Next product purchase and lapse predicting tool

Abstract

A processor-based system and method retrieve customer purchase history information from an internal customer purchase history database for a plurality of customer records representing customers that previously purchased products of an enterprise, and retrieve customer profile information for each customer record. The processor executes a predictive machine learning model to determine a set of product purchase scores for each of the customers by applying a logistic regression model utilizing gradient boosting to the customer purchase history information and the customer profile information. The processor classifies the customers into a target customer group and a non-target customer group by applying a classification criterion to the set of product purchase scores, and generates a report of customers in the target customer group including highest product purchase scores and products recommended for cross-sale. In some embodiments, the predictive machine learning model is configured to forecast likelihood that given customers will lapse in payment.