Predicting interpurchase time in a retail environment using customer-product networks: An empirical study and evaluation.

•We leverage similarities in customer purchases for product attrition prediction.•We extract an extensive feature set from customer-product graphs.•We boost predictive performance by 6% and product identification by 20%.•Our model illustrates the importance of transactional data for marketing.•We show the advantage of network-based analytics in offline retail.