Automated recommendation of targeting criteria

• US 20080228571A1
• Filed: 03/16/2007
• Published: 09/18/2008
• Est. Priority Date: 03/16/2007
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: Koran, Joshua M.
• Application Number:
  US11/725,020
• Publication Number:
  US 20080228571A1
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

A system and method to facilitate automated recommendation of targeting criteria are described. Targeting data associated with an advertiser entity and one or more competitor entities of the advertiser entity within a specified industry is retrieved. A set of criteria to target advertisements to a plurality of consumers of the advertiser entity based on the retrieved targeting data is further determined. Finally, presentation of the advertisements to the targeted consumers is facilitated based on the selected set of criteria.

Claims

1. A method comprising:

retrieving targeting data associated with an advertiser entity and at least one competitor entity of said advertiser entity;

determining a set of criteria to target advertisements to a plurality of consumers based on said retrieved targeting data; and

facilitating presentation of said advertisements to said plurality of consumers based on said set of criteria.

2. The method according to claim 1, wherein said determining further comprises:

populating a matrix with said retrieved targeting data; and

optimizing said matrix data to select a plurality of sets of targeting criteria correlated with advertising goals associated with said advertiser entity.

3. The method according to claim 2, wherein said determining further comprises:

ranking said plurality of sets of targeting criteria based on a performance parameter identified from respective targeting data;

selecting a predetermined number of sets of targeting criteria in ranked order;

calculating an optimized parameter value for each selected set of targeting criteria; and

ranking said predetermined number of sets of targeting criteria and corresponding optimized parameter values to select said set of criteria having the highest optimized parameter value.

4. The method according to claim 1, wherein said facilitating further comprises:

presenting said set of criteria to said advertiser entity;

receiving instructions to present said advertisements based on said set of criteria; and

presenting said advertisements to said consumers based on said received instructions.

5. The method according to claim 1, wherein said facilitating further comprises:

receiving said selected set of criteria; and

automatically presenting said advertisements to said consumers based on said set of criteria.

6. The method according to claim 1, wherein information related to said at least one competitor entity is provided by said advertiser entity.

7. The method according to claim 1, wherein information related to said at least one competitor entity is generated automatically by search click stream analysis, wherein click events performed by consumers on multiple result links associated with a single search event are considered link competitors corresponding to said at least one competitor entity.

8. A computer readable medium containing executable instructions, which, when executed in a processing system, cause said processing system to perform a method comprising:

retrieving targeting data associated with an advertiser entity and at least one competitor entity of said advertiser entity;

determining a set of criteria to target advertisements to a plurality of consumers based on said retrieved targeting data; and

facilitating presentation of said advertisements to said plurality of consumers based on said set of criteria.

9. The computer readable medium according to claim 8, wherein said determining further comprises:

populating a matrix with said retrieved targeting data; and

optimizing said matrix data to select a plurality of sets of targeting criteria correlated with advertising goals associated with said advertiser entity.

10. The computer readable medium according to claim 9, wherein said determining further comprises:

ranking said plurality of sets of targeting criteria based on a performance parameter identified from respective targeting data;

selecting a predetermined number of sets of targeting criteria in ranked order;

calculating an optimized parameter value for each selected set of targeting criteria; and

ranking said predetermined number of sets of targeting criteria and corresponding optimized parameter values to select said set of criteria having the highest optimized parameter value.

11. The computer readable medium according to claim 8, wherein said facilitating further comprises:

presenting said set of criteria to said advertiser entity;

receiving instructions to present said advertisements based on said set of criteria; and

presenting said advertisements to said consumers based on said received instructions.

12. The computer readable medium according to claim 8, wherein said facilitating further comprises:

receiving said selected set of criteria; and

automatically presenting said advertisements to said consumers based on said set of criteria.

13. The computer readable medium according to claim 8, wherein information related to said at least one competitor entity is provided by said advertiser entity.

14. The computer readable medium according to claim 8, wherein information related to said at least one competitor entity is generated automatically by search click stream analysis, wherein click events performed by consumers on multiple result links associated with a single search event are considered link competitors corresponding to said at least one competitor entity.

15. A system comprising:

at least one storage module to store targeting data associated with an advertiser entity and at least one competitor entity of said advertiser entity; and

an optimization engine coupled to said at least one storage module to retrieve said targeting data, to determine a set of criteria to target advertisements to a plurality of consumers based on said retrieved targeting data, and to facilitate presentation of said advertisements to said plurality of consumers based on said set of criteria.

16. The system according to claim 15, wherein said optimization engine further populates a matrix with said retrieved targeting data, and optimizes said matrix data to select a plurality of sets of targeting criteria correlated with advertising goals associated with said advertiser entity.

17. The system according to claim 16, wherein said optimization engine further ranks said plurality of sets of targeting criteria based on a performance parameter identified from respective targeting data, selects a predetermined number of sets of targeting criteria in ranked order, calculates an optimized parameter value for each selected set of targeting criteria, and ranks said predetermined number of sets of targeting criteria and corresponding optimized parameter values to select said set of criteria having the highest optimized parameter value.

18. The system according to claim 15, wherein said optimization engine further presents said set of criteria to said advertiser entity, receives instructions to present said advertisements based on said set of criteria, and presents said advertisements to said consumers based on said received instructions.

19. The system according to claim 15, further comprising a targeting engine coupled to said optimization engine, said targeting engine to receive said selected set of criteria, and to present automatically said advertisements to said consumers based on said set of criteria.

20. The system according to claim 15, wherein information related to said at least one competitor entity is provided by said advertiser entity.

21. The system according to claim 15, wherein information related to said at least one competitor entity is generated automatically by search click stream analysis, wherein click events performed by consumers on multiple result links associated with a single search event are considered link competitors corresponding to said at least one competitor entity.