data mining techniques for customer churn prediction

The profit resulting from customer relationship is essential to ensure companies viability, so an improvement in customer retention is crucial for competitiveness. as such, companies have recognized the importance of customer centered strategies and consequently customer relationship management (crm) is often at the core of their strategic plans. in this context, customer churn is an important subject. a churn consumer can be defined as a customer who transfers from one service provider to another service provider. recently, business operators have investigated many techniques that identify the customer churn since churn rates leads to serious business loss. this paper proposes a model to predict customer churn in one of iranian telecommunication company, using three classification techniques: logistic regression, classification and regression tree and random forrest.

Data mining techniques for Customer Churn Prediction

The profit resulting from customer relationship is essential to ensure companies viability, so an improvement in customer retention is crucial for competitiveness. As such, companies have recognized the importance of customer centered strategies and consequently customer relationship management (CRM) is often at the core of their strategic plans. In this context, customer churn is an important subject. A churn consumer can be defined as a customer who transfers from one service provider to another service provider. Recently, business operators have investigated many techniques that identify the customer churn since churn rates leads to serious business loss. This paper proposes a model to predict customer churn in one of Iranian Telecommunication Company, using three classification techniques: Logistic regression, Classification and Regression Tree and Random Forrest.