MOBILE MARKETING AND TARGETING USING PURCHASE TRANSACTION DATA

• US 20150039390A1
• Filed: 07/31/2013
• Published: 02/05/2015
• Est. Priority Date: 07/31/2013
• Status: Abandoned Application

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Hu, Po, Gerard, Jean Pierre
• Application Number:
  US13/955,058
• Publication Number:
  US 20150039390A1
• Time in Patent Office: Days
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0255 based on user history

Abstract

A method for making a targeted offer by a telecommunication entity to an audience is provided. The method involves receiving from the telecommunication entity a first set of information including billing activities attributable to the telecommunication entity and payment activities attributable to the audience, by a financial transaction processing entity; retrieving by the financial transaction processing entity a second set of information including billing activities attributable to the financial transaction processing entity and purchasing and payment activities attributable to the audience; and generating one or more predictive behavioral models based at least in part on the first set and second set of information. The method also involves identifying activities and characteristics attributable to the audience based on the predictive behavioral models, and conveying those to the telecommunication entity. A system for making a targeted offer by a telecommunication entity to an audience is also provided.

Claims

1. A method for making a targeted offer by a telecommunication entity to an audience of potential acceptors, said method comprising:

receiving from the telecommunication entity, from one or more databases, a first set of information including billing activities attributable to said telecommunication entity and payment activities attributable to said audience of potential acceptors, by a financial transaction processing entity;

retrieving by the financial transaction processing entity, from one or more databases, a second set of information including billing activities attributable to said financial transaction processing entity and purchasing and payment activities attributable to said audience of potential acceptors;

generating one or more predictive behavioral models based at least in part on the first set of information and the second set of information;

identifying activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models; and

conveying to the telecommunication entity said activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models, to enable the telecommunication entity to make a targeted offer to the audience of potential acceptors.

2. The method of claim 1, further comprising:

analyzing the first set of information and the second set of information to determine behavioral information of the audience of potential acceptors; and

extracting information related to an intent of the audience of potential acceptors from the behavioral information.

3. The method of claim 2, wherein the one or more predictive behavioral models are based upon the behavioral information of the audience of potential acceptors and the intent of the audience of potential acceptors.

4. The method of claim 1, wherein the audience of potential acceptors are people and/or businesses, the activities attributable to the audience of potential acceptors are financial transactions associated with the audience of potential acceptors, and the characteristics attributable to the audience of potential acceptors are demographics and/or geographical characteristics of the audience of potential acceptors.

5. The method of claim 1, wherein the first set of information comprises telecommunication billing and payment transactions and optionally demographic and/or geographic information.

6. The method of claim 1, wherein the second set of information comprises payment card billing, purchasing and payment transactions and optionally demographic and/or geographic information.

7. The method of claim 1, wherein the audience of potential acceptors comprise telecommunication entity subscribers and payment card holders.

8. The method of claim 1, wherein an identification number is associated with the first set of information that is received from the telecommunication entity by the financial transaction processing entity to protect personally identifiable information (PII).

9. The method of claim 1, wherein the telecommunication entity makes a targeted offer to the audience of potential acceptors by e-mails, text messages or phone calls.

10. The method of claim 1, further comprising:

tracking and measuring impact of the targeted offer based at least in part on purchasing and payment activities attributable to said audience of potential acceptors, after the targeted offer has been made.

11. The method of claim 1, further comprising:

associating said telecommunication entity with one or more merchant entities so as to enable a targeted offer to be made to customers of the one or more merchant entities.

12. A system for making a targeted offer by a telecommunication entity to an audience of potential acceptors, said system comprising:

one or more databases configured to store a first set of information including billing activities attributable to said telecommunication entity and payment activities attributable to said audience of potential acceptors;

one or more databases configured to store a second set of information including billing activities attributable to a financial transaction processing entity and purchasing and payment activities attributable to said audience of potential acceptors;

a processor configured to;

generate one or more predictive behavioral models based at least in part on the first set of information and the second set of information; and

identify activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models; and

a device for conveying to the telecommunication entity said activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models, to enable the telecommunication entity to make a targeted offer to the audience of potential acceptors.

13. The system of claim 12, wherein the processor is configured to:

analyze the first set of information and the second set of information to determine behavioral information of the audience of potential acceptors; and

extract information related to an intent of the audience of potential acceptors from the behavioral information.

14. The system of claim 13, wherein the one or more predictive behavioral models are based upon the behavioral information of the audience of potential acceptors and the intent of the audience of potential acceptors.

15. The system of claim 12, wherein the first set of information comprises telecommunication billing and payment transactions and optionally demographic and/or geographic information, and wherein the second set of information comprises payment card billing, purchasing and payment transactions and optionally demographic and/or geographic information.

16. The system of claim 12, wherein the processor is configured to:

track and measure impact of the targeted offer based at least in part on purchasing and payment activities attributable to said audience of potential acceptors, after the targeted offer has been made.

17. The system of claim 12, wherein the one or more predictive behavioral models provides a behavioral propensity score that is used for conveying to the telecommunication entity said activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models, and wherein the behavioral propensity score is indicative of a propensity to exhibit a certain behavior.

18. The system of claim 12, wherein the processor is configured to:

associate said telecommunication entity with one or more merchant entities so as to enable a targeted offer to be made to customers of the one or more merchant entities.

19. The system of claim 18, wherein the processor is configured to:

track and measure impact of the targeted offer based at least in part on purchasing and payment activities attributable to said audience of potential acceptors, after the targeted offer has been made.

20. The system of claim 17, wherein the behavioral propensity score is used for conveying to the one or more merchant entities said activities and characteristics attributable to said audience of potential acceptors based on the one or more predictive behavioral models, wherein the behavioral propensity score is indicative of a propensity to exhibit a certain behavior.

21. A method for generating one or more predictive behavioral models, said method comprising:

retrieving, from one or more databases, information including activities and characteristics attributable to one or more payment card holders;

analyzing the information to determine behavioral information of the one or more payment card holders;

extracting information related to an intent of the one or more payment card holders from the behavioral information; and

generating one or more predictive behavioral models based on the behavioral information and intent of the one or more payment card holders;

the one or more payment card holders having a propensity to carry out certain activities based on the one or more predictive behavioral models.

22. The method of claim 21, further comprising:

conveying to a telecommunication entity the activities and characteristics attributable to said one or more payment card holders based on the one or more predictive behavioral models, to enable the telecommunication entity to make a targeted offer to the one or more payment card holders.

23. The method of claim 22, wherein the one or more predictive behavioral models are capable of predicting behavior and intent in the one or more payment card holders.