The Citibank NA invention works as followsA disclosed example contains a database, communication interface and a processor. The database stores a log media impression to be used as a media ID for media that was accessed via the Internet. When a user does not wish to participate in third party tracking related to online activities, the communication interface will send a third-party device ID or a username identifying the user to a database proprietor. The database proprietor will then receive the third-party device identification or the user identifier. The processor will log the media impression and user information and create an impression report that corresponds to the media.
Background for Methods, apparatus and methods to collect user information for media impressions
Internet-based media delivery services allow Internet users to access different Internet media providers through their Internet service provider’s (ISP) connections. Internet-based media delivery services may be subscription services, may be pay-per-use services, and/or may be advertisement-supported services. Internet-based media delivery services may be accessed via personal computers, mobile devices, smart televisions, and/or dedicated over-the-top (OTT) devices (e.g., Roku media devices, AppleTV media devices, GoogleTV media devices, FireTV media devices, etc.).
When a user subscribes for an Internet-based Media Delivery Service, he/she registers with a server to gain access to media via the Internet.
Over the years, techniques for monitoring user access of Internet resources like webpages, advertisements, or other content have improved significantly. This monitoring used to be done through server logs. Particularly, websites that serve content via the Internet log the number and type of requests they receive for their content. It is not a good idea to base Internet usage research on server logs for several reasons. Server logs can be altered either directly or by zombie programs that repeatedly request content from the servers to increase their server log count. Second, sometimes content is retrieved once and cached locally. Then again, the cache can be accessed repeatedly from the local cache, without the server being involved in repeat viewings. These cached views cannot be tracked by server logs. Server logs can be susceptible to overcounting or undercounting errors.
The inventions disclosed at Blumenau, U.S. Pat. No. No. Blumenau, for example, disclosed a method that allows Internet content to be tracked to be tagged with beacon instruction. Monitoring instructions are specifically associated with the HTML (Hypertext markup Language) content to be tracked. Clients can request the content. The client is able to download both the content as well as the beacon instructions. The beacon instructions are executed when the content is accessed from a server, or from a cache.
The beacon instructions cause monitoring data indicating information about access to the content from the client to be sent to a monitoring agency. The monitoring entity is usually an audience measurement entity that didn’t provide the content to clients and who can provide accurate usage statistics (e.g., The Nielsen Company, LLC). The advantage is that the beaconing instructions are associated to the content and executed by client browsers whenever the content is accessed. This means that the audience measurement firm receives the monitoring information regardless of whether or not the client is a panelist.
It is however useful to link demographics or other user information with the monitoring information. The audience measurement company creates a panel of users that agree to share their demographic information and have their Internet browsing activities monitored. Individuals join the panel by providing detailed demographic information (e.g., gender and race, income, home address, occupation, etc.). The audience measurement company. The audience measurement company sets a device/user ID (a device/user identification) on the panelist’s device. This allows the audience measurement company to identify the panelist when the panelist views tagged content. It also sends monitoring information back to the audience measurement company. If the examples involve Internet-access apps or apps that accept cookie in connection to accessing Internet media (e.g. desktop web browsers accepting cookies, mobile browsers accepting cookies and/or other Internet-access apps and/or apps which accept cookies), the audience measuring entity places a cookie on the panelist’s device. Examples that involve Internet-access apps or apps that don’t accept cookies for accessing Internet media (e.g. mobile apps and/or other Internet-access apps and/or apps who do not accept cookie), the audience measurement entity sets/or uses a noncookie device/user ID (and/or any local data container such as HTML5 LDS) on the panelist device.
Most of the clients who provide monitoring information from the tag pages are not panelists, so it is necessary that statistical methods are used to infer demographic information using data collected for panelists. This information can then be applied to the larger user base providing data for the tags. The panel sizes of audience measurement entities are still small in comparison to the general user population. This presents a challenge in terms of increasing panel sizes and ensuring that panel demographic data is accurate.
