GSM churn management by using fuzzy c-means clustering and adaptive neuro fuzzy inference system
Expert Systems with Applications: An International Journal
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Customer churn is a vexing problem in the telecom industry. Data mining techniques play an important role in churn prediction. However, most of these techniques can only provide a result that customers may churn or not, but seldom tell why they churn. Therefore even an accurate prediction result is of minimal use to telecom management, especially to the strategies of customer retention. In this paper, we propose a new model for strategic alignment of churn predictors to an adaptation of the Delta strategic model for firm competitiveness. This model is substantiated using a dataset from Duke Universityýs Teradata center for CRM. Research results contribute to analyzing churn predictors from a new perspective 驴 that of organizational competitiveness strategy. Using factor analysis, the model links high-level churn predictors with competitiveness strategy.