User segmentation using predictive model interpretation

A system comprising:

• a non-transitory computer-readable medium storing computer-executable program instructions for determining user segments created by a predictive model based on user behavioral data;
• and
• a processing device communicatively coupled to the non-transitory computer-readable medium for executing the computer-executable program instructions, wherein executing the computer-executable program instructions configures the processing device to perform operations comprising:
• accessing training data comprising a plurality of instances of user interaction data, each instance of the user interaction data associated with a user interaction within a computer network and comprising a plurality of attributes and an outcome associated with the user interaction, wherein the training data were previously used to train a predictive model with an outcome of interest to obtain a trained predictive model;
• generating a set of conditions from the training data, each condition comprising an attribute and a range of values for the attribute;
• generating multiple instances of input data from the training data, wherein each instance of input data comprises at least one instance of user interaction data from the training data satisfying a condition of the set of conditions;
• determining a set of relevant conditions to the trained predictive model from the set of conditions based on the multiple instances of input data;
• generating one or more user segments based on the set of relevant conditions;
• and
• presenting the one or more user segments to a user interface.

A non-transitory computer-readable storage medium storing computer-executable program instructions, wherein when executed by a processing device, the computer-executable program instructions cause the processing device to perform operations comprising:

• accessing training data comprising a plurality of instances of user interaction data, each instance of the user interaction data associated with a user interaction within a computer network and comprising a plurality of attributes and an outcome associated with the user interaction, wherein the training data were previously used to train a predictive model with an outcome of interest to obtain a trained predictive model;
• generating a set of conditions from the training data, each condition comprising an attribute and a range of values for the attribute;
• generating multiple instances of input data from the training data, wherein each instance of input data comprises at least one instance of user interaction data from the training data satisfying a condition of the set of conditions;
• determining a set of relevant conditions to the trained predictive model from the set of conditions based on the multiple instances of input data;
• generating one or more user segments based on the set of relevant conditions;
• and
• presenting the one or more user segments to a user interface.