User Modeling for Churn Prediction in E-Commerce

In the domain of e-commerce, acquiring a new customer is generally more expensive than keeping the existing ones. A successful prediction of churn of a specific customer provides an opportunity to change his/her decision to leave. In this paper, we propose a novel complex user model focused on the user churn intent prediction. The idea of our model is based on composing of multiple sets of features representing user's interaction with the web application. The performance of our model is evaluated indirectly by the prediction of churn, using real data from online retailers. The results show that the prediction using the proposed model outperforms the churn prediction based on baseline models across two domains.