Customer churn has been stated as one of the main reasons of profitability losses in the telecommunications industry. As such, it seems critical to have an a priori knowledge about the risk of a given customer to churn at any moment, in order to take preventive measures to avoid the defection of potentially profitable customers. This study intends to develop a duration model of the residential ...

The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customer complaints data and provides a comparative analysis of neural networks, regression trees and regression in their capabilities of predicting customer churn. Keywords—Churn, Decision Trees, Neural Netwo...

Retaining customers is one of the most critical challenges in the maturing mobile telecommunications service industry. Using customer transaction and billing data, this study investigates determinants of customer churn in the Korean mobile telecommunications service market. Results indicate that call quality-related factors influence customer churn; however, customers participating in membershi...

There is a growing tendency for more companies to develop towards subscription business model. Under such trend, it important learn about the customer churn rate within business, from and adjust strategies accordingly. This paper aims predict in models using variety of machine learning algorithms. Through comparing results different algorithms, best algorithms can be identified so that provides...

Recently, telecommunication companies have been paying more attention toward the problem of identification of customer churn behavior. In business, it is well known for service providers that attracting new customers is much more expensive than retaining existing ones. Therefore, adopting accurate models that are able to predict customer churn can effectively help in customer retention campaign...

Predicting customer churn is a classic data mining problem. Telecommunications providers have a long history of analyzing customer usage patterns to predict churn. Many other industries, such as banking, routinely analyze customer behavior to predict customer satisfaction and renewal rates. The Software as a Service (SaaS) model enables software vendors to collect customer usage data that is no...

Customer retention and customer churn are key metrics of interest to marketers, but little attention has been placed on linking the different reasons for which customers churn to their value to a contractual service provider. In this article, we put forth a hierarchical competing risk model to jointly model when customers choose to terminate their service and why. Some of these reasons for chur...

Customer value analysis is critical for a good marketing and a customer relationship management strategy. An important component of this strategy is the customer retention rate. Customer retention rate has a strong impact on the customer lifetime value, and understanding the true value of a possible customer churn will help the company in its customer relationship management. Conventional stati...

This chapter proposes an integrated methodological system of telecommunication customer detainment management, including telecommunication customer churn prediction and strategy formulation of customer detainment management. The formulation of churn customer detainment management strategy includes customer detainment value assessment, customer detainment level determination, enterprise-attribut...

A huge number of customer data was collected by using of information technology in healthcare context. It is very important for healthcare providers to analyze this type of big data following the logic of customer relationship management. So here we propose an integration framework which can realize the customer segmentation and customer churn prediction together. To efficiently segment the cus...