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

Author:

Shokouhyar Sajjad1,Saeidpour Parna1,Otarkhani Ali1

Affiliation:

1. Department of Information Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran

Abstract

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 VAS1for 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.

Publisher

IGI Global

Subject

Information Systems and Management,Management Science and Operations Research,Strategy and Management,Information Systems,Management Information Systems

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