Customer Churn Analysis and Risk Prediction in E-Commerce

With global advancement, Information Technology has led to the growth of numerous Service Providers, which, in turn, has resulted in fierce competition between them. For Service Providers, the most prevalent obstacle is the handling of customer churn, retention, and satisfaction of customers for successful market sustenance. In today's competitive market, predicting and managing churn is essential for businesses to identify different types of churners and take appropriate action to keep consumers and revenues. The goal of churn models is to detect early signs of customer attrition and identify those who are most likely to leave on their own will. This work proposes a way for assessing Machine Learning (ML) for classification.