METHOD AND SYSTEM FOR RECOMMENDING RELEVANT MERCHANTS FOR A CONSUMER AT A GIVEN GEOGRAPHICAL LOCATION BY EVALUATING THE STRENGTH OF THE INTERSECT BETWEEN CONSUMER VECTORS AND MERCHANT VECTORS

• US 20170148081A1
• Filed: 11/20/2015
• Published: 05/25/2017
• Est. Priority Date: 11/20/2015
• Status: Active Application

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Chauhan, Rohit
• Application Number:
  US14/947,284
• Publication Number:
  US 20170148081A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A method is provided for recommending relevant merchants for a consumer at a given geographical location. The method generally includes identifying, using a computing processing unit, transactions processed over at least one payment device network as being associated with a payment network account of a consumer. The identified transactions are then parsed to extract ISO 8583 formatted data. By evaluating the extracted ISO 8583 formatted data and determining a location of the consumer, a list containing merchant that are available for more purchases and within a predetermined distance to a geographical location of the consumer are determined. Furthermore, the list may be refined by evaluating the strength of the intersect between a plurality of consumer vectors and a plurality of merchant vectors.

Claims

1. A method for recommending relevant merchants for a consumer at a given geographical location, the method comprising:

identifying transactions processed over at least one payment device network as being associated with a payment network account of a consumer;

parsing the identified transactions to extract ISO 8583 formatted data, wherein the ISO 8583 formatted data representing, where present, for each of the identified transactions, at least an associated merchant category code, an associated merchant category name, an associated merchant name, an associated merchant address and an associated transaction amount;

aggregating, using a computing processing unit, the associated transaction amounts for the identified transactions for each of the associated merchant categories, wherein all of the identified transactions for each of the associated merchant categories occurred in a predetermined time period;

comparing, using the computing processing unit, the aggregated amount for each of the associated merchant categories with a predetermined total threshold purchase amount of a respective merchant category of the consumer and wherein, for each of the aggregated amounts being less than the predetermined total threshold purchase amount, identifying the associated merchant category as a target merchant category;

determining geographical location of the consumer via a global positioning system (GPS) receiver of a mobile device of the consumer;

identifying, using the computing processing unit, merchants of each of the identified associated merchant categories within a predetermined distance to the geographical location of the consumer; and

transmitting, using a transmitting unit, an alert including a list of the identified merchants to the mobile device of the consumer.

2. The method of claim 1, wherein the list of the identified merchants of each of the identified associated merchant categories within the predetermined distance to the geographical location of the consumer is refined by evaluating the strength of correlation between a plurality of consumer vectors and a plurality of merchant vectors.

3. The method of claim 2, wherein the plurality of consumer vectors and the plurality of merchant vectors are generated by leveraging the identified transactions of the consumer.

4. The method of claim 3, wherein the plurality of consumer vectors and the plurality of merchant vectors are generated by leveraging data from social network websites of the consumer, demographics data provided by the consumer and preference data provided by the consumer.

5. The method of claim 2, wherein the plurality of consumer vectors includes a plurality of consumer purchase behavior vectors and a plurality of consumer total spend vectors.

6. The method of claim 5, wherein the plurality of consumer purchase behavior vectors include consumer geographical location, buyer segment of the consumer, purchase affluence indicator by merchant categories, average, minimum, maximum and standard deviation of average spending by merchant categories, purchase frequency cycle by merchant categories, purchase behavior by merchant categories days of the week, purchase behavior by merchant industries by hours, purchase behavior by merchant categories by online and offline average spending, purchase behavior by season, months and holidays, purchase sequence pattern by merchant categories, likely to try new store by merchant categories, consumer spending by merchant categories by zip codes, and consumer sub-category preferences by merchant categories.

7. The method of claim 5, wherein the plurality of consumer total spend vectors include total month-to-date and year-to-date spending by merchant categories, average monthly and yearly spending by merchant categories, and details of the last transaction.

8. The method of claim 2, wherein the plurality of merchant vectors includes a plurality of merchant trend vectors and a plurality of merchant total trend vectors.

9. The method of claim 8, wherein the plurality of merchant trend vectors include merchant geographical location, key buyer segments of consumers visiting the merchant, affluent profile of the store, average, minimum, maximum and the standard deviation of the average spending, average days between two consecutive visits, store traffic by days of the week, store traffic by hour interval, percentage of sales of online and offline, sales traffic by season, month and key holidays, purchase sequence traffic, percentage of new customers and return customers, store hours by days of the week, merchant feeder zip codes, and merchant sub-category.

10. The method of claim 8, wherein the plurality of merchant total trend vectors include sales growth of index of the merchant in the industry, consumer loyalty index of the merchant in the industry, and merchant return index relative to the industry.

