System and method for optimizing the selection and delivery of advertisements

• US 8,533,040 B2
• Filed: 04/09/2007
• Issued: 09/10/2013
• Est. Priority Date: 12/30/2005
• Status: Expired due to Fees

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Collins, Robert J.
• Primary Examiner(s): VANDERHORST, MARIA VICTORIA
• Application Number:
  US11/697,928
• Publication Number:
  US 20070179857A1
• Time in Patent Office: 2,346 Days
• Field of Search: 705/14, 705/14.41, 707/752
• US Class Current: 705/14.4
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0254 based on statistics

Abstract

The present invention is directed towards systems and methods for generating weights with which one or more advertisements comprising an advertisement group are selected for distribution. The method of the present invention comprises retrieving analytics data for the one or more advertisements comprising the advertisement group, and retrieving advertiser specified configuration data associated with the one or more advertisements comprising the advertisement group. A score is calculated for the one or more advertisements comprising the advertisement group, and weights are assigned to the one or more advertisements comprising the advertisement group based upon the scores and analytics data associated with the one or more advertisements.

Claims

1. A method for executing instructions stored in memory by one or more processors to generate weights with which one or more advertisements comprising an advertisement group are selected for distribution, the method comprising:

retrieving analytics data for a plurality of advertisements comprising an advertisement group, the analytics data including a plurality of advertising metrics and a frequency associated with the plurality of advertising metrics;

retrieving advertiser specified configuration data associated with the plurality of advertisements comprising the advertisement group, the advertiser specified configuration data includes a plurality of funnel values, each of the funnel values indicating a worth associated with at least one of the plurality of advertising metrics relative to at least one other of the plurality of advertising metrics, and one or more advertiser specified importance values of the plurality of advertising metrics;

calculating, via a computer, a score for each of the plurality of advertisements on the basis of the funnel values, the one or more advertiser specified importance values of the plurality of advertising metrics, and the analytics data, the score indicating a relative quality of a given one of the plurality of advertisements with respect to the plurality of advertisements comprising the advertisement group to which the given one of the plurality of advertisements belongs;

comparing the scores of the plurality of advertisements with the analytics data of the plurality of advertisements, wherein the analytics data includes data associated with the display of the advertisements;

determining a statistical significance in a difference between the scores and the analytics data;

assigning, via the computer, weights to the one or more plurality of advertisements based upon the comparison of the scores and the analytics data and based upon the determination of the statistical significance in the difference between the scores and the analytics data; and

utilizing the weights to select and distribute the one or more plurality of advertisements.

2. The method of claim 1, wherein retrieving analytics data comprises retrieving data indicating the frequency with which a given advertisement was displayed.

3. The method of claim 1, wherein retrieving analytics data comprises retrieving data indicating the frequency with a given advertisement was selected by one or more users of client devices.

4. The method of claim 1, wherein retrieving analytics data comprises retrieving data indicating the frequency with which a given advertisement resulted in a purchase of a product.

5. The method of claim 1, wherein a funnel value comprises an indication of a relative value of displaying one or more advertisements.

6. The method of claim 1, wherein a funnel value comprises an indication of a relative value of a user selection of one or more advertisements.

7. The method of claim 1, wherein a funnel value comprises an indication of a relative value of a user purchasing a product in response to one or more advertisements.

8. The method of claim 1, wherein a funnel value comprises an indication of a relative value of revenue generated from a user purchase of a product in response to one or more advertisements.

9. The method of claim 1, wherein retrieving advertiser specified configuration data comprises retrieving the one or more advertiser specified importance values.

10. The method of claim 9, wherein an advertiser specified importance value comprises an indication of a relative importance of one or more advertising metrics.

11. The method of claim 1, wherein calculating a score for a given advertisement comprises calculating a score through use of the analytics data associated with the advertisement and the advertiser specified configuration data.

12. The method of claim 1, wherein assigning a weight to a given advertisement comprises assigning a numerical value indicating a frequency with which the advertisement is to be distributed.

13. The method of claim 1, wherein assigning a weight to a given advertisement comprises assigning a numerical value indicating an amount by which analytics data associated with the advertisement is to be increased or decreased.

14. The method of claim 1, wherein determining a statistical significance in difference comprises determining through use of a Chi square test for statistical significance.

