Method and system for recommending a merchant based on transaction data

• US 9,530,151 B2
• Filed: 11/26/2014
• Issued: 12/27/2016
• Est. Priority Date: 11/26/2014
• Status: Active Grant

• Current Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Original Assignee: Mastercard International Incorporated (MasterCard Incorporated)
• Inventors: Chavarria, Pedro, Perez, Kristofer
• Primary Examiner(s): VO, TUYEN KIM
• Application Number:
  US14/554,981
• Publication Number:
  US 20160148258A1
• Time in Patent Office: 762 Days
• Field of Search: 235/375, 235/380, 235/383, 235/449, 235/493, 235/376, 235/385, 705 14- 26
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0261 based on user location

Abstract

A computer-implemented method for recommending a merchant based on transaction data is provided. The method is implemented using an analyzer computing device in communication with one or more memory devices. The method includes generating a profile indicating a stage of life of a cardholder, based at least in part on first transaction data stored in the one or more memory devices. The first transaction data is associated with one or more purchases made by the cardholder through a payment network. The method additionally includes retrieving, from the one or more memory devices, second transaction data associated with a plurality of sales from a first merchant, determining a transaction volume associated with the first merchant, and generating a recommendation for the cardholder to purchase goods from the first merchant, based at least in part on the determined transaction volume and the profile.

Claims

1. A computer-implemented method for recommending a merchant based on transaction data, said method implemented using an analyzer computing device in communication with one or more memory devices, said method comprising:

defining a plurality of stages of life, wherein each stage of life of the plurality of stages of life is associated with a time period in a lifetime of a cardholder;

receiving first transaction data for the cardholder, wherein the first transaction data is associated with one or more purchases made by the cardholder through a payment network;

determining a stage of life of the cardholder based on determining an interest of the cardholder, wherein the interest represents goods purchased by the cardholder including the one or more purchases;

generating, by the analyzer computing device, a profile associated with the cardholder, based at least in part on associating the first transaction data with the stage of life for the cardholder, wherein the profile indicates the stage of life of the cardholder;

retrieving, by the analyzer computing device, from the one or more memory devices, second transaction data associated with a plurality of sales associated with a first merchant, wherein the transactions were processed through the payment network;

determining, by the analyzer computing device, a transaction volume associated with the first merchant;

generating a ranking placing the first merchant higher than at least one other merchant in a plurality of merchants, based on a determination that the transaction volume is higher than at least one other transaction volume associated with a plurality of merchants, indicating that the first merchant is more highly regarded than the plurality of merchants; and

generating, by the analyzer computing device, a recommendation for the cardholder to purchase goods from the first merchant, based at least in part on the ranking and a determination that the first merchant sells one or more goods corresponding to the interest associated with the stage of life of the cardholder.

2. The method of claim 1, wherein the transaction volume is a first transaction volume, said method further comprising:

determining a second transaction volume associated with a second merchant;

comparing the first transaction volume to the second transaction volume; and

determining that the first transaction volume is greater than the second transaction volume.

3. The method of claim 1, further comprising:

associating the first merchant with a first geographic area;

determining a second transaction volume associated with a second merchant in the first geographic area;

comparing the first transaction volume to the second transaction volume; and

determining that the first transaction volume is greater than the second transaction volume.

4. The method of claim 1, further comprising:

associating the first merchant with a first set of goods;

determining a second transaction volume associated with a second merchant associated with the first set of goods;

comparing the first transaction volume to the second transaction volume; and

determining that the first transaction volume is greater than the second transaction volume.

5. The method of claim 1, further comprising:

determining a first geographic area associated with the cardholder;

determining that the first merchant is within the first geographic area;

determining a first category of goods associated with the cardholder, based on the profile; and

determining that the first merchant sells goods associated with the cardholder.

6. The method of claim 5, further comprising determining that the goods from the first merchant are geographically-based, further comprising determining that the geographic proximity of the first merchant to the cardholder affects the provisioning of the goods to the cardholder.

7. The method of claim 1, further comprising:

determining that the first merchant has paid a recommendation fee; and

transmitting the recommendation to a client computing device associated with the cardholder.

8. The method of claim 1, wherein the stage of life is associated with one or more interests, and wherein the one or more interests each represent the one or more goods sold by the plurality of merchants, further comprising determining the stage of life for the cardholder by:

comparing the first transaction data of the cardholder to transaction data associated with at least one other cardholder; and

generating a similarity score for the first cardholder wherein the similarity score indicates that the first cardholder is experiencing a stage of life.

9. The method of claim 8, wherein determining the stage of life for the cardholder includes comparing the first transaction data of the cardholder with one or more predefined sets of reference goods.

