Method and system for transaction based profiling of customers within a merchant network

Abstract

A computer-based method for managing a profile for a cardholder is provided. The cardholder having an account associated with a payment card. The method includes electronically receiving, at the computer, transaction information for a cardholder for transactions with at least a first business entity and a second business entity, the transaction information including data representing each transaction initiated by the cardholder using the payment card and at least one subdivision within the first business entity, the transaction information further including data representing each transaction initiated by the cardholder using the payment card and the second business entity. The method also includes electronically storing the transaction information within the database, generating a profile of the stored transaction information for the cardholder, the profile including a type, a recency and a frequency of transactions initiated by the cardholder using the payment card and the at least one subdivision, grouping the cardholder into a single cluster with other cardholders registered within the payment card network based on the profile of the cardholder and the other cardholders, and outputting marketing information based on the cluster.

1 . A computer-based method for managing a loyalty profile for a cardholder, the cardholder having an account associated with a payment card, the payment card issued by an issuer and registered in a payment card network to the cardholder, said method performed using a computer coupled to a database, said method comprising:
 electronically receiving, at the computer, transaction information for a cardholder for transactions with at least a first business entity and a second business entity, the transaction information including data representing each transaction initiated by the cardholder using the payment card and at least one subdivision within the first business entity, the transaction information further including data representing each transaction initiated by the cardholder using the payment card and the second business entity;   electronically storing the transaction information within the database;   generating a profile of the stored transaction information for the cardholder, the profile including a type, a recency and a frequency of transactions initiated by the cardholder using the payment card and the at least one subdivision;   grouping the cardholder into a single cluster with other cardholders registered within the payment card network based on the profile of the cardholder and the other cardholders; and   outputting marketing information based on the cluster.   
     
     
         2 . A computer-based method in accordance with  claim 1 , wherein generating a profile comprises generating a profile of the stored transaction information for the cardholder, the profile including a type, a recency and a frequency of transactions initiated by the cardholder using the payment card and the second business entity. 
     
     
         3 . A computer-based method in accordance with  claim 1 , wherein the at least one subdivision within the first business entity includes at least one of a department, a class, a subclass, and a stock-keeping unit (SKU). 
     
     
         4 . A computer-based method in accordance with  claim 1 , further comprising receiving a profile of past transaction information for the cardholder account. 
     
     
         5 . A computer-based method in accordance with  claim 4 , further comprising transforming the transaction information at the computer to update the profile for the cardholder, the profile representing a pattern of usage of the payment card and the associated account by the cardholder. 
     
     
         6 . A computer-based method in accordance with  claim 1 , further comprising grouping the remaining other cardholders into a single respective cluster with others of the remaining cardholders based on the respective profiles of the other remaining cardholders. 
     
     
         7 . A computer-based method in accordance with  claim 1 , wherein outputting marketing information based on the cluster comprises generating campaigns intended to increase at least one of spend, frequency of visits, and breadth of spend with the first business entity by cardholders included within the cluster. 
     
     
         8 . A computer-based method in accordance with  claim 1 , wherein electronically receiving transaction information comprises electronically receiving SKU-level transaction information wherein the SKU-level is associated with a subdivision. 
     
     
         9 . A computer-based method in accordance with  claim 1 , wherein the computer is associated with a third-party payment card interchange network, and wherein electronically receiving transaction information further comprises:
 electronically receiving, at the computer, transaction information for each transaction initiated by the cardholder and associated with the interchange network including data representing a subdivision level of the transaction within the merchant, a quantity that describes a number of items purchased by SKU-level, a total price that describes the total price for the transaction at the SKU-level, a SKU transaction date that describes the date of the transaction, and a type of transaction being initiated.   
     
     
         10 . A computer-based method in accordance with  claim 1 , wherein grouping a plurality of cardholders into a single cluster comprises:
 mapping a cardholder profile to a vector in a multi-dimensional Euclidean space;   determining a distance from that vector to each a centroid of each cluster; and   assigning an identification of the nearest centroid to the cardholder profile.   
     
     
         11 . A computer-based method in accordance with  claim 10 , wherein mapping a cardholder profile to a vector in a multi-dimensional Euclidean space comprises mapping a cardholder profile to a vector in a Euclidean space having greater than twelve dimensions. 
     
