Analysis of Telecom Churn using Machine Learning Techniques

Customers are the cornerstone of any company's success; thus, businesses understand how crucial it is to ensure their satisfaction. The telecommunications sector is developing quickly, and service providers are now more eager to expand their subscriber bases. Retaining existing customers has become a major issue to meet the need to survive in a competing economy. In this study, customer turnover is predicted using data from a telecoms business utilizing the survival analysis technique. This study will help telecom corporations better understand the risk and hazard of customer turnover by detecting which customers are likely to go and whether they will. Analysis of the telecommunications industry has revealed that it is significantly more immoderate to obtain a new client than to continue an existing one. Due to growing business competition, the importance of marketing techniques, and users' increasingly aware behaviours in recent years, customer turnover is a crucial issue and is examined one of the most important worries between enterprises. To address the churn problems resulting from the services they provide, the company must implement several ways. In the very dynamic and quickly evolving telecom market, customer attrition strategies are crucial. The process of switching telecom service providers happens because of the competitive firm's competitive rates, excellent services, or a variety of benefits it offers clients when they sign up. To anticipate customer loyalty and whether they would leave the company, information from the telecom business can be useful. To boost customer engagement and/or treatment resources as part of their churn reduction goals, telecom companies will benefit from the findings of this study.