An Analysis of Logistic Regression Technique to Predict Customer Churn

Abstract

Every business depends on customer's loyalty. The repeat business from customer is one of the cornerstone for business profitability. So, it is important to know the reason of customers leaving a business. Customers going away is known as customer churn. By looking at the past trends, judgement can be made to what factors influence customer churn and how to predict if a particular customer will go away from the business. In this research paper, multiple regression is used to study the past trends in customer churn and then predict which customers are likely to churn. Pandas’ library is used to load the source file which is that of telecommunication data into the Python program and look at some of the sample rows. Step wise regression is done to improve the accuracy of the prediction model.