WO2010093898A1

WO2010093898A1 - Identifying target information

Info

Publication number: WO2010093898A1
Application number: PCT/US2010/024068
Authority: WO
Inventors: Scott Spencer; Brad H. Bender; Wayne W. Lin
Original assignee: Google LLC
Current assignee: Google LLC
Priority date: 2009-02-13
Filing date: 2010-02-12
Publication date: 2010-08-19
Anticipated expiration: 2011-08-13

Abstract

Target information can be identified by receiving information indicating a first plurality of entities that meet a criterion for demonstrated interest in a second entity, and identifying a second plurality of entities in media planning information reflecting associations between entities and media content. The second plurality of entities is identified using the information. Target information for content distribution by the second entity is generated, and the target information indicates a plurality of media contents identified as being associated with the second plurality of entities.

Description

Identifying Target Information

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Application Serial No. 12/371,152, filed on February 13, 2009, entitled IDENTIFYING TARGET INFORMATION, the disclosure of which is incorporated herein by reference.

TECHNICAL FIELD

This document relates to information processing.

BACKGROUND

Content can be published using various forms of media. For example, internet content such as web page advertisements can target consumers with a specific lifestyle and demographic. Publishers can use systems such as software applications or other types of management tools to edit or control layout and appearance of published content.

An advertisement campaign can be evaluated in one or more ways. For example, the number of people who see or hear the campaign can be a measure of its success and various methods have been attempted to determine the relevant impact of the different types oaf advertisements. Another aspect is what results can be traced to the publication of the ad, such as whether users who were interested in the ad contacted the advertiser in any way, for example through a web site, and what were their activities on the site, such as whether the user placed an item in a shopping basket or actually purchased something.

SUMMARY

In some aspects, target information is identified by receiving information indicating a first plurality of entities that meet a criterion for demonstrated interest in a second entity, and identifying a second plurality of entities in media planning information reflecting associations between entities and media content. The second plurality of entities is identified using the information. Target information for content distribution by the second entity is generated, and the target information indicates a plurality of media contents identified as being associated with the second plurality of entities. The aspect can be practiced as a computer-implemented method or as instructions on a computer program product, for example.

Implementations can include any, all or none of the following features. The second plurality of entities can be identified as satisfying a similarity criterion to the first plurality of entities. Identifying the second plurality of entities can include abstracting the first plurality of entities to at least one interest category; and selecting the second plurality of entities from entities associated with the interest category. The plurality of media contents can be identified using a correlation relative to the first plurality of entities. The method can further include generating a ranking order of the plurality of media contents according to the correlation; and presenting the target information in a media planning tool that uses the media planning information, the plurality of media contents presented in the ranking order. The information can include a list of cookie identifiers obtained from a tool that tracks activities associated with content from the second entity. The method can further include identifying, using the information, at least one of the activities as being of interest in performing a content distribution campaign for the content from the second entity; and using the activity in identifying the plurality of media contents. The information can further identify media contents accessed by the first plurality of entities and at least a subset of the activities as having been performed regarding the media contents, and the media contents and the subset of the activities can be taken into account in identifying the plurality of media contents. The first plurality of entities can include users who have visited a page associated with the second entity; the content distribution can include publishing of at least one advertisement for the second entity; the media contents accessed by the first plurality of entities can include pages visited by the users; the subset of the activities having been performed regarding the media contents can include actions performed by the users on the pages; and the plurality of media contents indicated by the target information can include pages to be targeted by the advertisement. Identifying the second plurality of entities can include providing the information to a media planning tool that includes the media planning information, the media planning tool configured to perform planning operations for distribution campaigns based on the associations between the entities and the media content. The method can further include performing the content distribution at least twice, including (i) a first time before the information is received, wherein the information results at least in part from performing the content distribution the first time, and (ii) a second time after the target information has been generated, then directed toward at least the plurality of media contents. Performing the content distribution the second time can include a retargeting of the content distribution. The plurality of media contents can include at least one content type selected from the group consisting of: a top level domain of page contents; a cluster of sites identified in the media planning information; and a section of a site identified in the media planning information. In a second aspect, a graphical user interface for identifying target information includes a campaign creation area configured for a user to create a distribution campaign regarding content from a first entity. The graphical user interface includes a target information presentation area presenting target information that indicates a plurality of media contents identified as being associated with a first plurality of entities, the first plurality of entities being identified in media planning information that reflects associations between entities and media content and identified using information indicating a second plurality of entities that meet a criterion for demonstrated interest in the first entity. The graphical user interface includes a control for the user to cause distribution campaign created using the campaign creation area to be performed toward the plurality of media contents indicated by the target information. The graphical user interface can be implemented using a computer program product, for example.

