Customer Churn Analysis Using Association Rule Mining and Decision Tree Classifiers

Abstract

Customer churn is a prominent issue facing companies. Therefore, preventing customer churn and retaining and retaining customers has become an essential issue for business operations and development. This paper aims to identify the reasons for customer churn for a prominent logistics company by using Apriori association rule mining. The expected output will be used by the business users to understand where they have the gaps in their business processes. The results from the Decision Tree and Apriori Algorithm shed light on which business feature was most prominent for causing churn.