Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/24090
Title: Analysis of churn prediction: a case study on telecommunication services in Macedonia
Authors: Trivodaliev, Kire 
Petkovski, Aleksandar
Risteska Stojkoska, Biljana
Kalajdziski, Slobodan 
Keywords: churn prediction, data mining, decision trees, KNN, logistic regression, naïve Bayes
Issue Date: 22-Nov-2016
Publisher: IEEE
Conference: 24th Telecommunications forum TELFOR 2016
Abstract: — Customer churn is one of the main problems in the telecommunications industry. Several studies have shown that attracting new customers is much more expensive than retaining existing ones. Therefore, companies are focusing on developing accurate and reliable predictive models to identify potential customers that will churn in the near future. The aim of this paper is investigating the main reasons for churn in telecommunication sector in Macedonia. The proposed methodology for analysis of churn prediction covers several phases: understanding the business; selection, analysis and data processing; implementing various algorithms for classification; evaluation of the classifiers and choosing the best one for prediction. The obtained results for the data from a telecommunication company in Macedonia, should be of great value for management and marketing departments of other telecommunication companies in the country and wider.
URI: http://hdl.handle.net/20.500.12188/24090
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers

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