10. An analyzer computing device for recommending a merchant based on transaction data, said computing device comprising one or more processors in communication with one or more memory devices, said analyzer computing device configured to:

define a plurality of stages of life, wherein each stage of life of the plurality of stages of life is associated with a time period in a lifetime of a cardholder;

receive first transaction data for the cardholder, wherein the first transaction data is associated with one or more purchases made by the cardholder through a payment network;

determine a stage of life of the cardholder based on first transaction data of the cardholder, wherein said analyzer computing device is further configured to determine an interest of the cardholder, and wherein the interest represents goods purchased by the cardholder including the one or more purchases;

generate a profile associated with the cardholder, based at least in part on associating the first transaction data with the stage of life for the cardholder, wherein the profile indicates the stage of life of the cardholder;

retrieve, from the one or more memory devices, second transaction data associated with a plurality of sales associated with a first merchant, wherein the transactions were processed through the payment network;

determine a transaction volume associated with the first merchant;

generate a ranking placing the first merchant higher than at least one other merchant in a plurality of merchants, based on a determination that the transaction volume is higher than at least one other transaction volume associated with a plurality of merchants, indicating that the first merchant is more highly regarded than the plurality of merchants; and

generate a recommendation for the cardholder to purchase goods from the first merchant, based at least in part on the ranking and a determination that the first merchant sells one or more goods corresponding to the interest associated with the stage of life of the cardholder.

11. The analyzer computing device of claim 10, wherein the transaction volume is a first transaction volume, said analyzer computing device further configured to:

determine a second transaction volume associated with a second merchant;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.

12. The analyzer computing device of claim 10, further configured to:

associate the first merchant with a first geographic area;

determine a second transaction volume associated with a second merchant in the first geographic area;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.

13. The analyzer computing device of claim 10, further configured to:

associate the first merchant with a first set of goods;

determine a second transaction volume associated with a second merchant associated with the first set of goods;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.

14. The analyzer computing device of claim 10, further configured to:

determine a first geographic area associated with the cardholder;

determine that the first merchant is within the first geographic area;

determine a first category of goods associated with the cardholder, based on the profile; and

determine that the first merchant sells goods associated with the cardholder.

15. The analyzer computing device of claim 10, further configured to:

receive, from a client computing device associated with the cardholder, an indication that the cardholder agrees to generation of the profile; and

transmit the recommendation to the client computing device.

16. The analyzer computing device of claim 10, further configured to determine that the first merchant has paid a recommendation fee prior to generating the recommendation to the client computing device associated with the cardholder.

17. A non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by an analyzer computing device having one or more processors in communication with one or more memory devices, the computer-executable instructions cause the analyzer computing device to:

define a plurality of stages of life, wherein each stage of life of the plurality of stages of life is associated with a time period in a lifetime of a cardholder;

receive first transaction data for the cardholder, wherein the first transaction data is associated with one or more purchases made by the cardholder through a payment network;

determine a stage of life of the cardholder based on first transaction data of the cardholder, wherein said analyzer computing device is further configured to determine an interest of the cardholder, and wherein the interest represents goods purchased by the cardholder including the one or more purchases;

generate a profile associated with the cardholder, based at least in part on associating the first transaction data with the stage of life for the cardholder, wherein the profile indicates the stage of life of the cardholder;

retrieve, from the one or more memory devices, second transaction data associated with a plurality of sales associated with a first merchant, wherein the transactions were processed through the payment network;

determine a transaction volume associated with the first merchant;

generate a ranking placing the first merchant higher than at least one other merchant in a plurality of merchants, based on a determination that the transaction volume is higher than at least one other transaction volume associated with a plurality of merchants, indicating that the first merchant is more highly regarded than the plurality of merchants; and

generate a recommendation for the cardholder to purchase goods from the first merchant, based at least in part on the ranking and a determination that the first merchant sells one or more goods corresponding to the interest associated with the stage of life of the cardholder.

18. The non-transitory computer-readable storage medium of claim 17, wherein the transaction volume is a first transaction volume and said computer-executable instructions additionally cause the analyzer computing device to:

determine a second transaction volume associated with a second merchant;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.

19. The non-transitory computer-readable storage medium of claim 17, wherein the computer-executable instructions additionally cause the analyzer computing device to:

associate the first merchant with a first geographic area;

determine a second transaction volume associated with a second merchant in the first geographic area;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.

20. The non-transitory computer-readable storage medium of claim 17, wherein the computer-executable instructions additionally cause the analyzer computing device to:

associate the first merchant with a first set of goods;

determine a second transaction volume associated with a second merchant associated with the first set of goods;

compare the first transaction volume to the second transaction volume; and

determine that the first transaction volume is greater than the second transaction volume.