Systems and methods for measuring, targeting, verifying, and reporting advertising impressions

• US 20070198327A1
• Filed: 02/01/2007
• Published: 08/23/2007
• Est. Priority Date: 08/15/2003
• Status: Abandoned Application

• Current Assignee: comScore, Inc.
• Original Assignee: comScore, Inc.
• Inventors: Yazdani, Amir, Behnke, Chris
• Application Number:
  US11/701,959
• Publication Number:
  US 20070198327A1
• Time in Patent Office: Days
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Systems and methods are disclosed that enable an advertising or marketing company to identify with greater particularity the shows, movies, channels, entertainment commodity, commodity distribution channel, etc. in which they should place their ad for greatest effect, that is to attain the desired number of impressions in by the desired target audience. The present system and methods may also enable an advertising or marketing company to determine where to send their ads for greatest effect. By characterizing devices that receive or play entertainment commodities, an advertiser may be able to predict that the viewer of entertainment commodities and ads at that device would have particular characteristics that may be within or without the target audience. The systems and methods of the present disclosure enable an advertiser to characterize the viewer of the advertisement without collecting personal information or personally identifiable information from the view, the supplier of the entertainment commodity, or other source of personal information.

Claims

1. A method of reporting impressions of advertisements associated with distributed media assets, the method comprising:

collecting media asset perception data from at least one media asset distributor;

collecting advertisement placement data including information regarding relationships between at least one advertisement and one or more of the distributed media assets;

loading the collected media asset perception data and the collected advertisement placement data into at least one computerized database; and

generating advertisement impression data by correlating at least the collected media asset perception data and the collected advertisement placement data; and

producing at least one advertisement impression report based at least in part on the advertisement impression data.

2. The method of claim 1, wherein the collected media asset perception data includes at least one type of information regarding perceptions of one or more distributed media assets selected from times of the perceptions and methods of receiving the distributed media asset.

3. The method of claim 2, wherein the information regarding the time of the perception includes at least one type of information selected from dates of the perceptions, days of the week of the perceptions, times of day of the perceptions, and durations of the perceptions.

4. The method of claim 2, wherein the information regarding the method of receiving the distributed media asset includes at least one type of information selected from networks on which the media asset was perceived, system operators from whom the media asset was received, television markets in which the media asset was received, types of media receiver through which the media asset was perceived, operating modes of the media receiver through which the media asset was perceived, and unique media receiver codes adapted to distinguish and identify media receivers without revealing personally identifiable information.

5. The method of claim 1, wherein the method further comprises collecting environmental data on at least one audience environment factor, and wherein the at least one advertisement impression report is based at least in part on the environmental data.

6. The method of claim 5, wherein generating advertisement impression data includes correlating at least the collected media asset perception data, the collected advertisement placement data, and the collected environmental data.

7. A method of reporting impressions by a target audience of advertisements associated with distributed media assets, the method comprising:

collecting media asset perception data from at least one media asset distributor;

collecting advertisement placement data including information regarding relationships between at least one advertisement and one or more of the distributed media assets;

collecting at least one target audience profile from an advertiser identifying at least one characteristic of a target audience for one or more advertisements;

loading at least the collected media asset perception data, the collected advertisement placement data, and the at least one target audience profile into at least one inferential database;

generating one or more media asset profiles identifying at least one characteristic of a perceiving audience of the one or more distributed media assets and loading the one or more media asset profiles into the at least one inferential database;

generating target audience impression data with an inferential engine associated with the inferential database by correlating at least the collected media asset perception data, the collected advertisement placement data, the collected at least one target audience profile, and the one or more media asset profiles; and

producing at least one target audience impressions report based at least in part on the target audience impression data.

8. The method of claim 7, wherein the at least one characteristic of the perceiving audience identified by the one or more media asset profiles includes one or more characteristic selected from age group of the perceiving audience, education level of the perceiving audience, gender of the perceiving audience, income level of the perceiving audience, ethnicity of the perceiving audience, interests of the perceiving audience, home value of the perceiving audience, and geographic area of the perceiving audience.

9. The method of claim 8, wherein the one or more media asset profiles includes information about the distribution of one or more perceiving audience characteristics among the perceiving audience.

