Churn Analysis and Plan Recommendation for Telecom Operators
نویسنده
چکیده
With increasing number of mobile operators, user is entitled with unlimited freedom to switch from one mobile operator to another if he is not satisfied with service or pricing. This trend is not good for operators as they lose their revenue because of customer switch. To solve it, operators are looking for machine learning tools which can predict well in advance which customer may churn, so that they can predict any alternative plans to satisfy and retain them. In this paper, we design a hybrid machine learning classifier to predict if the customer will churn based on the CDR parameters and we also propose a rule engine to suggest best plans.
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تاریخ انتشار 2016