共 4 条
Churn models for prepaid customers in the cellular telecommunication industry using large data marts
被引:52
作者:
Owczarczuk, Marcin
[1
]
机构:
[1] Warsaw Sch Econ, Inst Econometr, PL-02554 Warsaw, Poland
关键词:
Churn prediction;
Retention;
Wireless;
Cellular;
CRM;
MANAGEMENT;
D O I:
10.1016/j.eswa.2009.11.083
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
In this article, we test the usefulness of the popular data mining models to predict churn of the clients of the Polish cellular telecommunication company. When comparing to previous studies on this topic, our research is novel in the following areas: (1) we deal with prepaid clients (previous studies dealt with postpaid clients) who are far more likely to churn, are less stable and much less is known about them (no application, demographical or personal data), (2) we have 1381 potential variables derived from the clients' usage (previous studies dealt with data with at least tens of variables) and (3) we test the stability of models across time for all the percentiles of the lift curve - our test sample is collected six months after the estimation of the model. The main finding from our research is that linear models, especially logistic regression, are a very good choice when modelling churn of the prepaid clients. Decision trees are unstable in high percentiles of the lift curve, and we do not recommend their usage. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4710 / 4712
页数:3
相关论文