An innovative optimized model to anticipate clients about immigration in telecom industry

Abstract

This article proposed an innovative model to predict churning and non churning of clients in the telecom industry. Now-a-days, telecom customers are frequently migrating from one network to the other due to various constraints, policies and standards in public and private sectors. Usually in current industry the cost to retain the existing clients is smaller than getting a pioneering customer. To survive in the current competitive world, there is a need to design an optimal prediction model for churning and non churning of telecom clients. The proposed model has been outperformed with an accuracy level of 99.61% than existing models and techniques. Earlier authors have achieved 94.03 % of accuracy using machine learning techniques to predict churning of customers.