11. The method of claim 1, wherein the mobile device includes mobile phones, smartphones, tablets and smartwatches.

12. A non-transitory machine-readable recording medium storing thereon a program of instruction which, when executed by a processor, cause the processor to:

identify transactions processed over at least one payment device network as being associated with a payment network account of a consumer;

parse the identified transactions to extract ISO 8583 formatted data, wherein the ISO 8583 formatted data representing, where present, for each of the identified transactions, at least an associated merchant category code, an associated merchant category name, an associated merchant name, an associated merchant address and an associated transaction amount;

aggregate, using a computing processing unit, the associated transaction amounts for the identified transactions for each of the associated merchant categories, wherein all of the identified transactions for each of the associated merchant categories occurred in a predetermined time period;

compare, using the computing processing unit, the aggregated amount for each of the associated merchant categories with a predetermined total threshold purchase amount of a respective merchant category of the consumer and wherein, for each of the aggregated amounts being less than the predetermined total threshold purchase amount, identifying the associated merchant category as a target merchant category;

determine geographical location of the consumer via a global positioning system (GPS) receiver of a mobile device of the consumer;

identify, using the computing processing unit, merchants of each of the identified associated merchant categories within a predetermined distance to the geographical location of the consumer; and

transmit, using a transmitting unit, an alert including a list of the identified merchants to the mobile device of the consumer.

13. The medium according to claim 12, wherein the list of the identified merchants of each of the identified associated merchant categories within the predetermined distance to the geographical location of the consumer is refined by evaluating the strength of correlation between a plurality of consumer vectors and a plurality of merchant vectors.

14. The medium according to claim 13, wherein the plurality of consumer vectors and the plurality of merchant vectors are generated by leveraging the identified transactions of the consumer.

15. The medium according to claim 14, wherein the plurality of consumer vectors and the plurality of merchant vectors are generated by leveraging data from social network websites of the consumer, demographics data provided by the consumer and preference data provided by the consumer.

16. The medium according to claim 13, wherein the plurality of consumer vectors includes a plurality of consumer purchase behavior vectors and a plurality of consumer total spend vectors.

17. The medium according to claim 16, wherein the plurality of consumer purchase behavior vectors include consumer geographical location, buyer segment of the consumer, purchase affluence indicator by merchant categories, average, minimum, maximum and standard deviation of average spending by merchant categories, purchase frequency cycle by merchant categories, purchase behavior by merchant categories days of the week, purchase behavior by merchant industries by hours, purchase behavior by merchant categories by online and offline average spending, purchase behavior by season, months and holidays, purchase sequence pattern by merchant categories, likely to try new store by merchant categories, consumer spending by merchant categories by zip codes, and consumer sub-category preferences by merchant categories.

18. The medium according to claim 16, wherein the plurality of consumer total spend vectors include total month-to-date and year-to-date spending by merchant categories, average monthly and yearly spending by merchant categories, and details of the last transaction.

19. The medium according to claim 13, wherein the plurality of merchant vectors includes a plurality of merchant trend vectors and a plurality of merchant total trend vectors.

20. The medium according to claim 19, wherein the plurality of merchant trend vectors include merchant geographical location, key buyer segments of consumers visiting the merchant, affluent profile of the store, average, minimum, maximum and the standard deviation of the average spending, average days between two consecutive visits, store traffic by days of the week, store traffic by hour interval, percentage of sales of online and offline, sales traffic by season, month and key holidays, purchase sequence traffic, percentage of new customers and return customers, store hours by days of the week, merchant feeder zip codes, and merchant sub-category.

21. The medium according to claim 19, wherein the plurality of merchant total trend vectors include sales growth of index of the merchant in the industry, consumer loyalty index of the merchant in the industry, and merchant return index relative to the industry.

22. The medium according to claim 12, wherein the mobile device includes mobile phones, smartphones, tablets and smartwatches.

23. A system for recommending relevant merchants for a consumer at a given geographical location, the system comprising:

one or more computing processing units configured to monitor financial transactions being transmitted over one or more payment device networks and to execute a plurality of algorithm models;

a member unit configured to provide a graphical user interface to the consumer for registering to the system, creating a user account profile and inputting user preference data;

one or more database management systems, each of the one or more database management systems including;

a user account database configured to store data associated with the consumer,

a transaction database configured to store financial transactions identified by the one or more computing processing units, and

a merchant database configured to store data structures corresponding to a relevant merchant profile, a plurality of consumer vectors and a plurality of merchant vectors; and

a transmitting unit configured to transmit an alert including a list of merchants in the relevant merchant profile to the consumer.