TITLE:
Research Model of Churn Prediction Based on Customer Segmentation and Misclassification Cost in the Context of Big Data
AUTHORS:
Yong Liu, Yongrui Zhuang
KEYWORDS:
Big Data, Churn Prediction, Customer Segmentation, Misclassification Cost
JOURNAL NAME:
Journal of Computer and Communications,
Vol.3 No.6,
June
4,
2015
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.