Applying Data Mining to Customer Churn Prediction in an Internet Service Provider

A business incurs much higher charges when attempting to win new customers than to retain existing ones. As a result, much research has been invested into new ways of identifying those customers who have a high risk of churning. However, customer retention efforts have also been costing organizations large amounts of resources. Same is the situation in ISP industry in I.R.Iran. Exploiting the use of demographic, billing and usage data, this study tends to identify the best churn predictors on the one hand and evaluates the accuracy of different data mining techniques on the other. Clustering users as per their usage features and incorporating that cluster membership information in classification models is another aspect which has been addressed in this study.

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