Method and apparatus for targeting best customers based on spend capacity
AssigneeAmerican Express Travel Related Services Company, Inc.
InventorsKathleen Haggerty, Chao Yuan, Benedict Okoh, Peter Williamson
Life of this patent
Estimating the term…
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. “Best customer” models can correlate SOW outputs with various customer groups for targeted marketing.
Claims28
A method of targeted marketing, comprising:
- (a) modeling consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;
- (b) determining spend capacities for existing customers using, for each existing customer, tradeline data of the customer, balance transfer data of the customer, and the model of consumer spending patterns;
- and
- (c) identifying preferred customers based on spend capacity.
A method of targeted marketing, comprising:
- (a) segmenting existing customers into categories;
- (b) modeling characteristics of the existing customers using individual and aggregate data of the existing customers, including tradeline data, internal customer data, and consumer panel data;
- (c) determining correlations between the categories and the characteristics of the existing customers;
- and
- (d) targeting consumers having characteristics correlated to a particular category.
An apparatus for targeted marketing, comprising:
- a processor;
- and
- a memory in communication with the processor, wherein the memory stores a plurality of processing instructions for directing the processor to:
- model consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;
- determine spend capacities for existing customers using, for each existing customer, tradeline data of the customer, balance transfer data of the customer, and the model of consumer spending patterns;
- and
- identify preferred customers based on spend capacity.
An apparatus for targeted marketing, comprising:
- a processor;
- and
- a memory in communication with the processor, wherein the memory stores a plurality of processing instructions for directing the processor to:
- segment existing customers into categories;
- model characteristics of the existing customers using individual and aggregate data of the existing customers, including tradeline data, internal customer data, and consumer panel data;
- determine correlations between the categories and the characteristics of the existing customers;
- and
- identify consumers having characteristics correlated to a particular category.
A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to perform targeted marketing, the control logic comprising:
- first computer readable program code means for causing the computer to model consumer spending patterns using individual and aggregate consumer data, including tradeline data, internal customer data, and consumer panel data;
- second computer readable program code means for causing the computer to determine spend capacities for existing customers using, for each existing customer, tradeline data of the customer, balance transfer data of the customer, and the model of consumer spending patterns;
- and
- third computer readable program code means for causing the computer to identify preferred customers based on spend capacity.
A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to perform targeted marketing, the control logic comprising:
- first computer readable program code means for causing the computer to segment existing customers into categories;
- second computer readable program code means for causing the computer to model characteristics of the existing customers using individual and aggregate data of the existing customers, including tradeline data, internal customer data, and consumer panel data;
- third computer readable program code means for causing the computer to determine correlations between the categories and the characteristics of the existing customers;
- and
- fourth computer readable program code means for causing the computer to identify consumers having characteristics correlated to a particular category.
Dependencies are inferred from the claim text.