b to request the user information 102a-b as described above in connection with
In the illustrated example of
Although the media publisher 120 is shown separate from the app publisher 110 in
In some examples, the media publisher 120 operates as a third-party media publisher relative to other traditional media publishers. In such examples, the media publisher 120 receives media from media providers and/or other traditional media publishers for publishing to electronic devices (e.g., the mobile device 106) while tracking media impressions of the published media (e.g., the media 118) and/or identities of devices to which media is published. That is, in addition to performing traditional media publisher services of publishing media to electronic devices, the media publisher 120 of the illustrated example additionally collects media impression tracking information as discussed above in connection with
In addition to associating user information (e.g., the user information 102a-b) with media IDs (e.g., the media ID 122) of published media, examples disclosed herein may additionally or alternatively be used to associate user information with other types of information collected from mobile devices representative of user interests and/or user behaviors. For example, techniques disclosed herein may also be used to monitor search terms provided by users at mobile devices, and associating those search terms with user information of users that provide the search terms. Example search terms may be provided via apps downloaded and installed on mobile devices, for searching information on the Internet and/or products at stores, websites, etc. For example, a search term may cause a search to be performed for information on the Internet, a search to be performed for a product, a search of a website to be performed, or a search for a website to be performed. Example systems that may be used to monitor search terms are described below in connection with
In the illustrated example of
When a user provides the search term(s) 1210 in the search field 1208, the data collector 1206 sends the search term(s) 1210, and the device/user identifier(s) 124 to the app publisher 110 as collected data 1214. The app publisher 110 can then generate the ACR ID 128 based on the device/user identifier(s) 124 using example techniques disclosed herein, and send the search term(s) 1210 and the ACR ID 128 to the AME 108 as user-interest data 1216. In other examples, the data collector 1206 may be configured to send the search term(s) 1210 and the ACR ID 128 (or the device/user identifier(s) 124) as the user-interest data 1216 directly to the AME 108. The AME 108 can then send the encrypted device/user identifier logs 136a-b to the partner database proprietors 104a-b to request the user information 102a-b as described above in connection with
In the illustrated example of
In the illustrated example, the app publisher 110 matches the device/user identifier(s) 124 from the collected data 1302 to the device/user identifier(s) 124 from the collected data 126 to determine that the search term(s) 1210 correspond to a search provided for the mobile device 106 associated with the device/user identifier(s) 124. The app publisher 110 of the illustrated example also generates an ACR ID 128 based on the device/user identifier(s) 124 as disclosed herein. The app publisher 110 then sends the user-interest data 1216, including the search term(s) 1210 and the associated ACR ID 128, to the AME 108. The AME 108 can then send the encrypted device/user identifier logs 136a-b to the partner database proprietors 104a-b to request the user information 102a-b as described above in connection with
In the illustrated example of
Although the search provider 1212 is shown separate from the app publisher 110 in
The example apparatus 200 may be entirely or partially implemented at the mobile device 106 (
In other examples, both of the encryptor 202 and the encoder 204 are implemented at the app publisher 110 (or other collection entity), at the media publisher 120, and/or at the search provider 1212. In such other examples, the app publisher 110 (or other collection entity), the media publisher 120, and/or the search provider 1212 receive(s) the device/user identifier(s) 124 from the mobile device 106. The app publisher 110 (or other collection entity), the media publisher 120, and/or the search provider 1212 generate(s) the ACR ID 128 to include the encrypted device/user identifier(s) 208a-i. The app publisher 110 (or other collection entity), the media publisher 120, and/or the search provider 1212 can then send the ACR ID 128 to the AME 108 along with the media ID 122 (e.g., as the impression data 130 of
While example manners of implementing the apparatus 200 and the apparatus 300 have been illustrated in
As mentioned above, example processes and/or operations of
Initially, the data collector 112 (
In some examples in which the encryptor 202 of
Initially, the media publisher 120 receives the device/user identifier(s) 124 (block 1102) from, for example, the data collector 912 of
When the media publisher 120 determines at block 1104 that it should serve media (e.g., the media 118), the media publisher 120 retrieves the media ID 122 from the media 118 to be served (block 1106). The media publisher 120 serves the media 118 (block 1108). For example, the media publisher 120 may use one or more of the device/user identifier(s) 124 received at block 1102 to identify the mobile device 106 as a receiving device of the served media 118. The media publisher 120 locates the media ID 122 and the device/user identifier(s) 124 in a message (block 1110). For example, in the example system 900 of
Initially, the search provider 1212 receives the device/user identifier(s) 124 (block 1502) from, for example, the data collector 1312 of
Initially, the encryptor 202 (
Initially, the server 132 receives the ACR ID 128 and the associated media ID 122, and/or the search term(s) 1210 (block 702). For example, the server 132 may receive the ACR ID 128 and the media ID 122 in the impression data 130 from the app publisher 110, from the media publisher 120, and/or from the mobile device 106 of
The processor 812 includes a local memory 813 (e.g., a cache) and is in communication with a main memory including a volatile memory 814 and a non-volatile memory 816 via a bus 818. The volatile memory 814 may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/or any other type of random access memory device. The non-volatile memory 816 may be implemented by flash memory and/or any other desired type of memory device. Access to the main memory 814, 816 is controlled by a memory controller.
