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Methods and systems for predicting consumer behavior from transaction card purchases

  • US 10,430,803 B2
  • Filed: 12/23/2008
  • Issued: 10/01/2019
  • Est. Priority Date: 12/23/2008
  • Status: Active Grant
First Claim
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1. A computer-based method for predicting consumer behavior within a predetermined time period, said method performed using a payment processor computer device coupled to a database, said method comprising:

  • recording, by the payment processor computer device, electronic consumer data in the database for each consumer of a global population of consumers including historical purchases made by each consumer, including at least one electronic transaction initiated by a consumer using a transaction card at a point-of-sale (POS) device;

    defining, by the payment processor computer device, a life event by assigning spending variables to the life event, wherein a spending variable represents a quantity of consumer spending associated with one or more of (i) a particular merchant and (ii) a particular type of good or service;

    generating an anticipated spend for each spending variable assigned to the life event by extrapolating a historical actual spend based on the historical purchases, wherein the anticipated spend represents anticipated spending in each spending variable assigned to the life event;

    calculating a residual value of a determined variance between the anticipated spend and an actual spend for each consumer by calculating a quotient of (i) the difference between the anticipated spend and the actual spend and (ii) the anticipated spend;

    determining that a residual value of a determined variance between the anticipated spend and the actual spend for each consumer exceeds a predefined threshold;

    assigning, by the payment processor computer device, the consumer to a sample group, wherein the sample group represents consumers that are experiencing the life event;

    generating, by the payment processor computer device, a predictive model based on historical purchases made by consumers within the sample group;

    applying, by the payment processor computer device, the predictive model to predict each consumer within the global population and outside of the sample group that will experience the life event; and

    outputting, by the payment processor computer device, a list of consumers outside of the sample group that are predicted to experience the life event within the predetermined time period.

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