Research Model of Churn Prediction Based on Customer Segmentation and Misclassification Cost in the Context of Big Data

Yong Liu, Yongrui Zhuang

School of Business, South China University of Technology, Guangzhou, China.

DOI: 10.4236/jcc.2015.36009                

Abstract

Enterprises have vast amounts of customer behavior data in the era of big data. How to take advantage of these data to evaluate custom forfeit risks effectively is a common issue faced by enterprises. Most of traditional customer churn predicting models ignore customer segmentation and misclassification cost, which reduces the rationality of model. Dealing with these deficiencies, we established a research model of customer churn based on customer segmentation and misclassification cost. We utilized this model to analyze customer behavior data of a telecom company. The results show that this model is better than those models without customer segmentation and misclassification cost in terms of the performance, accuracy and coverage of model.

Keywords

Big Data, Churn Prediction, Customer Segmentation, Misclassification Cost

Conflicts of Interest

The authors declare no conflicts of interest.

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