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Churn Forecasting Model for South African Pre-Paid Service Providers

Author

Listed:
  • Olusola Gbenga Olufemi

    (Tshwane University of Technology)

  • Trudie Strydom

    (Tshwane University of Technology)

Abstract

Telecommunication companies globally confront with rising problems of customer agitations. Inadequacy of telecoms’ rendered services, delivered products and many other causes, result to the difficult moments telecoms face. These problems have further degenerated to customers leaving from one network provider to the other, in quest for improved satisfaction. Churn is the term used to describe this customers’ resultant movement, due to agitation caused by inadequate operations. The Republic of South Africa (RSA) telecoms presently face this social problem called churn. To understand what causes customer churn, deep studies on varied literature on customer churn revealed the reasons behind this movement, i.e. churn factors. A developed customer experience questionnaire from these studied factors identified the main churn causing factors in RSA telecoms. This questionnaire eased the obtaining of data-records from respondents in South Africa, used in creating varied datasets. Using the varied datasets, a Bayesian networks’ model developed detected and evaluated churn likelihood in these different telecoms. This model proved to have more predicting potentials and relevance in our present days.

Suggested Citation

  • Olusola Gbenga Olufemi & Trudie Strydom, 2018. "Churn Forecasting Model for South African Pre-Paid Service Providers," Proceedings of the 7th International RAIS Conference, February 19-20, 2018 004, Research Association for Interdisciplinary Studies.
  • Handle: RePEc:smo:fpaper:004
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    References listed on IDEAS

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