10. The method of claim 7, wherein the collected media asset perception data includes at least information regarding times of perceptions and durations of perceptions.

11. The method of claim 7, wherein generating one or more media asset profiles includes generating at least one manual media asset profile based at least in part on assumptions regarding characteristics of a perceiving audience, and generating, with the inferential engine associated with the inferential database, at least one automatic media asset profile based at least in part on the at least one manual media asset profile.

12. The method of claim 11, further comprising monitoring the media asset perception data over time, and updating, at least periodically, the at least one automatic media asset profile based at least in part on the collected media asset perception data.

13. The method of claim 12, further comprising assigning a confidence value to at least one perceiving audience characteristic in the one or more media asset profiles, and updating, at least periodically, at least one confidence value in the automatic media asset profiles based at least in part on the collected media asset perception data.

14. The method of claim 13, wherein the step of producing at least one target audience impressions report is further based at least in part on the confidence value assigned to the perceiving audience characteristics of the automatic media asset profiles.

15. A method of identifying one or more distributed media assets with which one or more advertisements may be associated to increase the number of impressions of the one or more advertisements by a target audience, the method comprising:

collecting media asset perception data from one or more media asset distributors and loading the media asset perception data into at least one inferential database;

generating one or more media asset profiles identifying at least one characteristic of a perceiving audience of the one or more distributed media assets and loading the one or more media asset profiles into the at least one inferential database;

collecting at least one target audience profile from an advertiser identifying at least one characteristic of a target audience for one or more advertisements and loading the at least one target audience profile into the at least one inferential database;

generating targeted advertising data with an inferential engine associated with the inferential database by identifying relationships in the at least one inferential database between the at least one target audience profile, the collected media asset perception data, and the one or more media asset profiles; and

producing at least one targeted advertising report based at least in part on the targeted advertising data identifying at least one targeted distributed media asset with which the advertiser may associate the one or more advertisements to increase the number of advertisement impressions by an audience having at least one characteristic at least substantially similar to those identified in the target audience profile.

16. The method of claim 15, wherein generating one or more media asset profiles includes generating at least one manual media asset profile based at least in part on assumptions regarding characteristics of a perceiving audience, and generating, with the inferential engine associated with the inferential database, at least one automatic media asset profile based at least in part on the at least one manual media asset profile.

17. The method of claim 16, further comprising monitoring the media asset perception data over time, and updating, at least periodically, the at least one automatic media asset profile based at least in part on the collected media asset perception data.

18. The method of claim 17, further comprising assigning a confidence value to at least one perceiving audience characteristic in the one or more media asset profiles, and updating, at least periodically, at least one confidence value in the automatic media asset profiles based at least in part on the collected media asset perception data.

19. The method of claim 18, wherein the step of generating targeted advertising data produces at least one list of targeted distributed media assets based on correlating the one or more media asset profiles, the confidence values of the automatic media asset profiles, and the at least one target audience profiles.

20. The method of claim 15, wherein the collected at least one target audience profiles includes significance data regarding the importance of one or more characteristics of the target audience to the advertiser, and wherein the step of generating targeted advertising data produces at least one list of targeted distribution media assets based on correlating the at least one characteristic in the one or more media asset profiles with the significance data of the at least one target audience profiles.

21. A method of identifying one or more media receivers to which one or more advertisements may be directed to increase the number of impressions of the one or more advertisements by a target audience, the method comprising:

collecting media asset perception data from one or more media asset distributors and loading the media asset perception data into at least one inferential database;

generating one or more media asset profiles identifying at least one characteristic of a perceiving audience of the one or more distributed media assets and loading the one or more media asset profiles into the at least one inferential database;

generating one or more media receiver profiles with an inferential engine associated with the at least one inferential database and loading the one or more media receiver profiles into the at least one inferential database, wherein the one or more media receiver profiles identify at least one characteristic of users of the one or more media receivers and are based at least in part on the collected media asset perception data and the one or more media asset profiles;

collecting at least one target audience profile from an advertiser identifying at least one characteristic of a target audience for one or more advertisements and loading the at least one target audience profile into the at least one inferential database;

generating receiver-targeted advertising data with the inferential engine based at least in part on relationships in the at least one inferential database between the at least one target audience profile and the one or more media receiver profiles; and

producing at least one targeted advertising report based at least in part on identifying at least one targeted media receiver to which the advertiser may direct the one or more advertisements to increase the number of advertisement impressions by an audience having at least one characteristic at least substantially similar to those identified in the target audience profile.

