Predicting Customers' Churn Using Data Mining Technique and its Effect on the Development of Marketing Applications in Value-Added Services in Telecom Industry

被引：4

作者：

Shokouhyar, Sajjad ^{[1
]}

Saeidpour, Parna ^{[1
]}

Otarkhani, Ali ^{[1
]}

机构：

[1] Shahid Beheshti Univ, Management & Accounting Fac, Dept Informat Management, GC, Tehran, Iran

来源：

INTERNATIONAL JOURNAL OF INFORMATION SYSTEMS IN THE SERVICE SECTOR | 2018年 / 10卷 / 04期

基金：

美国国家卫生研究院;

关键词：

Churn of Customers; Customer Classification; Data Mining; KNN Algorithm; Mobile Telecom Market;

D O I：

10.4018/IJISSS.2018100104

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This article aims to predict reasons behind customers' churn in the mobile communication market. In this study, different data mining techniques such as logistic regression, decision trees, artificial neural networks, and K-nearest neighbor were examined. In addition, the general trend of the use of the techniques is presented, in order to identify and analyze customers' behavior and discover hidden patterns in the database of an active Coin the field of VAS1 for mobile phones. Based on the results of this article, organizations and companies active in this area can identify customers' behavior and develop the required marketing strategies for each group of customers.

引用

页码：59 / 72

页数：14