A Case of Churn Prediction in Telecommunications Industry

Churn prediction is the practice of assigning a probability to the event of a customer ending his contract with a service provider. Traditional data mining approaches to churn prediction in telecommunications industry are based on detecting patterns from customer contractual information, traffic related data, bills and payments, CRM data and customer service logs. The study presented in this paper has employed various machine learning approaches and assessed their performances using the data of a European mobile operator. The feature importance rankings which were used for feature selection yielded also some initial guidelines for acting on churn prevention in practice.