System and process for identifying users for which non-competitive advertisements is relevant

• US 20090198554A1
• Filed: 02/01/2008
• Published: 08/06/2009
• Est. Priority Date: 02/01/2008
• Status: Abandoned Application

• Current Assignee: RichRelevance Incorporated
• Original Assignee: RichRelevance Incorporated
• Inventors: Ahuja, Sundeep, Selinger, David, Sunwoo, Albert, Osial, James, Kohn, Tyler, DeCourcey, Michael
• Application Number:
  US12/012,450
• Publication Number:
  US 20090198554A1
• Time in Patent Office: Days
• US Class Current: 705/14.53
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising

Abstract

A process for identifying a subset of users for which a non-competitive advertisement is relevant includes the steps of generating a plurality of user models including user-specific data, identifying a subset of the plurality of user models by applying an advertisement-specific selection model to identify users for which a specific advertisement is relevant and applying a non-competitive rule set to the identified user models to identify which user models are associated with one or more non-competitive originating retailers. An arrangement for the same includes memory for storing user-specific data and a controller that generates user models using the user-specific data, identifies a subset of the user models by applying an advertisement-specific selection model to the user models to identify users for which the specific advertisement is relevant and applies a non-competitive rule set to the identified subset of user models to identify which user models are associated with one or more non-competitive originating retailers.

Claims

1. A process for identifying a subset of users for which a non-competitive advertisement is relevant comprising the steps of:

generating a plurality of user models, each user model including user-specific data;

identifying a subset of the plurality of user models by applying an advertisement-specific selection model to the plurality of user models to identify users for which a specific advertisement is relevant; and

applying a non-competitive rule set to the identified subset of user models to identify which user models are associated with one or more non-competitive originating retailers.

2. The process of claim 1 wherein user-specific data includes data regarding purchases, product views, searches and user lists.

3. The process of claim 1 wherein the advertisement-specific selection model includes one or more product graphs, category graphs and content/category graphs.

4. The process of claim 1 wherein the advertisement-specific selection model utilizes product data.

5. The process of claim 1 wherein the advertisement-specific selection model utilizes user behavior data.

6. The process of claim 1 wherein the user-specific data is provided by the one or more originating retailers.

7. The process of claim 1 wherein the user-specific data is provided by one or more third parties.

8. An arrangement for selecting personalized non-competitive electronic advertising from a plurality of competitive and non-competitive advertisements comprising:

memory for storing user-specific data; and

a controller that generates a plurality of user models using the user-specific data, identifies a subset of the plurality of user models by applying an advertisement-specific selection model to the plurality of user models to identify users for which the specific advertisement is relevant and applies a non-competitive rule set to the identified subset of user models to identify which user models are associated with one or more non-competitive originating retailers.

9. The arrangement of claim 8 wherein user-specific activity data is user behavior for a specific user and includes data regarding purchases, product views, searches and user lists.

10. The arrangement of claim 8 wherein the advertisement-specific selection model includes one or more product graphs, category graphs and content/category graphs.

11. The arrangement of claim 8 wherein the advertisement-specific selection model utilizes product data or user behavior data.

12. The arrangement of claim 8 wherein the user-specific data is provided by the one or more originating retailers.

13. The arrangement of claim 8 wherein the step of selecting non-competitive personalized electronic advertising occurs in real time.

14. A computer-readable medium having computer-executable instructions for selecting personalized non-competitive electronic advertising from a plurality of competitive and non-competitive advertisements, the computer-executable instructions causing the arrangement to perform the steps of:

generating a plurality of user models, each user model including user-specific data;

identifying a subset of the plurality of user models by applying an advertisement-specific selection model to the plurality of user models to identify users for which a specific advertisement is relevant; and

applying a non-competitive rule set to the identified subset of user models to identify which user models are associated with one or more non-competitive originating retailers.

15. The computer readable medium of claim 14 wherein user-specific data is user specific and includes data regarding purchases, product views, searches and user lists.

16. The computer readable medium of claim 14 wherein the advertisement-specific selection model includes one or more product graphs, category graphs and content/category graphs.

17. The computer readable medium of claim 14 wherein the advertisement-specific selection model utilizes product data.

18. The computer readable medium of claim 14 wherein the advertisement-specific selection model utilizes user behavior data.

19. The computer readable medium of claim 14 wherein the user specific identification data and user specific activity data is provided by the one or more originating retailers.

20. The computer readable medium of claim 14 wherein the step of selecting non-competitive personalized electronic advertising occurs in real time.