Method of analyzing credit card transaction data
First Claim
1. A method of analyzing customer purchase transaction data to provide targeted offerings to selected customers identified by the analysis as more likely than other customers to respond to the targeted offerings, wherein the transaction data comprises bulk transaction data relating to a multiplicity of purchase transactions effected by a plurality of customers with a plurality of merchants, the bulk transaction data comprising a multiplicity of records each relating to a purchase transaction by one of the plurality of customers and identifying the specific customer and the merchant of the purchase transaction, said method comprising the steps of:
- associating each of said plural merchants with characterizing fields in a plurality of category taxonomies, said fields identifying possible characteristics of the plural merchants, by identifying which selected ones of said fields are relevant characterizers of each of said plural merchants;
correlating the plural bulk transaction data records with the associated characterizing fields of said plural merchants to generate, for each said taxonomy, a first weighted table of the purchase transactions at the plural merchants for each of said characterizing fields of the said each taxonomy;
correlating, for each of said plural customers, the transaction data records of said each of the plural customers with the associated characterizing fields of said plural merchants to generate, for each said taxonomy, a second weighted table of the purchase transactions of the said each of the plural customers at the plural merchants for each of said characterizing fields of the said each taxonomy;
comparing for said each of the plural customers, for each of said characterizing fields of the said each taxonomy, the weights of the first and second tables, to calculate for each of said characterizing fields of the said each taxonomy a difference of said weights of the first and second tables; and
identifying for said each of the plural customers, in said each taxonomy, from among the said calculated differences of said weights of the first and second tables for said plural characterizing fields, a greatest of said calculated differences;
said greatest of said calculated differences in each of said taxonomies identifying a characteristic of said each of the plural customers for use in targeted offerings to said each of the plural customers based on said identified characteristic.
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Accused Products
Abstract
A method of analyzing debit and credit card transaction data to provide interpretations of customer purchasing patterns for use by third parties, such as financial services marketers, in providing offers and incentives to targeted groups of consumers. Bulk credit card or debit card transaction data that has been gathered for a large sample of cardholders is obtained, a multi-step process is applied to prepare the data for analysis, multiple categories of marketing “intelligence” or decisions are attached to each transaction contained in the bulk transaction data, a summation of all of the different intelligence categories for each cardholder and for the entire sample is performed to create comparative normalizations, and a score in vector form is generated for each customer based on differences or variations in the way in which that customer shops relative to the bulk-derived normalized data for each field or dimension within the comparative normalization.
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Citations
7 Claims
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1. A method of analyzing customer purchase transaction data to provide targeted offerings to selected customers identified by the analysis as more likely than other customers to respond to the targeted offerings, wherein the transaction data comprises bulk transaction data relating to a multiplicity of purchase transactions effected by a plurality of customers with a plurality of merchants, the bulk transaction data comprising a multiplicity of records each relating to a purchase transaction by one of the plurality of customers and identifying the specific customer and the merchant of the purchase transaction, said method comprising the steps of:
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associating each of said plural merchants with characterizing fields in a plurality of category taxonomies, said fields identifying possible characteristics of the plural merchants, by identifying which selected ones of said fields are relevant characterizers of each of said plural merchants;
correlating the plural bulk transaction data records with the associated characterizing fields of said plural merchants to generate, for each said taxonomy, a first weighted table of the purchase transactions at the plural merchants for each of said characterizing fields of the said each taxonomy;
correlating, for each of said plural customers, the transaction data records of said each of the plural customers with the associated characterizing fields of said plural merchants to generate, for each said taxonomy, a second weighted table of the purchase transactions of the said each of the plural customers at the plural merchants for each of said characterizing fields of the said each taxonomy;
comparing for said each of the plural customers, for each of said characterizing fields of the said each taxonomy, the weights of the first and second tables, to calculate for each of said characterizing fields of the said each taxonomy a difference of said weights of the first and second tables; and
identifying for said each of the plural customers, in said each taxonomy, from among the said calculated differences of said weights of the first and second tables for said plural characterizing fields, a greatest of said calculated differences;
said greatest of said calculated differences in each of said taxonomies identifying a characteristic of said each of the plural customers for use in targeted offerings to said each of the plural customers based on said identified characteristic. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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Specification