Churn Forecasting Model for South African Pre-Paid Service Providers

Olusola Gbenga Olufemi () and Trudie Strydom ()
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Olusola Gbenga Olufemi: Tshwane University of Technology
Trudie Strydom: Tshwane University of Technology

No 4, Proceedings of the 7th International RAIS Conference, February 19-20, 2018 from Research Association for Interdisciplinary Studies

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.

Keywords: Churn; Data Mining; Decision Support System; Customer Relationship Management; Bayesian Networks; DAG; Pre-paid Service; R BNlearn (search for similar items in EconPapers)
Pages: 20 pages
Date: 2018-03
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Published in Proceedings of the 7th International RAIS Conference on Social Sciences, February 19-20, 2018, pages 51-71

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