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The telecommunications industry is highly competitive, which means that themobile providers need a business intelligence model that can be used to achievean optimal level of churners, as well as a minimal level of cost in marketingactivities. Machine learning applications can be used to provide guidance onmarketing strategies. Furthermore, data mining techniques can be used in theprocess of customer segmentation. The purpose of this paper is to provide adetailed analysis of the C.5 algorithm, within naive Bayesian modelling for thetask of segmenting telecommunication customers behavioural profiling accordingto their billing and socio-demographic aspects. Results have beenexperimentally implemented.

Integration of Machine Learning Techniques to Evaluate Dynamic Customer Segmentation Analysis for Mobile Customers