Implementations can include any, all or none of the following features. The graphical user interface can include an integration of a tool that tracks activities associated with content from the second entity, and a media planning tool that includes the media planning information, the media planning tool configured to perform planning operations for distribution campaigns based on the associations between the entities and the media content. The graphical user interface can provide that the plurality of media contents indicated by the target information is a default for performing the distribution campaign. The graphical user interface can provide that the plurality of media contents indicated by the target information is a user-selectable option for performing the distribution campaign. The plurality of media contents can be identified using a correlation relative to the second plurality of entities, and the target information presentation can present the plurality of media contents in a ranking order generated according to the correlation.

Implementations can provide any, all or none of the following advantages. A more efficient content distribution can be provided. A content distributor can be given the opportunity to target or retarget a distribution based on tracked information that indicates activities relating to the distributor, such as by demonstrating an interest in the distributor and/or its goods and services.

The details of one or more embodiments are set forth in the accompanying drawings and the description below. Other features and advantages will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 shows an example system that can be used to identify target information.

FIG. 2 schematically shows an example process for managing a content distribution campaign.

FIG. 3 shows an example user interface that can be used to identify target information.

FIG. 4 is a block diagram of a computing system that can be used in connection with computer-implemented methods described in this document.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

FIG. 1 shows an example system 100 that can be used to identify target information. In examples below will be described how content distribution, such as an advertisement campaign, can be directed toward one or more target groups, and that analysis and processing can be performed to improve a target group using obtained data. For example, a campaign initially targeted toward particular media contents such as network pages can be retargeted based on information about interests of the advertiser's current customers or contacts. Such retargeting can lead to more efficient content distribution in some implementations.

In some implementations the system 100 can be considered an electronic distribution system that includes, and operates using, individual computer devices, such as the Internet. The system 100 includes a plurality of publisher systems that publish content, including publisher systems 102a and 102b. Content items can be distributed in the system 100 and providers of the content item can in some implementations compensate (e.g., pay) publishers to have their content distributed. The content published by the publisher systems can take any form, such as web or other internet pages, images, text, audio, video, text message updates sent to mobile devices, or any other digital media.

The system 100 can include one or more content provider systems 104a-b operated by a content provider such as an advertiser. In some implementations, the content provider can arrange to have contents (e.g., advertisement(s)) presented by the publisher(s) 104.

The system 100 here includes a content distributor system 106 for a distributor of contents such as advertisements. In some implementations, the content distributor system 106 manages the distribution of contents between multiple content provider systems 104 and multiple publisher systems 102, for example such that contents are served essentially on a real-time basis when they are needed. The systems 102, 104 and 106 can be connected through any kind of network 108, such as the Internet. In some implementations, other architectures can be used, including some that do not involve a client-server configuration.

The publisher systems 102a and 102b can process requests for contents received via the network 108. For example, such requests can be generated in one or more user systems 110a-b. In some implementations, the user system(s) 110 can include a browser or other client that generates requests for pages or other content from the publisher system(s) 102, such as one or more pages 112. The page(s) 112b can include any content such as web pages, electronic documents, news feeds, audio content, video content, or any other forms of electronic data, to name a few examples. Upon publication of the page(s) 112 or other publisher content to a user, one or more ads or other content from the content provider system 104 can be presented. In some implementations, a content server 115 can be used to serve content provided from the system(s) 104 to one or more of the user systems 110. For example, the content server can be operated by the content distributor and interact with the content provider system(s) 104 and/or the publisher system(s) 102 to serve the content, for example by serving ads. The content server 115 can be located in one or more components of the system 100 or elsewhere.

