Abstract: Customer churn is one of the most important metrics for a growing business to evaluate. While it's not the happiest measure, it's a number that can give a service oriented company, the hard truth about its customer retention. The churn rate, also known as the rate of attrition or customer churn, is the rate at which customers stop doing business with an entity. It is most commonly expressed as the percentage of service subscribers who discontinue their subscriptions within a given time period. It is also the rate at which employees leave their jobs within a certain period. For a company to expand its clientele, its growth rate (measured by the number of new customers) must exceed its churn rate. Purposes behind customer churn might be the disappointment with the nature of administration, high costs, ugly plans, no comprehension of the administration design, awful help, and so on. This paper gives emphasis on a hybrid data mining techniques which involves Decision Tree and Logistic Regression which is used to create the prediction model to predict the intention of the customers in service oriented organization.

Keywords: Churn, prediction, sectors, hybrid, logistic regression, decision tree.

| DOI: 10.17148/IARJSET.2021.86123