     
         12 . A computer-based method in accordance with  claim 10 , wherein mapping a cardholder profile to a vector in a multi-dimensional Euclidean space comprises mapping a cardholder profile to a vector in a Euclidean space having approximately seventy-two dimensions. 
     
     
         13 . A computer-based method in accordance with  claim 1 , wherein electronically receiving transaction information of the cardholder further comprises:
 electronically receiving first transaction information of the cardholder, the first transaction information including data representing each transaction for each subdivision the cardholder initiates using the payment card and each transaction associated with the cardholder account for a first predetermined period of time;   determining a first profile including a cluster assignment for the cardholder using the first transaction information;   electronically receiving updated transaction information of the cardholder, the updated transaction information including data representing each transaction using the payment card and the corresponding subdivision and each transaction associated with the cardholder account for a second predetermined period of time, the second predetermined period of time being more recent than the first predetermined period of time; and   determining an updated cluster assignment and profile for the cardholder from the updated transaction information and the first profile.   
     
     
         14 . A computer-based method in accordance with  claim 1 , wherein outputting marketing information based on the cluster further comprises selecting at least one cluster related to a marketing target wherein the marketing target is selected from a plurality of cardholders based on a similarity of transactions by the cardholders with the marketing target. 
     
     
         15 . A computer-based method in accordance with  claim 14 , wherein outputting marketing information based on the clusters comprises selecting a model package including a plurality of cardholders and transaction data associated with each of the plurality of cardholders. 
     
     
         16 . A computer-based method in accordance with  claim 15 , wherein outputting marketing information based on the cluster comprises selecting a model package wherein the associated transaction data includes at least one of a rate of spending for the cardholder in at least one of a predetermined subdivision, a number of different subdivisions in which the cardholder has conducted transactions, a number of trips made to the first business entity, an indication of timing of trips to the first business entity. 
     
     
         17 . A computer-based method in accordance with  claim 1 , wherein outputting marketing information based on the clusters further comprises outputting a profile report of the cardholder including a subdivision spend indicator, the subdivision spend indicator representative of changes in cardholder spending activities by comparing a current spend amount of the cardholder with the payment card in a subdivision to an average spend amount of the cardholder with the payment card in the subdivision. 
     
     
         18 . A network-based system for determining a profile for a cardholder account, the profile associated with a subdivision of a business entity, the cardholder account associated with a payment card used to initiate financial transactions over a third-party interchange network, the payment card issued by an issuer to the cardholder, said system comprising:
 a client computer system;   a database; and   a server system configured to be coupled to the client computer system and the database, said server system associated with the interchange network, said server system configured to:   receive transaction information of the cardholder, the transaction information including data representing each transaction in the subdivision of the business entity using the payment card and associated with the cardholder account;   store the transaction information within the database; and   generate the profile for the cardholder account, the profile representing a pattern of usage of the cardholder in each subdivision of the business entity by the cardholder wherein the at least one subdivision within the first business entity includes at least one of a department, a class, a subclass, and a stock-keeping unit (SKU).   
     
     
         19 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to receive, from the client system, transaction information for each transaction using the payment card including data representing a type of transaction, a purchasing frequency, a type of purchase, the subdivision in which the transaction occurred, a time the transaction occurred. 
     
     
         20 . A network-based system in accordance with  claim 19 , wherein said server system is further configured to determine a spend breadth of the cardholder when the spend breadth indicates a relative number of subdivisions of the business entity in which purchases were made by the cardholder. 
     
     
         21 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to:
 receive first transaction information of the cardholder, the first transaction information including data representing transactions using the payment card in at least one of a plurality of subdivisions for a first predetermined period of time;   determine a first profile for the cardholder account from the first transaction information;   receive updated transaction information of the cardholder, the updated transaction information including data representing transactions using the payment card in at least one of a plurality of subdivisions for a second predetermined period of time, the second predetermined period of time being more recent than the first predetermined period of time; and   determine an updated profile for the cardholder account from the updated transaction information and the first profile.   
     
     
         22 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to determine a cluster of the cardholder based on a grouping of a plurality of cardholders having similar transaction data in at least one subdivision. 
     
     
         23 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to output a profile report of the cardholder including a subdivision level retail activity of an account, the subdivision level retail activity showing cardholder transactions in one or more subdivisions including a number of items purchased and a cost amount of the items purchased. 
     