Ads or other content can include images, text, links and/or banners in a web page, commercials spliced into a video or audio stream, or any other form of content, to name just a few examples. In some implementations, the advertisement or other content presented by the publisher system(s) 104 can refer to, can be linked to, or can otherwise be associated with, one or more pages 114 in the content provider system 104. For example, the page 114 can serve as an e-business presence where the advertiser's commercial enterprise interacts with customers and others.

The content distributor system 106 here includes an activity tracking tool 116. In some implementations, the tool 116 can track one or more activities in the system 100. For example, the tool 116 can be configured to track views of the page(s) 112 by the user system(s) 110, whether products/services on the page 112 are selected (e.g., by being placed in a shopping basket), whether products/services are sold, and/or whether user registrations for more information are received. For these and/or other purposes, the tool 116 can be given access to one or more aspects of information available in the system 100, such as user transactions, page downloads, and/or interactions with page functions. Data relating to tracked activities can be stored by the tool 116 and be made available to one or more other components. In some implementations, the activity tracking tool can be operated by and/or reside on another component in the system 100, such as on the content provider system 104. For example, the activity tracking tool 116 can include, or be created based on, the Boomerang solution developed by the company DoubleClick.

The content distributor system 106 here includes an interest tracking tool 118. In some implementations, the interest tracking tool 118 can track one or more aspects regarding operators of the user systems 110, such as their interests, as demonstrated by viewing habits and/or information provided in response to questionnaires, etc. For example, the interest tracking tool can include or over time develop a record of identifiers categorized by interests, such that demographic searches can be performed and used (e.g., for targeting advertising or other content distribution). In some implementations, the interest tracking tool can be operated by and/or reside on another component in the system 100. For example, the interest tracking tool 118 can include, or be created based on, the Ad Planner solution developed by Google Inc.

In some implementations, the activity tracking tool 116 and the interest tracking tool 118 can be integrated in whole or in part. This can be performed on a common device or distributed over multiple devices; as another example, the integrated tools can appear as separate but joined components or as one inseparable unit. In some implementations, a graphical user interface can be provided that combines at least one respective feature from the tools 116 and 118 for a user. For example, the integration can include that a record of an activity history obtained using the activity tracking tool 116 and relating to a content provider can be provided to the interest tracking tool 118 and be used to generate target information for a content distribution campaign for the content provider. Such target information can indicate a plurality of media contents, such as multiple pages, as being potential targets for the content distribution campaign.

In some implementations, one or more of the user systems 110 can be configured to permit files or other information to be provided to the user system 110 in connection with activities being undertaken in the system 100. For example, one or more cookies 120 can be stored on the user system 110, such as in connection with downloading of the page 112 from the publisher system 102a and/or the page 114 from the content provider system 104. The cookie 120 can include information relating to the event that prompted the user system 110 to receive the cookie, such as data about the timing of the download and/or other pertinent information. In some implementations, the cookie 120 or other information accepted by the user system 110 can include a unique identifier so that the cookie 120 or other information can be identified, and distinguished from other cookies on the same user system 110 and/or on another user system 110.

FIG. 2 schematically shows an example process 200 for managing a content distribution campaign. In some implementations, the process 200 can be performed in a media distribution system. For example, some or all of system 100 (FIG. 1) can be used in the process 200.

In one aspect, the operations in the process 200 can proceed generally along a flow indicator 202. An example of such a proceeding is as follows. A user such as an advertiser or other content provider can employ a media planning tool 204 to plan a content distribution, such as an advertisement campaign. In some implementations, the media planning tool can be used to research and select a target group toward which the distribution is to be directed. For example, the user can select individual media contents such as pages on the Internet in the media planning tool 204 and associate them with the content to be distributed. In some implementations, information gathered by and/or available from the interest tracking tool 118 (FIG. 1) can be used. For example, the media planning tool 204 can include some or all portions of the interest tracking tool 118.

The user can employ a creative copy tool 206 to generate and/or gather the content to be distributed. For example, the tool 206 can provide one or more advertisements or other content to be provided in the distribution campaign. In some implementations, the tool 206 can include a media content editor and repository where media contents can be stored and accessed.

The process 200 can include a budget tool 208 to manage financial aspects of content distribution. In some implementations, costs of generating the media content, costs of distributing the content and/or costs for evaluating the distribution can be taken into account. For example, the tool 208 can track the respective costs associated with presenting content such as an advertisement on the page(s) 112 (FIG.

