Customer defection is critically important since it leads to serious business loss. Therefore, investigating methods to identify defecting customers (i.e. churners) has become a priority for telecommunication operators. In this paper, a churn prediction framework is proposed aiming at enhancing the ability to forecast customer churn. The framework combine two heuristic approaches: Self Organizi...

Companies’ interest in customer relationship modelling and key issues such as customer lifetime value and churn has substantially increased over the years. However, the complexity of building, interpreting and applying these models creates obstacles for their implementation. The main contribution of this paper is to show how domain knowledge can be incorporated in the data mining process for ch...

Churn prediction is a Big Data domain, one of the most demanding use cases recent time. It also critical indicators healthy and growing business, irrespective size or channel sales. This paper aims to develop deep learning model for customers’ churn in e-commerce, which main contribution article. The experiment was performed over real e-commerce data where 75% buyers are one-off customers. base...