The computer 800 also includes an interface circuit 820. The interface circuit 820 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.
One or more input devices 822 are connected to the interface circuit 820. The input device(s) 822 permit a user to enter data and commands into the processor 812. The input device(s) can be implemented by, for example, a keyboard, a mouse, a touchscreen, a track-pad, a trackball, isopoint and/or a voice recognition system.
One or more output devices 824 are also connected to the interface circuit 820. The output devices 824 can be implemented, for example, by display devices (e.g., a liquid crystal display, a cathode ray tube display (CRT), a printer and/or speakers). The interface circuit 820, thus, typically includes a graphics driver card.
The interface circuit 820 also includes a communication device such as a modem or network interface card to facilitate exchange of data with external computers via a network 826 (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, coaxial cable, a cellular telephone system, etc.).
The computer 800 also includes one or more mass storage devices 828 for storing software and data. Examples of such mass storage devices 828 include floppy disk drives, hard drive disks, compact disk drives and digital versatile disk (DVD) drives.
Coded instructions 832 representative of machine readable instructions of
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.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2013204953 | Apr 2013 | AU | national |
This patent arises from a continuation of U.S. patent application Ser. No. 17/018,872, filed Sep. 11, 2020, now U.S. Pat. No. 11,483,160, which is a continuation of U.S. patent application Ser. No. 16/045,440, filed Jul. 25, 2018, now U.S. Pat. No. 10,778,440, which is a continuation of U.S. patent application Ser. No. 15/449,331, filed Mar. 3, 2017, now U.S. Pat. No. 10,063,378, which is a continuation of U.S. patent application Ser. No. 14/959,990, filed Dec. 4, 2015, now U.S. Pat. No. 9,912,482, which is a continuation of U.S. patent application Ser. No. 14/562,319, filed Dec. 5, 2014, now U.S. Pat. No. 9,210,130, which is a continuation of U.S. patent application Ser. No. 14/127,414, filed Dec. 18, 2013, now U.S. Pat. No. 8,930,701, which is a national stage entry of International Patent Application No. PCT/US2013/057045, filed Aug. 28, 2013, which claims priority to Australian Patent Application No. 2013204953, filed on Apr. 12, 2013, U.S. Provisional Patent Application No. 61/697,597, filed on Sep. 6, 2012, and U.S. Provisional Patent Application No. 61/695,169, filed on Aug. 30, 2012. U.S. patent application Ser. No. 17/018,872, U.S. patent application Ser. No. 16/045,440, U.S. patent application Ser. No. 15/449,331, U.S. patent application Ser. No. 14/959,990, U.S. patent application Ser. No. 14/562,319, U.S. patent application Ser. No. 14/127,414, International Patent Application No. PCT/US2013/057045, Australian Patent Application No. 2013204953, U.S. Provisional Patent Application No. 61/697,597, and U.S. Provisional Patent Application No. 61/695,169 are all hereby incorporated herein by reference in their entireties.
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| Number | Date | Country | |
|---|---|---|---|
| 20230011482 A1 | Jan 2023 | US |
| Number | Date | Country | |
|---|---|---|---|
| 61697597 | Sep 2012 | US | |
| 61695169 | Aug 2012 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 17018872 | Sep 2020 | US |
| Child | 17947668 | US | |
| Parent | 16045440 | Jul 2018 | US |
| Child | 17018872 | US | |
| Parent | 15449331 | Mar 2017 | US |
| Child | 16045440 | US | |
| Parent | 14959990 | Dec 2015 | US |
| Child | 15449331 | US | |
| Parent | 14562319 | Dec 2014 | US |
| Child | 14959990 | US | |
| Parent | 14127414 | US | |
| Child | 14562319 | US |