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The process 200 can include an execution tool 210 for activating the content distribution. In some implementations, the execution tool 210 can cause the contents such as advertisements to be presented, such as according to a presentation plan or upon request. For example, the tool 210 can coordinate serving of advertisements or other contents to one or more of the user systems 110 (e.g., for combination with other contents of the page 112) and/or the publisher system 102.

The process 200 can include a tracking tool 212 for tracking one or more aspects of information relevant to the content distribution campaign. In some implementations, the tracking tool 212 can track activities, such as page visits or purchases, relating to the content provider behind the campaign. For example, the tracking tool 116 (FIG. 1) can be implemented and used in the process 200.

The tracking tool 212 can generate an output based on the tracking. In some implementations, the output can be inform of a list or other collection that indicates entities 214 who have partaken in one or more of the activities. For example, the entities 214 can correspond to respective ones of the user systems 110 in implementations where the tracking tool 212 registers the identities of the individual systems. Assuming that each of the systems 110 is operated by at least one person, the entities 214 are here schematically illustrated as individuals.

A feedback loop 216 can be performed in the process 200. The feedback loop 216 can indicate information transfer in a direction generally opposite that of the flow indicator 202. In some implementations, the feedback loop 216 can indicate an integration between the tracking tool 212 (e.g., the activity tracking tool 116) and the media planning tool 204 (e.g., the interest tracking tool 118).

The media planning tool 204 contains and/or has access to media planning information. This information can be used for one or more purposes, such as to plan the scope or other specifics of a content distribution campaign. For example, the media planning information can indicate that certain entities (e.g., an individual or a computer device) are connected with particular media content, for example because that media content (e.g., a web page) has been downloaded by the individual or to the computer device. The media planning information can reflect associations between entities and media content on any of a number of bases including, but not limited to, the example downloading just mentioned. For example, tracking such associations can be considered an investigation of interests held by one or more entities.

Such interests can be useful information, for example if the content provider wishes to modify a distribution campaign. For example, assume that the content provider has identified the entities 214 in the process 200. The entities 214 have demonstrated an interest, for example by placing a product/service in a shopping cart on the content provider's page 114. Thus, the entities 214 in a sense are valuable to the content provider because they represent the demonstrated interest in the content provider. Now the content provider might want to improve the content distribution (e.g., an advertisement campaign) based on the identification of the entities 214.

One approach for the content provider can be to identify another group of entities 218. In some implementations, a similarity criterion can be established and the media planning tool 204 can identify the entities 218 as those who satisfy the similarity criterion with regard to the entities 214. Any kind of criterion that affects interest in the content provider can be used including, but not limited to, demographic criteria such as similarity in age, income, location, country, hobbies, or any other aspect of the entities 218. For example, based on the entities 214 the media planning tool 204 can find the entities 218 who have one or more aspects in common with the entities 214.

In some implementations, abstraction of the entities 214 can be performed. For example, multiple categories (e.g., interest categories) can be established, each of which reflects some trait or feature that can apply to an entity. Each of the entities 214 can be assigned to one or more categories, for example through sorting performed by a human or by an automated (such as keyword-based) process. One or more of the categories having been identified as applying to the entities 214, the media planning tool 204 in some implementations can look for other entities that have also been classified in the respective categories and assign the entity or entities to the entities 218. In some implementations, the content provider can use the entities 218 as the basis for a new or revised distribution campaign; for example by directing an advertisement campaign toward the entities 218.

In some implementations, media content 220 can be identified based on the entities 218. For example, the media planning tool 204 can identify the media content 220 based on stored media planning information that relates at least in part to the entities 218, such as tracked interests of one or more of the entities 218. In some implementations, the media content 220 can be identified as having a previously identified connection with one or more of the entities 218, such that the media content 220 includes a page that one or more of the entities has visited. In some implementations, the media planning tool 204 can determine a correlation between entities and media content based on the media planning information, and such correlation can be used in identifying the media content 220 from the entities 218. In some implementations, if the entities 218 are identified based on the entities 214, the media content 220 can be considered to have an association with the entities 214, for example such that the media contents 220 can be considered as correlating with the entities 214 to some extent.

