CUSTOMER CHURN PREDICTION IN THE TELECOM INDUSTRY: LEVERAGING DATA MINING TECHNIQUES FOR ENHANCED CUSTOMER RETENTION

Abstract

Customer churn prediction has become a central research focus in the Telecom Industry in recent years, owing to the exponential growth of data generated within the industry. This paper explores the significance of customer churn, which has emerged as a critical challenge for Telecom providers, given the higher costs associated with acquiring new customers compared to retaining existing ones. Leveraging data mining techniques, this study surveys and analyzes the most used approaches to identify customer churn patterns. Additionally, the paper reviews the latest literature on predictive data mining techniques concerning customer churn behavior, and concludes by discussing potential avenues for future research.