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REAL-TIME MARKETING CAMPAIGN STIMULI SELECTION BASED ON USER RESPONSE PREDICTIONS

  • US 20160210657A1
  • Filed: 12/17/2015
  • Published: 07/21/2016
  • Est. Priority Date: 12/30/2014
  • Status: Abandoned Application
First Claim
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1. A computer implemented method comprising:

  • storing in a computer, a plurality of touchpoint encounters that represent marketing messages exposed to a plurality of users;

    identifying an audience segment of users comprising a subset of the users;

    sorting data for the touchpoint encounters in the computer to separate into converting user data, which comprises touchpoint encounters for the users that exhibited a positive response to the marketing message, and non-converting user data that comprises touchpoint encounters for the users that exhibited a negative response to the marketing message;

    retrieving, from storage, the converting user data and the non-converting user data;

    training, using machine-learning techniques in a computer, the converting user data and the non-converting user data as training data to generate a touchpoint response predictive model that defines a plurality of sets of touchpoint encounters that reflect a positive response to the marketing message;

    receiving at least one user interaction data record corresponding to a detected online user touchpoint encounter associated with a user of the audience segment of users for presentation of one or more marketing campaigns;

    predicting, using the touchpoint response predictive model, and responsive to the user interaction data record, at least one touchpoint encounter from a set of touchpoint encounters defined for the audience segment of users; and

    determining one or more selected stimuli parameters for the user of the audience segment of users based on the predicted touchpoint to effectuate the marketing campaigns.

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