In some implementations, the identification of the entities 214 can be part of an effort to define what activity or activities relative to the content provider to take into account. For example, the tracking tool 212 can be configured to track any of multiple different activities, and by the selection of the entities 214 it can be defined which of the activities are considered more or less relevant. By the feedback loop 216, moreover, the content provider can cause the media planning tool 204 to create a content distribution (e.g., a retargeted campaign or a new one) that targets entities and/or media content selected for the relevant activity or activities, such as relevant actions taken by interested entities.

The entities 218 and/or the media content 220 can be identified at a higher or smaller level of granularity . For example, the entities 218 can be identified relatively individually, such as by user name or cookie ID, or more generally, such as by category or a demographic indicator. As another example, the media contents 220 can be identified relatively individually, such as by individual contents (e.g., a page or site or a section of pages belonging to a common site), or more generally, such as by top level domain. Other characteristics can be used in identifying the entities 218 and/or the media content 220. In some implementation, the tracking tool 212 can identify the entities 214 as well as provide other information that can be useful in the feedback loop 216. For example, the entities 214 can be indicated by providing a list of cookie IDs corresponding to them, and also by identifying one or more sites (or other content) associated with the cookie IDs. As another example, the tracking tool 212 can provide a list of cookie IDs, respective pages visited using one or more of those cookie IDs and/or one or more activities undertaken using the cookie ID(s). Any or all of such example information can be used in targeting or retargeting a content distribution campaign. For example, a list of sites and/or activities can be expanded by the media planning tool to identify other sites/activities that may be relevant to the content distributor.

In some implementations, to protect the privacy of users, the tracking tool 212 and/or another component in the process 200 anonymizes data for users so that the stored data cannot be associated with the users. For example, each query can be associated with a unique 128-bit number that is not associated with any user. However, opt-in and/or opt-out procedures can be provided, and if the user opts-in for tracking of user history data, the process 200 can associate search queries, clicks and/or other user activities with a user identifier that is uniquely associated with the user. A user can grant permission to the tracking tool 212 to track the user's history so that historical data for the user's search sessions and other user data are tracked and associated with the user identifier. For example, at the user's option, a search engine can be configured to track only data approved by the user, such as only search queries and search result selections. The user can clear historical data associated with the user at any time, and can opt-out of such tracking at any time.

In another example, an identifier can also anonymously identify a device (e.g., a laptop or a mobile phone) from which the user activity originated. A device identifier can be, for example, a cookie or an Internet Protocol (IP) address. In some implementations, the identity of the user is protected by use of one or more anonymization processes. For example, the user history and login association, or device history and address association, can be anonymized by use of collision- resistant hashes that hash the identification data. Additional privacy protection techniques can also be used, such as the use of one or more encryption processes.

FIG. 3 shows an example user interface 300 that can be used to identify target information. In some implementations, the user interface 300 can be generated in the system 100, such as by a processor in the system 100 (e.g., in the content distributor system 106) that executes instructions in a computer-readable medium. In some implementations, the user interface 300 can be implemented on a tool that integrates at least activity tracking (such as by the tools 116 and/or 212) and interest tracking (such as by the tools 118 and/or 204). For example, a content provider such as an advertiser can employ the user interface 300 to create and implement a content distribution such as an advertisement campaign.

The user can select a research tab 302 to perform research on media planning information. For example, one or more characteristics of target entities and/or target media can be selected in an area 304. Media content that is available for the content provider to choose from can be presented in an area 306. For example, a content provider can choose one or more media contents (such as a site) to be a target for content distribution. The content distribution can be defined in another area of the user interface 300 after the user selects a medial plan control 308. In some implementations, the user interface 300 can be a front end for one or more of the components involved in the process 200 (FIG. 2). For example, the control 308 can allow the user to define contents for the distribution, establish and/or manage a budget for distributing the content and/or to manage execution of the campaign (such as by starting or stopping the campaign or defining a presentation schedule).

