Customer Churn Prediction:A Survey
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Abstract
Customer churn prediction is a core research topic in recent years. Churners are persons who quit a company’s service for some reasons. Companies should be able to predict the behavior of customer correctly in order to reduce customer churn rate. Customer churn has emerged as one of the major issues in every Industry. Researches indicates that it is more expensive to gain a new customer than to retain an existing one. In order to retain existing customers, service providers need to know the reasons of churn, which can be realized through the knowledge extracted from the data. To prevent the customer churn, many different prediction techniques are used .The commonly used techniques are neural networks, statistical based techniques, decision trees, covering algorithms, regression analysis, kmeans etc. This paper surveys the commonly used techniques to identify customer churn patterns.
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