Systems and methods for recommending merchants
First Claim
1. A computer system for recommending at least one merchant of a plurality of merchants to a candidate cardholder, said computer system comprising:
- a memory device for storing data; and
a processor in communication with said memory device, said processor programmed to;
identify a plurality of merchants located within a predefined geographical region;
retrieve, from a payment network, electronic payment transaction information for a plurality of electronic payment card transactions involving a plurality of cardholders including the candidate cardholder and at least some of the plurality of merchants, the plurality of electronic payment transactions occurring within a predefined time period;
identify from the electronic payment transaction information a subset of cardholders from the plurality of cardholders, each of the subset of cardholders having completed electronic payment transactions with at least two of the plurality of merchants;
create, based on the retrieved electronic payment transaction information associated with the subset of cardholders, a merchant popularity matrix, wherein the merchant popularity matrix includes a counter associated with each pair of merchants included within the plurality of merchants, wherein to create the matrix, an associated counter is incremented when a cardholder in the subset of cardholders completes electronic payment transactions at both merchants in the pair, and wherein, to reduce an effect of cardholder bias towards a single merchant, no counter in the merchant popularity matrix is incremented when a cardholder completes multiple electronic payment transactions at the same merchant;
receive data signals from the payment network including data associated with electronic payment transactions for the candidate cardholder;
determine gratuity information for the candidate cardholder from the data signals;
determine candidate cardholder preference information for at least one candidate merchant of the plurality of merchants based at least in part on the gratuity information determined from the data signals;
create a candidate cardholder preference vector based on the candidate cardholder preference information, wherein the candidate cardholder preference vector represents a level of preference of the candidate cardholder for one merchant relative to at least one other merchant;
determine a merchant rank for each merchant of the plurality of merchants based on the merchant popularity matrix and the candidate cardholder preference vector;
determine a neutral merchant rank for each merchant of the plurality of merchants based on the retrieved electronic payment transaction information associated with the plurality of cardholders and a neutral preference vector including preference information values that are equal for each merchant of the plurality of merchants;
determine a merchant score for each merchant of the plurality of merchants based on a difference between the merchant rank and the neutral merchant rank; and
cause a list of recommended merchants including the at least one merchant to be displayed on a user device based on the determined merchant scores, wherein the user device is associated with the candidate cardholder.
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Accused Products
Abstract
A computer system for recommending merchants to a candidate cardholder is provided. The computer system includes a memory device in communication with a processor. The processor is programmed to receive transaction information for a plurality of cardholders from a payment network. The transaction information includes data relating to purchases made by the cardholders at a plurality of merchants, the purchases satisfying a first criteria. The processor receives candidate cardholder preference information for at least one of the merchants input by the candidate cardholder, determines a merchant rank for each merchant based on the received transaction information and the candidate cardholder preference information, determines a neutral merchant rank for each merchant based on the received transaction information and neutral cardholder preferences of the plurality of cardholders, and determines a merchant score for each of the plurality of merchants by comparing the merchant rank to the neutral merchant rank.
98 Citations
20 Claims
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1. A computer system for recommending at least one merchant of a plurality of merchants to a candidate cardholder, said computer system comprising:
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a memory device for storing data; and a processor in communication with said memory device, said processor programmed to; identify a plurality of merchants located within a predefined geographical region; retrieve, from a payment network, electronic payment transaction information for a plurality of electronic payment card transactions involving a plurality of cardholders including the candidate cardholder and at least some of the plurality of merchants, the plurality of electronic payment transactions occurring within a predefined time period; identify from the electronic payment transaction information a subset of cardholders from the plurality of cardholders, each of the subset of cardholders having completed electronic payment transactions with at least two of the plurality of merchants; create, based on the retrieved electronic payment transaction information associated with the subset of cardholders, a merchant popularity matrix, wherein the merchant popularity matrix includes a counter associated with each pair of merchants included within the plurality of merchants, wherein to create the matrix, an associated counter is incremented when a cardholder in the subset of cardholders completes electronic payment transactions at both merchants in the pair, and wherein, to reduce an effect of cardholder bias towards a single merchant, no counter in the merchant popularity matrix is incremented when a cardholder completes multiple electronic payment transactions at the same merchant; receive data signals from the payment network including data associated with electronic payment transactions for the candidate cardholder; determine gratuity information for the candidate cardholder from the data signals; determine candidate cardholder preference information for at least one candidate merchant of the plurality of merchants based at least in part on the gratuity information determined from the data signals; create a candidate cardholder preference vector based on the candidate cardholder preference information, wherein the candidate cardholder preference vector represents a level of preference of the candidate cardholder for one merchant relative to at least one other merchant; determine a merchant rank for each merchant of the plurality of merchants based on the merchant popularity matrix and the candidate cardholder preference vector; determine a neutral merchant rank for each merchant of the plurality of merchants based on the retrieved electronic payment transaction information associated with the plurality of cardholders and a neutral preference vector including preference information values that are equal for each merchant of the plurality of merchants; determine a merchant score for each merchant of the plurality of merchants based on a difference between the merchant rank and the neutral merchant rank; and cause a list of recommended merchants including the at least one merchant to be displayed on a user device based on the determined merchant scores, wherein the user device is associated with the candidate cardholder. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer-implemented method of recommending at least one merchant of a plurality of merchants to a candidate cardholder using a merchant analytic (MA) computer system, wherein the MA computer system is in communication with a memory device, said method comprising:
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identifying a plurality of merchants located within a predefined geographical region; retrieving, at the MA computer system, electronic payment transaction information for a plurality of electronic payment card transactions involving a plurality of cardholders including the candidate cardholder and at least some of the plurality of merchants, the plurality of electronic payment transactions occurring within a predefined time period, the electronic payment transaction information received from a payment network; identifying from the electronic payment transaction information a subset of cardholders from the plurality of cardholders, each of the subset of cardholders having completed electronic payment transactions with at least two of the plurality of merchants; creating, based on the retrieved electronic payment transaction information associated with the subset of cardholders, a merchant popularity matrix, wherein the merchant popularity matrix includes a counter associated with each pair of merchants included within the plurality of merchants, wherein to create the matrix, an associated counter is incremented when a cardholder in the subset of cardholders completes electronic payment transactions at both merchants in the pair, and wherein, to reduce an effect of cardholder bias towards a single merchant, no counter in the merchant popularity matrix is incremented when a cardholder completes multiple electronic payment transactions at the same merchant; prompting the candidate cardholder to scan a transaction card with a user device associated with the candidate cardholder, wherein the user device generates scanned card data in response to scanning the transaction card; receiving the scanned card data from the user device; processing the scanned card data to request historical electronic transaction information from the payment network; receiving the historical electronic transaction data; determining candidate cardholder preference information for at least one candidate merchant of the plurality of merchants at least in part on the historical electronic transaction information; creating a candidate cardholder preference vector based on the candidate cardholder preference information, wherein the candidate cardholder preference vector represents a level of preference of the candidate cardholder for one merchant relative to at least one other merchant; determining a merchant rank for each merchant of the plurality of merchants based on the merchant popularity matrix and the candidate cardholder preference vector; determining a neutral merchant rank for each merchant of the plurality of merchants based on the retrieved electronic payment transaction information associated with the plurality of cardholders and a neutral preference vector including preference information values that are equal for each merchant of the plurality of merchants; determining, by the MA computer system, a merchant score for each merchant of the plurality of merchants based on a difference between the merchant rank and the neutral merchant rank; and causing a list of recommended merchants including the at least one merchant to be displayed on the user device based on the determined merchant scores. - View Dependent Claims (15, 16, 17, 18)
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19. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon for recommending at least one merchant of a plurality of merchants to a candidate cardholder, wherein when executed by at least one processor, the computer-executable instructions cause the processor to:
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identify a plurality of merchants located within a predefined geographical region; retrieve, from a payment network, electronic payment transaction information for a plurality of electronic payment card transactions involving a plurality of cardholders including the candidate cardholder and at least some of the plurality of merchants, the plurality of electronic payment transactions occurring within a predefined time period; identify from the electronic payment transaction information a subset of cardholders from the plurality of cardholders, each of the subset of cardholders having completed electronic payment transactions with at least two of the plurality of merchants; create, based on the retrieved electronic payment transaction information associated with the subset of cardholders, a merchant popularity matrix, wherein the merchant popularity matrix includes a counter associated with each pair of merchants included within the plurality of merchants, wherein to create the matrix, an associated counter is incremented when a cardholder in the subset of cardholders completes electronic payment transactions at both merchants in the pair, and wherein, to reduce an effect of cardholder bias towards a single merchant, no counter in the merchant popularity matrix is incremented when a cardholder completes multiple electronic payment transactions at the same merchant; receive data signals from the payment network including data associated with electronic payment transactions for the candidate cardholder; determine gratuity information for the candidate cardholder from the data signals; determine candidate cardholder preference information for at least one candidate merchant of the plurality of merchants based at least in part on the gratuity information determined from the data signals; create a candidate cardholder preference vector based on the candidate cardholder preference information, wherein the candidate cardholder preference vector represents a level of preference of the candidate cardholder for one merchant relative to at least one other merchant; determine a merchant rank for each merchant of the plurality of merchants based on the merchant popularity matrix and the candidate cardholder preference vector; determine a neutral merchant rank for each merchant of the plurality of merchants based on the retrieved electronic payment transaction information associated with the plurality of cardholders and a neutral preference vector including preference information values that are equal for each merchant of the plurality of merchants; determine a merchant score for each merchant of the plurality of merchants based on a difference between the merchant rank and the neutral merchant rank; and cause a list of recommended merchants including the at least one merchant to be displayed on a user device based on the determined merchant scores, wherein the user device is associated with the candidate cardholder. - View Dependent Claims (20)
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Specification