As companies increase their efforts in retaining customers, being able to predict accurately ahead of time, whether a customer will churn in the foreseeable future is an extremely powerful tool for any marketing team. The paper describes in depth the application of Deep Learning in the problem of churn prediction. Using abstract feature vectors, that can generated on any subscription based comp...

Customer churn is a main concern of most firms in all industries. The aim of customer churn prediction is detecting customers with high tendency to leave a company. Although, many modeling techniques have been used in the field of churn prediction, performance of ensemble methods has not been thoroughly investigated yet. Therefore, in this paper, we perform a comparative assessment of the perfo...

The defection or churn of customers represents an important concern for any company and a central matter of interest in customer base analysis. An additional complication arises in non-contractual settings, where the characteristics that should be observed to saying that a customer has totally or partially defected are not clearly defined. As a matter of fact, different definitions of the churn...

Customer churn, the loss of customers for a company, is one of the biggest loss of revenue for Verizon Wireless and other wireless telecommunications companies. Many companies use the lifetime value of a customer, the expected future cash flow from a particular customer, to determine long-term allocation of resources and human capital. As a result, the sudden defection of customers can greatly ...

During the last two decades, the mobile communication has become a dominant medium of communication. In numerous countries, especially the developed ones, the market is saturated to the extent that each new customer must be won over from the competitors. Advancements in technology and rapid improvements in telecom industry have provided customers with many choices. Customer retention is one of ...

In the process of user churn modeling, due to imbalance between lost users and retained users, use traditional classification models often cannot accurately comprehensively identify with tendency. To address this issue, it is not sufficient simply increase misclassification cost minority class samples in cost-sensitive methods. This paper proposes using Focal Loss hard example mining technique ...

The present study attempts to establish a new framework to speculate customer lifetime value by a stochastic approach. In this research the customer lifetime value is considered as combination of customer’s present and future value. At first step of our desired model, it is essential to define customer groups based on their behavior similarities, and in second step a mechanism to count current ...