     
         24 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to output a profile report of the cardholder including a trip indicator, the trip indicator showing cardholder trip activities to one or more subdivisions including a frequency of trips and a recency of trips. 
     
     
         25 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to output a profile report of the cardholder including a spend breadth indicator, the spend breadth indicator showing changes in the subdivisions the cardholder uses the payment card. 
     
     
         26 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to:
 electronically store cardholder data in a rewards system data warehouse;   electronically store transactional data in a relational data warehouse;   electronically store a current cardholder profile in a SKU (stock-keeping unit) data warehouse;   electronically store cardholder account information in the SKU data warehouse; and   electronically store model package data in a model package data warehouse.   
     
     
         27 . A network-based system in accordance with  claim 18 , wherein said server system further comprises a transaction gatherer component configured to collect current cardholder data stored in the rewards system data warehouse and current transactional data stored in the relational data warehouse, and transmit the collected data to the transaction batch component. 
     
     
         28 . A network-based system in accordance with  claim 18 , wherein said server system further comprises a transaction batch component configured to format the collected data, and transmit the formatted data to the profile event loop component. 
     
     
         29 . A network-based system in accordance with  claim 18 , wherein said server system further comprises a profile event loop component configured to determine the profile for the cardholder using the formatted data and at least one model from the model package data warehouse, and store the determined profile in the profile data warehouse as an updated profile. 
     
     
         30 . A network-based system in accordance with  claim 18 , wherein said server system further comprises a post processing component configured to perform cluster scoring and post-process reporting. 
     
     
         31 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to store a plurality of models within the model package data warehouse, wherein the plurality of models includes at least one of a subdivision model, a trip model, and a breadth model for generating at least a portion of the profile for the cardholder. 
     
     
         32 . A network-based system in accordance with  claim 18 , wherein said server system is further configured to update an existing profile of the cardholder using subdivision activity data for the cardholder, the subdivision activity data representing a retail transaction behavior of the cardholder in each of the subdivisions, using trip activity data for the cardholder, the trip activity data representing a trips to each subdivision behavior of the cardholder, and using breadth of purchase data for the subdivisions by the cardholder, the breadth of purchase data representing a number of different subdivisions in which the payment card was used. 
     
     
         33 . A computer program embodied on a computer readable medium for determining a profile based on a SKU (stock-keeping unit) of items purchased for a cardholder, the cardholder having an account associated with a payment card, the payment card issued by an issuer to the cardholder, said program comprises at least one code segment executable by a computer to instruct the computer to:
 receive transaction information of the cardholder, the transaction information including data representing a SKU of items purchased in each transaction using the payment card and associated with the cardholder account;   record the transaction information; and   generate the profile for the cardholder, the profile representing a pattern of usage of the payment card and the associated account by the cardholder for items based on the SKU of each of the items in each transaction at a first business entity.   
     
     
         34 . A computer program in accordance with  claim 33 , wherein said program comprises at least one code segment executable by the computer to instruct the computer to receive transaction information of the cardholder, the transaction information including data representing transactions using the payment card and associated with the cardholder account at a second business entity. 
     
     
         35 . A computer program in accordance with  claim 33 , wherein said program comprises at least one code segment executable by the computer to instruct the computer to receive transaction information of the cardholder, the transaction information including data representing a SKU of items purchased using the payment card and associated with the cardholder account at a second business entity. 
     
     
         36 . A computer program in accordance with  claim 33 , wherein said program comprises at least one code segment executable by the computer to instruct the computer to receive transaction information for each transaction using the payment card including data representing a type of transaction, a purchasing frequency, a type of purchases, the subdivision in which the transaction occurred, and a time the transaction occurred. 
     
     
         37 . A computer program in accordance with  claim 33 , wherein said program comprises at least one code segment executable by the computer to instruct the computer to:
 receive first transaction information of the cardholder, the first transaction information including data representing the SKU of items purchased using the payment card for a first predetermined period of time;   determine a first profile including a cluster assignment for the cardholder from the first transaction information;   receive updated transaction information of the cardholder, the updated transaction information including data representing SKU information of each transaction using the payment card for a second predetermined period of time, the second predetermined period of time being more recent than the first predetermined period of time; and   determine an updated cluster assignment and profile for the cardholder from the updated transaction information and the first profile.