Customer Churn Prediction using Machine Learning

Abstract

The varying customer requirements and interests often result in subscription cancellation. Hence, running a subscription business necessitates an accurate churn forecasting model as even a minor change will result in a significant impact. If the seller is not informed that the customer is about to cancel the subscription, no action will be taken to retain them. As a result, this research study attempts to design and develop a churn prediction model to predict a subscription cancellation and provide incentives for that particular subscriber to stay back. This results in significant cost savings and generate an additional revenue source for any online business. The primary goal of this research work is to analyze different models for predicting the active churners with high accuracy. In existing systems, the service providers track down the clients before they leave in order to solve this problem. This study has compared the well-known machine learning techniques to solve the problem and also predict the results in a more accurate way.