Social Targeting

• US 20130166379A1
• Filed: 04/25/2012
• Published: 06/27/2013
• Est. Priority Date: 12/21/2011
• Status: Abandoned Application

• Current Assignee: Dell Products LP (Dell Technologies Inc.)
• Original Assignee: Dell Products LP (Dell Technologies Inc.)
• Inventors: Narang, Rajiv, Ehindero, Akintunde, Chen, Yingchi
• Application Number:
  US13/455,497
• Publication Number:
  US 20130166379A1
• Time in Patent Office: Days
• US Class Current: 705/14.52
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system and method are disclosed for social targeting within a social media environment. A sample set of social media interactions containing a reference to an intent to purchase a product is processed to generate a prioritization index. The prioritization index is then used to monitor social media interactions in a target social media environment to identify social media users exhibiting propensity-to-purchase behavior. A propensity-to-purchase value is then generated for each of the identified social media users and they are ranked accordingly. The ranked social media users are then converted into sales leads for nurturing.

Claims

1. A computer-implemented method for social targeting, comprising:

processing a first set of social media interaction data to generate a second set of social media interaction data containing a reference to an intent to purchase a product, the first set of social media interaction data associated with a first set of social media users and the second set of social media interaction data associated with a second set of set of social media users;

processing the second set of social media interaction data to generate a prioritization index;

processing a third set of social media interaction data with the prioritization index to generate a propensity-to-purchase value for individual users of a third set of social media users, the third set of social media interaction data associated with the third set of social media users; and

performing ranking operations to rank the third set of social media users according to their respective propensity-to-purchase value.

2. The method of claim 1, wherein the second set of social media interaction data is generated by performing Natural Language Processing (NLP) operations.

3. The method of claim 1, wherein the prioritization index is generated from a site visit index and a purchase index.

4. The method of claim 1, wherein the propensity-to-purchase value is generated by performing statistical modeling operations.

5. The method of claim 4, wherein the statistical modeling operations are performed using input data comprising at least one of:

a set of media response variables;

a set of promotion variables;

a set of revenue variables;

a set of firmographics data; and

a site visit index.

6. The method of claim 5, wherein the at least one site visit index is generated using a set of purchase variables as input data.

7. A system comprising:

a processor;

a data bus coupled to the processor; and

a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for;

processing a first set of social media interaction data to generate a second set of social media interaction data containing a reference to an intent to purchase a product, the first set of social media interaction data associated with a first set of social media users and the second set of social media interaction data associated with a second set of set of social media users;

processing a third set of social media interaction data with the prioritization index to generate a propensity-to-purchase value for individual users of a third set of social media users, the third set of social media interaction data associated with the third set of social media users; and

performing ranking operations to rank the second set of social media users according to their respective propensity-to-purchase value.

8. The system of claim 7, wherein the second set of social media interaction data is generated by performing Natural Language Processing (NLP) operations.

9. The system of claim 7, wherein the prioritization index is generated from a site visit index and a purchase index.

10. The system of claim 7, wherein the propensity-to-purchase value is generated by performing logic statistical modeling operations.

11. The system of claim 10, wherein the statistical modeling operations are performed using input data comprising at least one of:

a set of media response variables;

a set of promotion variables;

a set of revenue variables;

a set of firmographics data;

a site visit index.

12. The system of claim 11, wherein the at least one site visit index is generated using a set of purchase variables as input data.

13. A computer-usable medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

processing a first set of social media interaction data to generate a second set of social media interaction data containing a reference to an intent to purchase a product, the first set of social media interaction data associated with a first set of social media users and the second set of social media interaction data associated with a second set of set of social media users;

processing the second set of social media interaction data to generate a prioritization index;

processing a third set of social media interaction data with the prioritization index to generate a propensity-to-purchase value for individual users of a third set of social media users, the third set of social media interaction data associated with the third set of social media users; and

performing ranking operations to rank the third set of social media users according to their respective propensity-to-purchase value.

14. The computer usable medium of claim 13, wherein the second set of social media interaction data is generated by performing Natural Language Processing (NLP) operations.

15. The computer usable medium of claim 13, wherein the prioritization index is generated from a site visit index and a purchase index.

16. The computer usable medium of claim 13, wherein the propensity-to-purchase value is generated by performing statistical modeling operations.

17. The computer usable medium of claim 16, wherein the statistical modeling operations are performed using input data comprising at least one of:

a set of media response variables;

a set of promotion variables;

a set of revenue variables;

a set of firmographics data; and

a site visit index.

18. The computer usable medium of claim 17, wherein the at least one site visit index is generated using a set of purchase variables as input data.

19. The computer usable medium of claim 13, wherein the computer executable instructions are deployable to a client computer from a server at a remote location.

20. The computer usable medium of claim 13, wherein the computer executable instructions are provided by a service provider to a customer on an on-demand basis.