15. A system for generating weights with which one or more advertisements comprising an advertisement group are selected for distribution, the system comprising:

a computer processing and memory containing a scoring component, which when executed by the computer processor;

retrieves analytics data and advertiser specified configuration data associated with a plurality of advertisements comprising an advertisement group, the analytics data including a plurality of advertising metrics and a frequency associated with the plurality of advertising metrics, the advertiser specified configuration data includes a plurality of funnel values, each of the funnel values indicating a worth associated with at least one of the plurality of advertising metrics relative to at least one other of the plurality of advertising metrics, and one or more advertiser specified importance values of the plurality of advertising metrics; and

generates scores for each of the plurality of advertisements on the basis of the funnel values, the one or more advertiser specified importance values of the plurality of advertising metrics, and the analytics data, the scores indicating a relative quality of a given one of the plurality of advertisements with respect to the plurality of advertisements comprising the advertisement group to which the given one of the plurality of advertisements belongs;

the memory containing a statistical component, which when executed by the computer processor performs one or more comparisons between the scores of the plurality of advertisements and the analytics data of the plurality of advertisements, wherein the statistical component further determines a statistical significance in a difference between the scores associated with one or more advertisements and the analytics data;

the memory containing a weight component, which when executed by the computer processor assigns weights to the plurality of advertisements based upon the one or more performed comparisons of the scores and the analytics data and based upon the determination of the statistical significance in the difference between the scores and the analytics data; and

the memory containing a distribution component, which when executed by the computer processor utilizes the weights to select and distribute the plurality of advertisements.

16. The system of claim 15, wherein the scoring component is operative to retrieve analytics data indicating the frequency with which the one or more advertisements comprising the advertisement group were displayed.

17. The system of claim 15, wherein the scoring component is operative to retrieve analytics data indicating the frequency with which the one or more advertisements comprising the advertisement group were selected by one or more users of client devices.

18. The system of claim 15, wherein the scoring component is operative to retrieve analytics data indicating the frequency with which a purchase of a product was made in response to one or more advertisements comprising the advertisement group.

19. The system of claim 15, wherein the statistical component is operative to perform a comparison with respect to the scores associated with one or more advertisements and analytics data associated with the display of the one or more advertisements.

20. The system of claim 15, wherein a funnel value comprises an indication of a relative value of displaying one or more advertisements.

21. The system of claim 15, wherein a funnel value comprises an indication of a relative value of a user selection of one or more advertisements.

22. The system of claim 15, wherein a funnel value comprises an indication of a relative value of a user purchasing a product in response to one or more advertisements.

23. The system of claim 15, wherein a funnel value comprises an indication of a relative value of revenue generated from a user purchase of a product in response to one or more advertisements.

24. The system of claim 15, wherein an advertiser specified importance value comprises an indication of a relative importance of one or more advertising metrics.

25. The system of claim 15, wherein the statistical component is operative to utilize a Chi square test for determining a statistical significance in difference between the scores associated with one or more advertisements and analytics data associated with the display of the one or more advertisements.

26. The system of claim 15, wherein the weight component operative to assign weights to the one or more advertisements comprising the advertisement group based upon the statistical significance in difference between the scores associated with one or more advertisements and analytics data associated with the display of the one or more advertisements.

27. A non-transitory medium comprising instructions executable to:

retrieve analytics data for a plurality of advertisements comprising an advertisement group, the analytics data including a plurality of advertising metrics and a frequency associated with the plurality of advertising metrics;

retrieve advertiser specified configuration data associated with the plurality of advertisements comprising the advertisement group, the advertiser specified configuration data includes a plurality of funnel values, each of the funnel values indicating a worth associated with at least one of the plurality of advertising metrics relative to at least one other of the plurality of advertising metrics, and one or more advertiser specified importance values of the plurality of advertising metrics;

calculate a score for each of the plurality of advertisements on the basis of the funnel values, the one or more advertiser specified importance values of the plurality of advertising metrics, and the analytics data, the score indicating a relative quality of a given one of the plurality of advertisements with respect to the plurality of advertisements comprising the advertisement group to which the given one of the plurality of advertisements belongs;

compare the scores of the plurality of advertisements with the analytics data of the plurality of advertisements, wherein the analytics data includes data associated with the display of the advertisements;

determine a statistical significance in a difference between the scores and the analytics data;

assign weights to the one or more plurality of advertisements based upon the comparison of the scores and the analytics data and based upon the determination of the statistical significance in the difference between the scores and the analytics data; and

utilize the weights to select and distribute the one or more plurality of advertisements.

28. The non-transitory medium of claim 27, wherein the instructions are further executable to retrieve data indicating the frequency with which a given advertisement was displayed.

29. The non-transitory medium of claim 27, wherein the instructions are further executable to retrieve data indicating the frequency with a given advertisement was selected by one or more users of client devices.