USING PRODUCT AND SOCIAL NETWORK DATA TO IMPROVE ONLINE ADVERTISING

• US 20090171748A1
• Filed: 12/27/2007
• Published: 07/02/2009
• Est. Priority Date: 12/27/2007
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Merino, James Raymond, Moore, Paul Cameron, Haynes, Jonathan Frank, Aven, Brandy Lee, Burgess, David Anthony
• Granted Patent: US 8,843,406 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0256 User search
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Methods and apparatus for improving word-of-mouth online advertising are provided. Construct a social network including multiple users based on the users'"'"' social network data and optionally further based on the users'"'"' demographical and/or other personal information. Categorize the users in the social network with respect to a type of product in terms of their propensity to adopt the type of product and to influence others in the social network in adopting the type of product. Determine appropriate content object(s) for each category of users, and send the content object(s) to each category of users via different channels at the appropriate time during the product'"'"'s lifecycle.

Claims

1. A computer-implemented method of online advertising, comprising:

receiving a request for an interface from a user;

determining at least one content object to be displayed on the interface based on at least one category to which the user belongs with respect to a social network to which the user belongs and with respect to a type of product, wherein each category indicates a position of the user in the social network and activities of the user in connection with the type of product; and

delivering the at least one content object to the user via the interface.

2. The computer-implemented method, as recited in claim 1, further comprising:

categorizing the user into one of a plurality of categories with respect to the social network and with respect to the type of product.

3. The computer-implemented method, as recited in claim 2, wherein categorizing the user into one of the plurality of categories is based on comparing the user'"'"'s actions with respect to the type of product with actions of other users belonging to the social network with respect to the type of product.

4. The computer-implemented method, as recited in claim 1, further comprising:

categorizing a plurality of users belonging to the social network into a plurality of categories respectively with respect to the type of product, wherein the user is one of the plurality of users.

5. The computer-implemented method, as recited in claim 4, wherein categorizing the plurality of users is based on historical product data associated with the type of product and social network data of each of the plurality of users.

6. The computer-implemented method, as recited in claim 4, wherein categorizing the plurality of users is based on a score system, such that each of the plurality of users has a score with respect to the type of product that is determined based on the user'"'"'s historical activity data relating to the type of product.

7. The computer-implemented method, as recited in claim 4, further comprising:

constructing the social network using social network data from each of the plurality of users.

8. The computer-implemented method, as recited in claim 7, wherein constructing the social network further uses at least one selected from the group consisting of demographic data, behavior data, and user intent data from each of the plurality of users.

9. The computer-implemented method, as recited in claim 4, wherein the plurality of categories are selected from the group consisting of innovators, early adopters, influencers, brand advocators, majority, early majority, late majority, late adopters, and laggards.

10. The computer-implemented method, as recited in claim 4, further comprising:

determining at least one content object for each of the plurality of categories of users with respect to the type of product.

11. A system for online advertising, comprising at least one computing device configured to:

receive a request for an interface from a user;

determine at least one content object to be displayed on the interface based on at least one category to which the user belongs with respect to a social network to which the user belongs and with respect to a type of product, wherein each category indicates a position of the user in the social network and activities of the user in connection with the type of product; and

deliver the at least one content object to the user via the interface.

12. The system, as recited in claim 11, wherein the at least one computer device is further configured to:

categorize the user into one of a plurality of categories with respect to the social network and with respect to the type of product.

13. The system, as recited in claim 11, wherein the at least one computer device is further configured to:

categorize a plurality of users belonging to the social network into a plurality of categories respectively with respect to the type of product, wherein the user is one of the plurality of users.

14. The system, as recited in claim 13, wherein categorize the plurality of users is based on historical product data associated with the type of product, user event data, and social network data of each of the plurality of users.

15. The system, as recited in claim 13, wherein categorize the plurality of users is based on a score system, such that each of the plurality of users has a score with respect to the type of product that is determined based on the user'"'"'s historical activity data relating to the type of product.

16. A computer program product for online advertising comprising a computer-readable medium having a plurality of computer program instructions stored therein, which are operable to cause at least one computing device to:

receive a request for an interface from a user;

determine at least one content object to be displayed on the interface based on at least one category to which the user belongs with respect to a social network to which the user belongs and with respect to a type of product, wherein each category indicates a position of the user in the social network and activities of the user in connection with the type of product; and

deliver the at least one content object to the user via the interface.

17. The computer program product, as recited in claim 16, wherein the plurality of computer program instructions are further operable to cause the at least one computing device to:

categorize the user into one of a plurality of categories with respect to the social network and with respect to the type of product.

18. The computer program product, as recited in claim 16, wherein the plurality of computer program instructions are further operable to cause the at least one computing device to:

categorize a plurality of users belonging to the social network into a plurality of categories respectively with respect to the type of product, wherein the user is one of the plurality of users.

19. The computer program product, as recited in claim 18, wherein categorize the plurality of users is based on historical product data associated with the type of product, user event data, and social network data of each of the plurality of users.

20. The computer program product, as recited in claim 18, wherein categorize the plurality of users is based on a score system, such that each of the plurality of users has a score with respect to the type of product that is determined based on the user'"'"'s historical activity data relating to the type of product.