A target for a content distribution can be established by specifying target information accordingly. In some implementations, information from activity tracking (e.g., cookie IDs, sites and/or activities) can be used in defining the relevant target information, for example through the feedback loop 216 (FIG. 2). In the user interface 300, such information can be taken into account when the area 306 is presented. In some implementations, the media content 220 (FIG. 2) can be presented in the area 306 so that the user can choose from it when targeting the campaign. For example, those of the media contents 220 that correlate more strongly to the entities 214 can be indicated in the user interface 300, such as by placing them in a more conspicuous location in the area 306. In some implementations, a ranking algorithm can take into account correlation (such as between the entities 214 and the entities 218 and/or the media content 220) and present the media contents in a ranking order accordingly.

In some implementations, the user interface 300 can provide the user an option whether to take the tracking based information into account. For example, the user interface 306 can receive an input from the user determining whether the media contents in the area 306 should include the media contents 220 and/or, if the media content 220 is included in the area 306, whether the content should be treated different from other choices in any way (e.g., by different ranking). In some implementations, a default setting in the user interface 300 can be that information from the tracking tool 212 is taken into account when retargeting a content distribution.

FIG. 4 is a schematic diagram of a generic computer system 400. The system 400 can be used for the operations described in association with any of the computer- implement methods described previously, according to one implementation. The system 400 includes a processor 410, a memory 420, a storage device 430, and an input/output device 440. Each of the components 410, 420, 430, and 440 are interconnected using a system bus 450. The processor 410 is capable of processing instructions for execution within the system 400. In one implementation, the processor 410 is a single-threaded processor. In another implementation, the processor 410 is a multi-threaded processor. The processor 410 is capable of processing instructions stored in the memory 420 or on the storage device 430 to display graphical information for a user interface on the input/output device 440.

The memory 420 stores information within the system 400. In one implementation, the memory 420 is a computer-readable medium. In one implementation, the memory 420 is a volatile memory unit. In another implementation, the memory 420 is a non-volatile memory unit.

The storage device 430 is capable of providing mass storage for the system 400. In one implementation, the storage device 430 is a computer-readable medium. In various different implementations, the storage device 430 may be a floppy disk device, a hard disk device, an optical disk device, or a tape device.

The input/output device 440 provides input/output operations for the system 400. In one implementation, the input/output device 440 includes a keyboard and/or pointing device. In another implementation, the input/output device 440 includes a display unit for displaying graphical user interfaces.

The features described can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. The apparatus can be implemented in a computer program product tangibly embodied in an information carrier, e.g., in a machine -readable storage device or in a propagated signal, for execution by a programmable processor; and method steps can be performed by a programmable processor executing a program of instructions to perform functions of the described implementations by operating on input data and generating output. The described features can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

Suitable processors for the execution of a program of instructions include, by way of example, both general and special purpose microprocessors, and the sole processor or one of multiple processors of any kind of computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memories for storing instructions and data. Generally, a computer will also include, or be operatively coupled to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto -optical disks; and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non- volatile memory, including by way of example semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, ASICs (application- specific integrated circuits).

To provide for interaction with a user, the features can be implemented on a computer having a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer. The features can be implemented in a computer system that includes a back- end component, such as a data server, or that includes a middleware component, such as an application server or an Internet server, or that includes a front-end component, such as a client computer having a graphical user interface or an Internet browser, or any combination of them. The components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, e.g., a LAN, a WAN, and the computers and networks forming the Internet.

The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a network, such as the described one. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

A number of embodiments have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of this disclosure. Accordingly, other embodiments are within the scope of the following claims.

Claims

WHAT IS CLAIMED IS:

1. A computer-implemented method for identifying target information, the method comprising: receiving information indicating a first plurality of entities that meet a criterion for demonstrated interest in a second entity; identifying a second plurality of entities in media planning information reflecting associations between entities and media content, the second plurality of entities identified using the information; and generating target information for content distribution by the second entity, the target information indicating a plurality of media contents identified as being associated with the second plurality of entities.

2. The computer-implemented method of claim 1 , wherein the second plurality of entities is identified as satisfying a similarity criterion to the first plurality of entities.

3. The computer-implemented method of claim 2, wherein identifying the second plurality of entities comprises: abstracting the first plurality of entities to at least one interest category; and selecting the second plurality of entities from entities associated with the interest category.

4. The computer-implemented method of claim 2, wherein the plurality of media contents is identified using a correlation relative to the first plurality of entities.

