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Customer churn prediction in Chinese traditional broadcasting industry: A positive analysis

  • Bing Zhang Hou
  • , Yue Wu
  • , Li Ming Zheng
  • , Dong Lai Zhao
  • , Ao Ran Xie
  • School of Management, Harbin Institute of Technology
  • School of Electronics and Information Engineering, Harbin Institute of Technology
  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In order to better respond to market competition, national broadcast service providers such as cable network enterprises have to recognize customer preference and forecast customer churn intention before their rivals do so. In this paper, data recorded by the digital set-Top box and consuming records in cable network's finance system is used for analyzing customer churn. First, the results of this research indicate that customer watching intensity, customer consumption amount and customer paying habits have significant influence on customer churn. And the effect of customer watching intensity on customer churn is moderated by customer watching preference. Second, this research uses logistic regression to build the prediction model. Finally, we propose different user retention strategies targeting the churn customers. This study demonstrates that our proposed user churn factors are efficient and capable of providing effective marketing strategies for cable network enterprises.

Original languageEnglish
Title of host publication2017 International Conference on Management Science and Engineering - 24th Annual Proceedings, ICMSE 2017
EditorsMa Tao, Shao Zhen, Ji Yuan
PublisherIEEE Computer Society
Pages596-605
Number of pages10
ISBN (Electronic)9781538613740
DOIs
StatePublished - 2 Jul 2017
Externally publishedYes
Event24th Annual International Conference on Management Science and Engineering, ICMSE 2017 - Nomi, Japan
Duration: 17 Aug 201720 Aug 2017

Publication series

NameInternational Conference on Management Science and Engineering - Annual Conference Proceedings
Volume2017-August
ISSN (Print)2155-1847

Conference

Conference24th Annual International Conference on Management Science and Engineering, ICMSE 2017
Country/TerritoryJapan
CityNomi
Period17/08/1720/08/17

Keywords

  • Cable networks provider
  • Customer behavior
  • Customer churn
  • Customer relationship management
  • Customer retention
  • Data mining

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