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Churn Prediction in Telecommunication Industry Using Rough Set Approach

  • Adnan AminEmail author
  • Saeed Shehzad
  • Changez Khan
  • Imtiaz Ali
  • Sajid Anwar
Part of the Studies in Computational Intelligence book series (SCI, volume 572)

Abstract

The Customer churn is a crucial activity in rapidly growing and mature competitive telecommunication sector and is one of the greatest importance for a project manager. Due to the high cost of acquiring new customers, customer churn prediction has emerged as an indispensable part of telecom sectors’ strategic decision making and planning process. It is important to forecast customer churn behavior in order to retain those customers that will churn or possible may churn. This study is another attempt which makes use of rough set theory, a rule-based decision making technique, to extract rules for churn prediction. Experiments were performed to explore the performance of four different algorithms (Exhaustive, Genetic, Covering, and LEM2). It is observed that rough set classification based on genetic algorithm, rules generation yields most suitable performance out of the four rules generation algorithms. Moreover, by applying the proposed technique on publicly available dataset, the results show that the proposed technique can fully predict all those customers that will churn or possibly may churn and also provides useful information to strategic decision makers as well.

Keywords

Churn Prediction Rough Set Theory Classification 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Adnan Amin
    • 1
    Email author
  • Saeed Shehzad
    • 2
  • Changez Khan
    • 1
  • Imtiaz Ali
    • 1
  • Sajid Anwar
    • 1
  1. 1.Institute of Management Sciences PeshawarPeshawarPakistan
  2. 2.City University of Science and TechnologyPeshawarPakistan

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