5. The computer-implemented method of claim 4, further comprising: generating a ranking order of the plurality of media contents according to the correlation; and presenting the target information in a media planning tool that uses the media planning information, the plurality of media contents presented in the ranking order.

6. The computer-implemented method of claim 1 , wherein the information includes a list of cookie identifiers obtained from a tool that tracks activities associated with content from the second entity.

7. The computer-implemented method of claim 6, further comprising: identifying, using the information, at least one of the activities as being of interest in performing a content distribution campaign for the content from the second entity; and using the activity in identifying the plurality of media contents.

8. The computer-implemented method of claim 7, wherein the information further identifies media contents accessed by the first plurality of entities and at least a subset of the activities as having been performed regarding the media contents, and wherein the media contents and the subset of the activities are taken into account in identifying the plurality of media contents.

9. The computer-implemented method of claim 8, wherein: the first plurality of entities includes users who have visited a page associated with the second entity; the content distribution includes publishing of at least one advertisement for the second entity; the media contents accessed by the first plurality of entities includes pages visited by the users; the subset of the activities having been performed regarding the media contents includes actions performed by the users on the pages; and the plurality of media contents indicated by the target information includes pages to be targeted by the advertisement.

10. The computer-implemented method of claim 1 , wherein identifying the second plurality of entities comprises: providing the information to a media planning tool that includes the media planning information, the media planning tool configured to perform planning operations for distribution campaigns based on the associations between the entities and the media content.

11. The computer-implemented method of claim 10, further comprising: performing the content distribution at least twice, including (i) a first time before the information is received, wherein the information results at least in part from performing the content distribution the first time, and (ii) a second time after the target information has been generated, then directed toward at least the plurality of media contents.

12. The computer-implemented method of claim 11 , wherein performing the content distribution the second time comprises a retargeting of the content distribution.

13. The computer-implemented method of claim 1 , wherein the plurality of media contents includes at least one content type selected from the group consisting of: a top level domain of page contents; a cluster of sites identified in the media planning information; and a section of a site identified in the media planning information.

14. A computer program product tangibly embodied in a computer-readable storage medium and comprising instructions that when executed by a processor perform a method for identifying target information, the method comprising: receiving information indicating a first plurality of entities that meet a criterion for demonstrated interest in a second entity; identifying a second plurality of entities in media planning information reflecting associations between entities and media content, the second plurality of entities identified using the information; and generating target information for content distribution by the second entity, the target information indicating a plurality of media contents identified as being associated with the second plurality of entities.

15. A computer program product tangibly embodied in a computer-readable storage medium, the computer program product including instructions that, when executed, generate on a display device a graphical user interface for identifying target information, the graphical user interface comprising: a campaign creation area configured for a user to create a distribution campaign regarding content from a first entity; a target information presentation area presenting target information that indicates a plurality of media contents identified as being associated with a first plurality of entities, the first plurality of entities being identified in media planning information that reflects associations between entities and media content and identified using information indicating a second plurality of entities that meet a criterion for demonstrated interest in the first entity; and a control for the user to cause distribution campaign created using the campaign creation area to be performed toward the plurality of media contents indicated by the target information.

16. The computer program product of claim 15 , wherein the graphical user interface comprises an integration of a tool that tracks activities associated with content from the second entity, and a media planning tool that includes the media planning information, the media planning tool configured to perform planning operations for distribution campaigns based on the associations between the entities and the media content.

17. The computer program product of claim 15 , wherein the graphical user interface provides that the plurality of media contents indicated by the target information is a default for performing the distribution campaign.

18. The computer program product of claim 15 , wherein the graphical user interface provides that the plurality of media contents indicated by the target information is a user-selectable option for performing the distribution campaign.

19. The computer program product of claim 15 , wherein the plurality of media contents is identified using a correlation relative to the second plurality of entities, and wherein the target information presentation area presents the plurality of media contents in a ranking order generated according to the correlation.

20. A computer-implemented method for identifying target information, the method comprising: receiving information indicating a first plurality of entities; identifying a second plurality of entities in media planning information reflecting associations between entities and media content, the second plurality of entities identified using the information; and generating target information for content distribution, the target information indicating a plurality of media contents identified as being associated with the second plurality of entities.