The inventions described in Mainak and al., U.S. Pat. No. No. 8,370,489 is herein incorporated by reference in its entirety. It allows audience measurement entities (AMEs), to leverage existing databases of database proprietors to gather more extensive Internet usage data and demographic data. This can be done by expanding the beaconing process to include partnered database proprietors, and using such partners to act as interim data collectors. Mainak and colleagues have disclosed the inventions. This task is accomplished by creating an AME that responds to beacon requests from clients. (Who may not be members of an audience panel and thus may not be known to the audience member entity). The client is then redirected from the audience measurement entity towards a database proprietor such as a social media site partnered with an audience member entity. The redirection opens a communication session between client and database proprietor. To identify the client, the database proprietor (e.g. Facebook) can access any cookie that it has placed on the client. If the client is a subscriber to the database proprietor, the database proprietor logs an image in association with the demographic information associated with the client. The database proprietor then forwards the logged impressions on to the audience measurement company. If the client doesn’t correspond to a subscriber to the database proprietor, the database proprietor can redirect the client to an audience measurement entity or another database proprietor. In response to the redirection by the first database proprietor, the audience measurement entity might redirect the client to another database proprietor who is partnered with them. The second database proprietor might then attempt to identify and contact the client as described above. The process of redirecting the client to the database proprietor can be repeated until the client has been identified and the content exposed logged. If all database partners have not been contacted, the client will still be identified. All redirections occur automatically. The client’s user is not aware of them and may not be involved in any of the communication sessions.
Periodically or aperiodically the database owners of partnered databases provide their logs, as well as demographic information, to the audience measurement entity. This then compiles the data into statistical reports that accurately identify the demographics of those who have accessed the tagged media. The identification of clients is done using huge databases that include many users, far beyond what is available in a traditional audience measurement panel. This makes the data extremely reliable, accurate, detailed, and reliable.
The audience measurement entity (e.g., the client’s request for beacon instructions) is the first leg in the data collection process. This allows the audience measurement entity to hide the source of media access from the database proprietors. It also protects the privacy of media sources and the identity of media users. However, it does not compromise the database proprietors’ ability to log impressions. Cookies are also used to identify device/users. The Internet security cookie protocols can be complied with as the only servers that have access to a cookie are those associated with the Internet domain (e.g. Facebook.com).
Examples disclosed by Mainak et. al. (U.S. Pat. No. No. You can find it on the Internet. These disclosed examples allow for more accurate correlation of Internet advertising exposure to demographics. They also effectively expand panel sizes and compositions beyond those who are part of the audience measurement entity or a ratings entity. These extensions leverage the media tags capabilities of the ratings entity as well as the use of other databases, such social media and Google, to create a large, demographically accurate panel that allows for reliable, accurate measurements of exposures to Internet-based media such as programming and advertising.
The inventions disclosed by Burbank et al. U.S. Pat. No. No. Burbank et al. This goal was achieved despite numerous obstacles from audience measurement entities. For example, Burbank et al. The method of accessing the data of database proprietors without compromising subscribers’ privacy, panelists or proprietors of the tracked contents was disclosed. Burbank et al. Burbank et al. also revealed how to access this data due to technical restrictions imposed on mobile device app software platforms that don’t employ cookies.
Many Internet media providers, including Twitter, CNN and Hulu, want to track the media access habits of their audience members. These Internet media providers must offer an ‘opt-out’ option due to Internet privacy policies. Users who don’t want their Internet activities tracked by third-party tracking technology have options. Internet media providers may have implemented site-wide policies to prohibit third-party entities tracking users using techniques that transmit impression requests (e.g. beacon requests) from Internet media provider websites to third party impression collection servers. The Internet media providers make sure that everyone is protected, no matter if they choose to opt out. Third-party tracking will not be used to track users’ Internet activity on websites of Internet media providers. Third-party tracking policies such as those of Mainak and others make it difficult for people to follow the Mainak et. al. teachings. (U.S. Pat. No. No. 8.370,489) to collect impressions in order to obtain demographics and log impressions. These protections can be applied to all users regardless of their opt-out or not. However, this limits the Internet media providers’ ability to track the Internet activities of non-opt out users. This means that some users might not choose to opt out from third-party tracking. Therefore, even though an Internet media provider may track Internet activity of non-opt out users, its general policy to prohibit third-party monitoring does not permit third-party surveillance of non-opt out users.
As explained above, the advantage of leveraging third-party databases proprietors is that it allows for more extensive Internet usage and demographic data. This data can then be used to associate with media impressions tracked on devices. Although Internet media providers may have site-wide policies that prohibit third-party monitoring for all users and non-opt out users, they would still like to be able to track Internet activity associated with non-opt out users using third-party technology.
