Data-driven personalized assortment optimization by considering customers’ value and their risk of churning: Case of online grocery shopping

•Developing dynamic assortment customization to increase the e-tailer’s profit.•Reducing the risk of customer churn in the case of an imbalanced inventory.•Using the survival analysis technique to find at-risk customers.•Elaborating the applicably of the approach using a real case study.