CPC G06Q 30/0244 (2013.01) [G06Q 30/0201 (2013.01); G06Q 30/0239 (2013.01); G06Q 30/0271 (2013.01); G06N 20/00 (2019.01)] | 16 Claims |
1. A method for selecting a set of offers comprising:
defining, by one or more processors, values for a plurality of variables;
applying, by one or more processors, heuristics to filter a set of possible offers to a first set of offers;
generating, by one or more processors, an offer vector for each offer in the first set of offers, wherein each offer vector includes a variable value for each variable of the plurality of variables and a success metric of the offer corresponding to the offer vector, wherein the success metric of the offer is a weighted composite of at least two of redemption rates, speed of deletion, shares, and saves;
generating, by one or more processors, a derivative table based on the generated offer vectors, wherein the derivative table comprises a plurality of differential vectors, wherein each differential vector comprises pair-wise differences between variable values for a pair of the generated offer vectors and a differential success score representing a difference of the success metrics of the pair of generated offer vectors;
training, by one or more processors, at least one of a neural network or a decision tree based on the derivative table;
generating, by one or more processors, a score for each offer in the first set of offers using the at least one of a neural network or a decision tree;
generating, by one or more processors, correlations of the variable values to the generated scores to identify winning variable values;
generating, by one or more processors, a test set of offers using permutations of the winning variable values; and
transmitting the set of test offers to a plurality of users.
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