To identify the factors responsible for prepaid customer churn and to propose feasible recommendations: Bharti Airtel Ltd

Abstract

It is typically much more expensive to acquire new customers than to retain existing ones. Consequently, predicting churn, i.e. if a customer is likely to leave for a competitor, is a critical requirement for customer retention. Predicting that a customer is likely to churn and then successfully convincing him/her to stay can substantially increase the revenue of a company. Customer churn is also closely related to the estimation of the lifetime value of the customer. The churn models are used to determinate the customers who are at risk of leaving and to analyze whether those customers are worth retaining. A company will therefore have a sense of how much is really being lost because of the customer churn and the scale of the efforts that would be appropriate for retention campaign. Thus customer churn is closely related to the customer retention rate and loyalty.