Customer churn prediction model using data mining techniques

Abstract

A big problem that encounters businesses, especially telecommunications business is `customer churn' this occurs when a customer decides to leave a company's landline business for another cable competitor. Therefore, our aim beyond this study to build a model that will predict churn customer through defining the customer's precise behaviors and attributes. We will use data mining techniques such as clustering, classification and association rule. The accuracy and preciseness of the technique used is so essential to the success of any retention attempting. After all, if the company is not aware of a customer who is about to leave their business; no proper action can be taken by that company towards that customer.