Segmentation of telecom customers based on customer value by decision tree model

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

40 Scopus Citations
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Author(s)

  • Shui Hua Han
  • Shui Xiu Lu
  • Stephen C.H. Leung

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)3964-3973
Journal / PublicationExpert Systems with Applications
Volume39
Issue number4
Publication statusPublished - Mar 2012

Abstract

The more the telecom services marketing paradigm evolves, the more important it becomes to retain high value customers. Traditional customer segmentation methods based on experience or ARPU (Average Revenue per User) consider neither customers' future revenue nor the cost of servicing customers of different types. Therefore, it is very difficult to effectively identify high-value customers. In this paper, we propose a novel customer segmentation method based on customer lifecycle, which includes five decision models, i.e. current value, historic value, prediction of long-term value, credit and loyalty. Due to the difficulty of quantitative computation of long-term value, credit and loyalty, a decision tree method is used to extract important parameters related to long-term value, credit and loyalty. Then a judgments matrix formulated on the basis of characteristics of data and the experience of business experts is presented. Finally a simple and practical customer value evaluation system is built. This model is applied to telecom operators in a province in China and good accuracy is achieved. © 2011 Elsevier Ltd. All rights reserved.

Research Area(s)

  • Credit, Customer lifecycle, Customer value, Decision tree model, Loyalty

Citation Format(s)

Segmentation of telecom customers based on customer value by decision tree model. / Han, Shui Hua; Lu, Shui Xiu; Leung, Stephen C.H.

In: Expert Systems with Applications, Vol. 39, No. 4, 03.2012, p. 3964-3973.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal