Optimized advertising fulfillment

• US 20060253327A1
• Filed: 05/05/2006
• Published: 11/09/2006
• Est. Priority Date: 05/06/2005
• Status: Abandoned Application

• Current Assignee: RhythmOne LLC (Nexxen International Ltd.)
• Original Assignee: RhythmOne LLC (Nexxen International Ltd.)
• Inventors: Bilsborrow, Todd, Morris, James T., Shamim, Shaukat, Shroff, Rajat, Kohli, Ujjal
• Application Number:
  US11/418,766
• Publication Number:
  US 20060253327A1
• Time in Patent Office: Days
• US Class Current: 705/14.420
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0243 Comparative campaigns
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0257 User requested
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A system and a method to match advertisement requests with campaigns using targeting attributes, and campaigns are selected for fulfillment of the advertisement request according to a priority algorithm. The targeting uses end user information that is verifiable, and which the user has granted permission to use, improving the granularity and accuracy of the targeting data. The algorithm includes load balancing and campaign state evaluation on a per campaign, per user basis. The algorithm enables control over the frequency and number of exposures for a campaign, optimizing the advertising both from the perspective of the user and the advertiser.

Claims

1. A method for optimizing fulfillment of advertisement requests, comprising:

determining a plurality of reserved campaigns that satisfy parameters associated with an advertisement request;

prioritizing the plurality of reserved campaigns according to an algorithm, the algorithm comprising load balancing and campaign state evaluation with respect to an end user associated with the advertisement request; and

delivering a selected campaign.

2. The method of claim 1, wherein determining a plurality of reserved campaigns comprises determining all campaigns for which at least one advertisement request parameter is satisfied.

3. The method of claim 1, wherein the algorithm further comprises a value consideration.

4. The method of claim 1, wherein the algorithm further comprises at least one preset threshold.

5. The method of claim 1, wherein the algorithm further comprises at least one priority override.

6. The method of claim 1, wherein load balancing further comprises weighing campaign variety and value with respect to the end user.

7. The method of claim 1, wherein campaign state evaluation further comprises time since last advertisement and campaign progress with respect to at least one of the plurality of reserved campaigns.

8. The method of claim 1, wherein algorithm further comprises prioritization of advertising for which an end user has indicated an interest.

9. The method of claim 1, further comprising incrementing an impression count for the selected of the one or more campaigns.

10. The method of claim 9, wherein the impression count informs a forecasting model.

11. A computer program product for optimizing fulfillment of advertisement requests, the computer program product comprising:

a computer-readable medium; and

computer program code, coded on the medium, for;

determining a plurality of reserved campaigns that satisfy parameters associated with an advertisement request;

prioritizing the plurality of reserved campaigns according to an algorithm, the algorithm comprising load balancing and campaign state evaluation with respect to an end user associated with the advertisement request; and

delivering a selected campaign.

12. The computer program product of claim 11, wherein determining a plurality of reserved campaigns comprises determining all campaigns for which at least one advertisement request parameter is satisfied.

13. The computer program product of claim 11, wherein the algorithm further comprises a value consideration.

14. The computer program product of claim 11, wherein the algorithm further comprises at least one preset threshold.

15. The computer program product of claim 11, wherein the algorithm further comprises at least one priority override.

16. The computer program product of claim 11, further comprising computer program code, coded on the medium, for incrementing an impression count for the selected of the one or more campaigns.

17. The computer program product of claim 16, wherein the impression count informs a forecasting model.

18. A system for optimizing fulfillment of advertisement requests, comprising:

means for determining a plurality of reserved campaigns that satisfy parameters associated with an advertisement request;

means for prioritizing the plurality of reserved campaigns according to an algorithm, the algorithm comprising load balancing and campaign state evaluation with respect to an end user associated with the advertisement request; and

means for delivering a selected campaign.

19. The system of claim 18, wherein determining a plurality of reserved campaigns comprises determining all campaigns for which at least one advertisement request parameter is satisfied.

20. The system of claim 18, wherein the algorithm further comprises a value consideration.

21. The system of claim 18, wherein the algorithm further comprises at least one preset threshold.

22. The system of claim 18, wherein the algorithm further comprises at least one priority override.

23. The system of claim 18, further comprising means for incrementing an impression count for the selected of the one or more campaigns.

24. The system of claim 23, wherein the impression count informs a forecasting model.