METHOD AND SYSTEM FOR REAL TIME TARGETED ADVERTISING IN A RETAIL ENVIRONMENT

• US 20150199716A1
• Filed: 01/10/2014
• Published: 07/16/2015
• Est. Priority Date: 01/10/2014
• Status: Active Grant

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Gerard, Jean Pierre
• Granted Patent: US 9,424,590 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0281 Customer communication at a business location, e.g. providing product or service information, consulting
• CPC Class Codes: H04W 4/80 Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

Abstract

A method and a system for real time targeted advertising using purchase transaction data and payment card holder activity and location information in a retail environment. The system comprises one or more databases configured to store a first set of information comprising payment card holder information including at least purchasing and payment activities attributable to the payment card holder, a second set of information comprising payment card holder activity and location in a retail environment, and a third set of information comprising merchant advertising information. The system further comprises a processor configured to generate predictive behavioral models based at least in part on the first set of information and the second set of information, associate the predictive behavioral models with the third set of information, and convey the associated information to a merchant to enable the merchant to make targeted offers to the payment card holder.

Claims

1. A method comprising:

retrieving from one or more databases a first set of information comprising payment card holder information including at least purchasing and payment activities attributable to said payment card holders;

retrieving from one or more databases a second set of information comprising payment card holder activity and location in a retail environment, wherein the retail environment has at least one radio frequency identification (RFID) reader and the payment card holder has at least one payment card having at least one RFID tag, wherein the at least one RFID reader is capable of operably communicating with the at least one RFID tag to determine activity and location of the payment card holder in the retail environment;

retrieving from one or more databases a third set of information comprising merchant advertising information;

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

associating the one or more predictive behavioral models with the third set of information; and

conveying at least a portion of the associated information to a merchant to enable the merchant to make one or more targeted offers to the payment card holder.

2. The method of claim 1, further comprising algorithmically analyzing the first set of information and the second set of information to generate the one or more predictive behavioral models.

3. The method of claim 1, further comprising algorithmically associating the one or more predictive behavioral models with the third set of information to generate the one or more targeted offers.

4. 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 one or more payment card holders; and

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

5. The method of claim 1, wherein the one or more predictive behavioral models are based upon the behavioral information of the one or more payment card holders and the intent of the one or more payment card holders.

6. 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 the one or more payment card holders, after the targeted offer has been made.

7. The method of claim 1, wherein the first set of information comprises payment card purchasing and payment transactions and demographic and/or geographic information.

8. The method of claim 1, wherein the second set of information comprises information on the payment card holder'"'"'s path in the retail environment, information on an amount of time spent in a particular area of the retail environment, and information on stores of the retail environment visited by the payment card holder.

9. The method of claim 1, wherein the third set of information comprises a commercial for a product or service, information about the product or service, suggested activities that incorporate the product or service, recommendations of other products or services that can be used in conjunction with the product or service, and coupons or rebates for the product or service.

10. The method of claim 1, further comprising:

conveying at least a portion of the associated information to the merchant to enable the merchant to make one or more targeted offers to the payment card holder on a real time basis.

11. A system comprising:

one or more databases configured to store a first set of information comprising payment card holder information including at least purchasing and payment activities attributable to the payment card holder;

one or more databases configured to store a second set of information comprising payment card holder activity and location in a retail environment, wherein the retail environment has at least one radio frequency identification (RFID) reader and the payment card holder has at least one payment card having at least one RFID tag, wherein the at least one RFID reader is capable of operably communicating with the at least one RFID tag to determine activity and location of the payment card holder in the retail environment;

one or more databases configured to store a third set of information comprising merchant advertising information;

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;

associate the one or more predictive behavioral models with the third set of information; and

convey at least a portion of the associated information to a merchant to enable the merchant to make one or more targeted offers to the payment card holder.

12. The system of claim 11, wherein the processor is configured to algorithmically analyze the first set of information and the second set of information to generate the one or more predictive behavioral models.

13. The system of claim 11, wherein the processor is configured to algorithmically associate the one or more predictive behavioral models with the third set of information to generate the one or more targeted offers.

14. The system of claim 11, wherein the one or more predictive behavioral models provides a behavioral propensity score that is used for conveying to the merchant the activities and characteristics attributable to the payment card holder 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.

15. The system of claim 11, 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 the payment card holder, after the targeted offer has been made.

16. The system of claim 11, wherein the processor is configured to:

analyze the first set of information and the second set of information to determine behavioral information of the payment card holder; and

extract information related to an intent of the one or more payment card holders from the behavioral information.

17. The system of claim 11, wherein the one or more predictive behavioral models are based upon the behavioral information of the payment card holder and the intent of the payment card holder.

18. The system of claim 11, wherein the first set of information comprises payment card purchasing and payment transactions and demographic and/or geographic information.

19. The system of claim 11, wherein the second set of information comprises information on the payment card holder'"'"'s path in the retail environment, information on an amount of time spent in a particular area of the retail environment, and information on stores of the retail environment visited by the payment card holder.

20. The system of claim 11, wherein the third set of information comprises a commercial for a product or service, information about the product or service, suggested activities that incorporate the product or service, recommendations of other products or services that can be used in conjunction with the product or service, and coupons or rebates for the product or service.

21. The system of claim 11, wherein the processor is configured to:

convey at least a portion of the associated information to the merchant to enable the merchant to make one or more targeted offers to the payment card holder on a real time basis.

22. A method for generating one or more predictive behavioral models, the method comprising:

retrieving from one or more databases a first set of information comprising payment card holder information including at least purchasing and payment activities attributable to a payment card holder;

retrieving from one or more databases a second set of information comprising payment card holder activity and location in a retail environment, wherein the retail environment has at least one radio frequency identification (RFID) reader and the payment card holder has at least one payment card having at least one RFID tag, wherein the at least one RFID reader is capable of operably communicating with the at least one RFID tag to determine activity and location of the payment card holder in the retail environment;

analyzing the first set of information and the second set of information to determine behavioral information of the payment card holder;

extracting information related to an intent of the payment card holder from the behavioral information; and

generating one or more predictive behavioral models based on the behavioral information and intent of the payment card holder, the payment card holder having a propensity to carry out certain activities based on the one or more predictive behavioral models.

23. The method of claim 22, further comprising:

associating the one or more predictive behavioral models with a third set of information comprising merchant advertising information; and

conveying at least a portion of the associated information to a merchant to enable the merchant to make one or more targeted offers to the payment card holder on a real time basis.