Targeted Incentives Based Upon Predicted Behavior
OwnerMark Davis, Patrick Venkerinventors
Life of this patent
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Abstract
A computer implemented system and method employs predictive analysis on purchase data to determine product categories for which a consumer is statistically likely to purchase and either has not purchased or has not purchased at the statistically expected level at a particular retail store or chain of retail stores, and responds by generating a purchase incentive offer for that consumer requiring purchase of a product in the target category as a condition for the consumer obtaining the offered incentive.
Claims23
A computerized method for selecting consumers to which to provide purchase incentive offers for purchase of products, comprising:
- (1) storing in computer memory purchase history data for purchases from one or more retail stores during a certain time period, wherein said purchase history data includes CID records, wherein each CID record stores in association with one another at least CID, PIDs of products purchased in transactions associated with said at least one CID, and quantity of product items having said PIDs;
- (2) defining a Target Category Correlation Function (TCCF) for a target category, wherein said TCCF is a function of at least quantity of purchase of products in non target categories;
- (3) applying statistical analysis to at least a subset of said purchase history records and said TCCF to define values of coefficients for terms of said TCCF, said values corresponding to correlation of purchase of products in non target categories to purchase of products in said target category;
- (4) applying said TCCF to purchase history records associated with CIDs to obtain CID TCCF values for said CIDs;
- (5) deciding whether to provide purchase incentive offers for purchase of products in said target category to consumers associated with said CIDs based at least in part upon said CID TCCF values.
A computer system for selecting consumers to which to provide purchase incentive offers for purchase of products, comprising:
- at least one central processing unit;
- an input device;
- an output device;
- (1) computer memory storing purchase history data for purchases from one or more retail stores during a certain time period, wherein said purchase history data includes CID records, wherein each CID record stores in association with one another at least CID, PIDs of products purchased in transactions associated with said at least one CID, and quantity of product items having said PIDs;
- (2) code stored in computer memory defining a Target Category Correlation Function (TCCF) for a target category, wherein said TCCF is a function of at least quantity of purchase of products in non target categories;
- (3) code stored in computer memory for applying statistical analysis to at least a subset of said purchase history records and said TCCF to define values of coefficients for terms of said TCCF, said values corresponding to correlation of purchase of products in non target categories to purchase of products in said target category;
- (4) code stored in computer memory for applying said TCCF to purchase history records associated with CIDs to obtain CID TCCF values for said CIDs;
- (5) code stored in computer memory for deciding whether to provide purchase incentive offers for purchase of products in said target category to consumers associated with said CIDs based at least in part upon said CID TCCF values.
Dependencies are inferred from the claim text.