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Churn Forecasting Model for South African Pre-Paid Service Providers

Domain:

socioeconomicdigital infrastructure

Record type:

paperdatasetmodelsoftware
Creator:
Olusola Gbenga OlufemiTrudie Strydom
Publisher:
Zenodo
Host:avatar

 

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. 

Visit

doi.org

Tags

Churn, Data Mining, Decision Support System, Customer Relationship Management, Bayesian Networks, DAG, Pre-paid Service, R BNlearn.

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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