Examples herein allow Internet media providers to work with audience measurement entities or third-party database owners to be able measure Internet activity of non-opt out users. This allows impressions to be logged for media accessed through the Internet by non-opt out users, and to obtain demographics without violating privacy safeguards. The examples herein can be used to obtain demographics for non-opt-out users. However, this is possible without violating the corporate policies of Internet media providers or database proprietors. For example, there are policies that prohibit Internet universe resource locator calls from being made outside of the domains of Internet media provider and/or data base providers. There are also policies that prevent downloading software not provided by Internet media providers or database proprietors. This allows Internet media providers and/or data proprietors to have greater control over website performance, user experience, and software configuration management. For example, they can better control the software running on their websites, reduce or stop HTTP 404 Not Found error messages, and so forth. This will reduce the risk of malware being downloaded to Internet media providers and/or database owners via third-party sources.
The examples herein can be used for determining content impressions, advertisements impressions, content exposure and advertisement exposure. And/or any other media impressions or exposure using user data, which is distributed across multiple databases (e.g. different website owners, service provider, etc.). Internet. Examples disclosed herein allow for more accurate correlation of Internet exposure to user information. They also extend panel sizes beyond those who are part of the audience measurement entity and/or ratings entity panels to include persons who are registered in other Internet database proprietors such as the databases wireless service providers, mobile software/service provider databases, and social media sites (e.g. Facebook, Twitter and Google). ), and/or any Internet site, such as Yahoo! MSN, Apple iTunes or Experian. This extension leverages the media impression tracking capabilities and the use databases of non-AME entities such as social media to create a huge, demographically accurate panel that allows for reliable, accurate measurements of exposure to Internet content such as programming and advertising.
Traditionally audience measurement entities (also known as “ratings entities”) were used to determine the reach of advertising programs. Based on the demographic reach of registered panel members, advertising and media programming can be determined. An audience measurement entity is responsible for enrolling people who have consented to be monitored into a panel. The audience measurement entity collects demographic information about the people who are enrolled so that future correlations can be made between the advertisement/media exposure of those panelists, and other demographic markets. Contrary to traditional methods where audience measurement entities only rely on their panel members data to measure audience size, the example methods, apparatus and/or articles made herein allow audience measurement entities to share demographic information with entities that are based on user-registration models. A user registration model, as used herein is one in which users register to subscribe to the services of other entities by creating an account or providing demographic-related information. The sharing of demographic information with database proprietors registered users allows an audience measurement entity the ability to expand or supplement their panel data by using substantially reliable demographic information (e.g. database proprietors) thus increasing their coverage, accuracy, and/or completeness in their demographics-based audience measurement. This access allows the audience measurement entity monitor people who may not have otherwise joined an audience measurement panel. The audience measurement entity may collaborate with any entity that has a database that identifies the demographics of a group of people. These entities are sometimes called “database proprietors”. These entities include wireless service providers, mobile software/service provider, and social media sites (e.g. Facebook, Twitter, Google). ), and/or any additional Internet sites such as Yahoo! (MSN), Apple iTunes, Experian etc.
The examples disclosed herein can be used by Internet media providers and audience measurement entities (e.g., any entity that is interested in measuring or tracking audience exposures for advertisements, content and/or other media) in collaboration with any number of database owners, such as online service providers, in order to develop online media exposure metrics. These database proprietors/online service providers could be wireless service providers, mobile software/service provider, or social networking sites (e.g. Facebook, Twitter and MySpace). ), multiservice sites (e.g., Yahoo!, Google, Experian, etc. ), online retailer sites (e.g., Amazon.com, Buy.com, etc. ), and/or any other website(s) that keep user registration records.
In some cases, in order to increase the probability that measured audienceship and viewership are accurately attributed to correct demographics,” examples disclosed herein use user data located in the audience measurement entity?s records and/or user info located at one or several database proprietors that maintain records of accounts or profiles of users. Examples disclosed herein can be used to augment user information kept by ratings entities (e.g., The Nielsen Company of Schaumburg. Ill., United States of America), which collects media exposure measurement, demographics and/or user information.Click here to view the patent on Google Patents.