OPTIMIZING MONETIZATION WITH BRAND IMPACT SCORING

• US 20140095325A1
• Filed: 02/14/2013
• Published: 04/03/2014
• Est. Priority Date: 09/28/2012
• Status: Abandoned Application

• Current Assignee: Google Inc. (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Kim, Woo Jin, Beser, James, Mehta, Bhavesh, Bender, Brad
• Application Number:
  US13/767,235
• Publication Number:
  US 20140095325A1
• Time in Patent Office: Days
• US Class Current: 705/14.71
• CPC Class Codes: G06Q 30/0275 Auctions

Abstract

Systems and methods for generating a bid for use in a content auction include providing brand-related content to a client device for presentation with first-party content. The method also includes receiving activity data indicative of online activity regarding the brand and analyzing the activity data to determine a brand impact score. The method further includes generating a content auction bid using the brand impact score.

Claims

1. A method for generating a bid for use in a content auction comprising:

providing third-party content to a client device for presentation with first-party content, the third-party content being related to a brand;

receiving, at a processing circuit, activity data indicative of online activity regarding the brand, the activity data being indicative of an increase to search queries relating to the brand made at a search engine;

analyzing, by the processing circuit, the activity data to determine a brand impact score; and

determining, by the processing circuit, an amount for a content auction bid using the brand impact score.

2. The method of claim 1, further comprising:

using the brand impact score to predict an amount of brand impact, wherein the amount for the content auction bid is determined based in part on the predicted amount of brand impact.

3. The method of claim 1, further comprising:

using the brand impact score to generate a quality score for the first-party content, wherein the amount for the content auction bid is determined based in part on the quality score for the first-party content.

4. The method of claim 1, wherein the content auction bid corresponds to a cost per unit of brand impact, and wherein the amount for the content auction bid is determined in order to optimize an average cost per unit of brand impact.

5. The method of claim 4, wherein the average cost per unit of brand impact is optimized using a feedback loop.

6. The method of claim 1, wherein the activity data comprises data indicative of an increase to search queries relating to the brand.

7. The method of claim 1, further comprising:

using the brand impact score to generate a quality score for the brand-related content, wherein the amount for content auction bid is determined based in part on the quality score for the brand-related content.

8. The method of claim 1, wherein the brand-related content is an impression-based advertisement that is not interactive.

9. A system for generating a bid for use in a content auction comprising a processing circuit configured to:

provide third-party content to a client device for presentation with first-party content, the third-party content being related to a brand;

receive activity data indicative of online activity regarding the brand, the activity data being indicative of an increase to search queries relating to the brand made at a search engine;

analyze the activity data to determine a brand impact score; and

determine an amount for a content auction bid using the brand impact score.

10. The system of claim 9, wherein the processing circuit is further operable to use the brand impact score to predict an amount of brand impact, wherein the amount for the content auction bid is determined based in part on the predicted amount of brand impact.

11. The system of claim 9, wherein the processing circuit is further operable to use the brand impact score to generate a quality score for the first-party content, wherein the amount for the content auction bid is determined based in part on the quality score for the first-party content.

12. The system of claim 9, wherein the content auction bid corresponds to a cost per unit of brand impact, and wherein the amount for the content auction bid is determined in order to optimize an average cost per unit of brand impact.

13. The system of claim 12, wherein the average cost per unit of brand impact is optimized using a feedback loop.

14. The system of claim 9, wherein the activity data comprises data indicative of traffic to a webpage devoted to the brand.

15. The system of claim 9, wherein the processing circuit is further configured to use the brand impact score to generate a quality score for the first-party content, wherein the amount for the content auction bid is generated based in part on the quality score for the first-party content.

16. The system of claim 9, wherein the third-party content is an impression-based advertisement that is not interactive.

17. A computer-readable storage medium having machine instructions therein, the instructions being executable by a processor to cause the processor to perform operations, the operations comprising:

providing third-party content to a client device for presentation with first-party content;

receiving activity data indicative of online activity regarding the brand, the activity data being indicative of an increase to search queries relating to the brand made at a search engine;

analyzing the activity data to determine a brand impact score; and

determining an amount for a content auction bid using the brand impact score.

18. The computer-readable storage medium of claim 17, wherein the amount for the content auction bid corresponds to a cost per unit of brand impact, and wherein the amount for the content auction bid is determined using a feedback loop configured to optimize an average cost per unit of brand impact.

19. The computer-readable storage medium of claim 17, wherein the activity data comprises data indicative of traffic to a webpage devoted to the brand.

20. The computer-readable storage medium of claim 17, wherein the content auction bid corresponds to a cost per unit of brand impact, and wherein the content auction bid is determined such that an average cost per unit of brand impact is optimized.