Application of Social Network Inferred Data to Churn Modeling in Telecoms

The subject of this work is the use of social network analysis to increase the effectiveness of methods used to predict churn of telephony network subscribers. The social network is created on the basis of operational data (CDR records). The result of the analysis is customer segmentation and additi...

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Bibliographic Details
Published inJournal of Telecommunications and Information Technology Vol. 2; no. 2016; pp. 77 - 86
Main Authors Gruszczynski, Witold, Arabas, Piotr
Format Journal Article
LanguageEnglish
Published Warsaw Instytut Lacznosci - Panstwowy Instytut Badawczy (National Institute of Telecommunications) 30.06.2016
National Institute of Telecommunications
Subjects
churn reduction
classification
Information technology
Mathematical models
Regression
Regression analysis
Segmentation
Segments
Social networks
Telecommunications
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ISSN1509-4553
1899-8852
DOI10.26636/jtit.2016.2.722

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Summary:The subject of this work is the use of social network analysis to increase the effectiveness of methods used to predict churn of telephony network subscribers. The social network is created on the basis of operational data (CDR records). The result of the analysis is customer segmentation and additional predictor variables. Proposed hybrid predictor employs set of regression models tuned to specific customer segments. The verification was performed on data obtained from one of the Polish operators.
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ISSN:1509-4553
1899-8852
DOI:10.26636/jtit.2016.2.722