22. The method of claim 21, wherein the at least one characteristic of the perceiving audience identified by the one or more media asset profiles includes one or more characteristic selected from age group of the perceiving audience, education level of the perceiving audience, gender of the perceiving audience, income level of the perceiving audience, ethnicity of the perceiving audience, interests of the perceiving audience, home value of the perceiving audience, and geographic area of the perceiving audience.

23. The method of claim 22, wherein the one or more media asset profiles includes information about the distribution of one or more perceiving audience characteristics among the perceiving audience.

24. The method of claim 21, wherein the collected media asset perception data includes at least information regarding methods of receiving the distributed media asset, which information includes at least one type of information selected from networks on which the media asset was perceived, system operators from whom the media asset was received, television markets in which the media asset was received, types of media receiver through which the media asset was perceived, operating modes of the media receiver through which the media asset was perceived, and unique media receiver codes adapted to distinguish and identify the media receivers through which the media asset was perceived without revealing personally identifiable information.

25. The method of claim 21, wherein the collected media asset perception data includes at least information regarding times of perceptions and durations of perceptions.

26. The method of claim 21, wherein generating one or more media asset profiles includes generating at least one manual media asset profile based at least in part on assumptions regarding characteristics of a perceiving audience, and generating, with the inferential engine associated with the inferential database, at least one automatic media asset profile based at least in part on the at least one manual media asset profile.

27. The method of claim 26, further comprising monitoring the media asset perception data over time, and updating, at least periodically, the at least one automatic media asset profile based at least in part on the media asset perception data collected during monitoring.

28. The method of claim 26, further comprising monitoring the media asset perception data over time, and updating, at least periodically, the one or more media receiver profiles based at least in part on the media asset perception data collected during monitoring.

29. The method of claim 27, further comprising assigning a confidence value to at least one user characteristic in the one or more media receiver profiles, and updating, at least periodically, at least one confidence value in the one or more media receiver profiles based at least in part on the media asset perception data collected during monitoring.

30. The method of claim 29, wherein the step of producing at least one targeted audience advertising report is further based at least in part on the confidence value assigned to the user characteristics of the media receiver profiles.

31. The method of claim 21, wherein the collected at least one target audience profiles includes significance data regarding the importance of one or more characteristics of the target audience to the advertiser, and wherein the step of generating receiver-targeted advertising data produces at least one list of targeted media receivers based on correlating the at least one characteristic in the one or more media receiver profiles with the significance data of the at least one target audience profiles.

32. A method of verifying the effectiveness of a targeted advertising campaign associating one or more advertisements with one or more distributed media assets, the method comprising:

collecting media asset perception data from one or more media asset distributors and loading the media asset perception data into at least one inferential database;

generating one or more media asset profiles identifying at least one characteristic of a perceiving audience of the one or more distributed media assets and loading the one or more media asset profiles into the at least one inferential database;

collecting at least one target audience profile from an advertiser identifying at least one characteristic of a target audience for one or more advertisements and loading the at least one target audience profile into the at least one inferential database;

generating targeted advertising data with an inferential engine associated with the inferential database by identifying relationships in the at least one inferential database between the at least one target audience profile and the one or more media asset profiles;

producing at least one targeted advertising report based at least in part on the targeted advertising data identifying at least one targeted distributed media asset with which the advertiser may associate the one or more advertisements to increase the number of advertisement impressions by an audience having at least one characteristic at least substantially similar to those identified in the target audience profile

collecting advertisement placement data including information regarding relationships between at least one advertisement and one or more of the distributed media assets and loading the collected advertisement placement data into the at least one inferential database;

generating target audience impression data with the inferential engine by correlating at least the collected media asset perception data, the collected advertisement placement data, the collected at least one target audience profile, and the calculated media asset profiles; and

producing at least one target audience impressions performance report based at least in part on the target audience impression data and the targeted advertising report.