Method and apparatus for targeting best customers based on spend capacity

Abstract

Share of Wallet (“SOW”) is a modeling approach that utilizes various data sources to provide outputs that describe a consumers spending capability, tradeline history including balance transfers, and balance information. These outputs can be appended to data profiles of customers and prospects and can be utilized to support decisions involving prospecting, new applicant evaluation, and customer management across the lifecycle. A SOW score focusing on a consumer's spending capability can be used in the same manner as a credit bureau score.

What is claimed is: 
     
         1 . A method of targeted marketing, comprising:
 segmenting, by a targeted marketing computer-based system, existing consumers into categories, wherein the segmented existing consumer data is stored in a memory of the computer-based system;   modeling, by the computer-based system, characteristics of the existing consumers using individual and aggregate data of the existing consumers, including tradeline data, internal consumer data, and consumer panel data;   determining, by the computer-based system, correlations between the categories and the characteristics of the existing consumers;   targeting, by the computer-based system, consumers having characteristics correlated to a particular category, wherein the targeting comprises:
 estimating identifying, by the computer-based system, an existence of an estimated previous balance transfer of a consumer, 
 wherein the existence of the estimated previous balance transfer is estimated based on a change in the magnitude of a balance on at least one tradeline of the individual consumer during a given time period as compared to a balance of the at least one tradeline of the individual consumer in a time period prior to the given time period such that the change meets or exceeds a given threshold; 
 estimating characteristics of the consumer based on, for a consumer, tradeline data of the consumer that comprises a spend amount associated with the consumer, balance transfers of the consumer, and a model of consumer spending patterns, 
 offsetting, by the computer-based system, the spend capacity by the estimated previous balance transfer; 
 determining a subset of consumers having characteristics similar to the characteristics correlated to a particular category; and 
 targeting the subset of consumers. 
   
     
     
         2 . The method of  claim 1 , wherein the particular category represents preferred consumers. 
     
     
         3 . The method of  claim 1 , wherein the targeted consumers are prospective consumers. 
     
     
         4 . The method of  claim 1 , wherein the targeted consumers are existing consumers. 
     
     
         5 . The method of  claim 1 , wherein consumers are targeted based on an individual spend capacity. 
     
     
         6 . The method of  claim 1 , wherein the estimating characteristics of the consumer comprises determining spend capacities for the consumer. 
     
     
         7 . The method of  claim 1 , wherein the modeling the characteristics of the existing consumers comprises modeling consumer spending patterns. 
     
     
         8 . The method of  claim 1 , further comprising:
 identifying the characteristics common to preferred consumers,   wherein the particular category represents preferred consumers; and   targeting consumers having the characteristics common to the preferred consumers.   
     
     
         9 . The method of  claim 1 , wherein the targeted consumers are existing consumers. 
     
     
         10 . The method of  claim 1 , further comprising targeting consumers identified as preferred consumers. 
     
     
         11 . The method of  claim 1 , further comprising:
 estimating a spend capacity for consumers using, for a consumer, tradeline data of the consumer, balance transfer data of the consumer, and the model of consumer spending patterns; and   targeting consumers having spend capacities similar to spend capacities of preferred consumers.   
     
     
         12 . A system comprising:
 a targeted marketing processor,   a tangible, non-transitory memory configured to communicate with the processor,   the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising:
 segmenting, by processor, existing consumers into categories, wherein the segmented existing consumer data is stored in a memory of the computer-based system; 
 modeling, by the processor, characteristics of the existing consumers using individual and aggregate data of the existing consumers, including tradeline data, internal consumer data, and consumer panel data; 
 determining, by the processor, correlations between the categories and the characteristics of the existing consumers; 
 targeting, by the processor, consumers having characteristics correlated to a particular category, wherein the targeting comprises:
 estimating identifying, by the processor, an existence of an estimated previous balance transfer of a consumer, 
 wherein the existence of the estimated previous balance transfer is estimated based on a change in the magnitude of a balance on at least one tradeline of the individual consumer during a given time period as compared to a balance of the at least one tradeline of the individual consumer in a time period prior to the given time period such that the change meets or exceeds a given threshold; 
 estimating characteristics of the consumer based on, for a consumer, tradeline data of the consumer that comprises a spend amount associated with the consumer, balance transfers of the consumer, and a model of consumer spending patterns, 
 offsetting, by the processor, the spend capacity by the estimated previous balance transfer; 
 determining a subset of consumers having characteristics similar to the characteristics correlated to a particular category; and 
 targeting the subset of consumers. 
 
   
     
     
         13 . The system of  claim 12 , wherein the particular category represents preferred consumers. 
     
     
         14 . The system of  claim 12 , wherein the targeted consumers are prospective consumers. 
     
     
         15 . The system of  claim 12 , wherein the targeted consumers are existing consumers. 
     
     
         16 . The system of  claim 12 , wherein consumers are targeted based on an individual spend capacity. 
     
     
         17 . The system of  claim 12 , wherein the estimating characteristics of the consumer comprises determining spend capacities for the consumer. 
     
     
         18 . The system of  claim 12 , wherein the modeling the characteristics of the existing consumers comprises modeling consumer spending patterns. 
     
     
         19 . The system of  claim 12 , further comprising:
 identifying the characteristics common to preferred consumers,   wherein the particular category represents preferred consumers; and   targeting consumers having the characteristics common to the preferred consumers.   
     
     
         20 . An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a targeted marketing computer-based system, cause the computer-based system to perform operations comprising:
 segmenting, by the computer-based system, existing consumers into categories, wherein the segmented existing consumer data is stored in a memory of the computer-based system;   modeling, by the computer-based system, characteristics of the existing consumers using individual and aggregate data of the existing consumers, including tradeline data, internal consumer data, and consumer panel data;   determining, by the computer-based system, correlations between the categories and the characteristics of the existing consumers;   targeting, by the computer-based system, consumers having characteristics correlated to a particular category, wherein the targeting comprises:
 estimating identifying, by the computer-based system, an existence of an estimated previous balance transfer of a consumer, 
 wherein the existence of the estimated previous balance transfer is estimated based on a change in the magnitude of a balance on at least one tradeline of the individual consumer during a given time period as compared to a balance of the at least one tradeline of the individual consumer in a time period prior to the given time period such that the change meets or exceeds a given threshold; 
 estimating characteristics of the consumer based on, for a consumer, tradeline data of the consumer that comprises a spend amount associated with the consumer, balance transfers of the consumer, and a model of consumer spending patterns, 
 offsetting, by the computer-based system, the spend capacity by the estimated previous balance transfer; 
 determining a subset of consumers having characteristics similar to the characteristics correlated to a particular category; and 
 targeting the subset of consumers.