Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees

The goal of the paper is to present the framework for combining clustering and classification for churn management in telecommunications. Considering the value of market segmentation, we propose a three-stage approach to explain and predict the churn in telecommunications separately for different ma...

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Autores principales:	Mirjana Pejić Bach, Jasmina Pivar, Božidar Jaković
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	churn telecommunications clustering k-means market segmentation prediction Risk in industry. Risk management HD61 Finance HG1-9999
Acceso en línea:	https://doaj.org/article/f6842e11f5954ba884ddc5b455d48bac
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id	oai:doaj.org-article:f6842e11f5954ba884ddc5b455d48bac
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spelling	oai:doaj.org-article:f6842e11f5954ba884ddc5b455d48bac2021-11-25T18:08:41ZChurn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees10.3390/jrfm141105441911-80741911-8066https://doaj.org/article/f6842e11f5954ba884ddc5b455d48bac2021-11-01T00:00:00Zhttps://www.mdpi.com/1911-8074/14/11/544https://doaj.org/toc/1911-8066https://doaj.org/toc/1911-8074The goal of the paper is to present the framework for combining clustering and classification for churn management in telecommunications. Considering the value of market segmentation, we propose a three-stage approach to explain and predict the churn in telecommunications separately for different market segments using cluster analysis and decision trees. In the first stage, a case study churn dataset is prepared for the analysis, consisting of demographics, usage of telecom services, contracts and billing, monetary value, and churn. In the second stage, k-means cluster analysis is used to identify market segments for which chi-square analysis is applied to detect the clusters with the highest churn ratio. In the third stage, the chi-squared automatic interaction detector (CHAID) decision tree algorithm is used to develop classification models to identify churn determinants at the clusters with the highest churn level. The contribution of this paper resides in the development of the structured approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable structure. The proposed approach is continuous since the results of market segmentation and rules for churn prediction can be fed back to the customer database to improve the efficacy of churn management.Mirjana Pejić BachJasmina PivarBožidar JakovićMDPI AGarticlechurntelecommunicationsclusteringk-meansmarket segmentationpredictionRisk in industry. Risk managementHD61FinanceHG1-9999ENJournal of Risk and Financial Management, Vol 14, Iss 544, p 544 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	churn telecommunications clustering k-means market segmentation prediction Risk in industry. Risk management HD61 Finance HG1-9999
spellingShingle	churn telecommunications clustering k-means market segmentation prediction Risk in industry. Risk management HD61 Finance HG1-9999 Mirjana Pejić Bach Jasmina Pivar Božidar Jaković Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
description	The goal of the paper is to present the framework for combining clustering and classification for churn management in telecommunications. Considering the value of market segmentation, we propose a three-stage approach to explain and predict the churn in telecommunications separately for different market segments using cluster analysis and decision trees. In the first stage, a case study churn dataset is prepared for the analysis, consisting of demographics, usage of telecom services, contracts and billing, monetary value, and churn. In the second stage, k-means cluster analysis is used to identify market segments for which chi-square analysis is applied to detect the clusters with the highest churn ratio. In the third stage, the chi-squared automatic interaction detector (CHAID) decision tree algorithm is used to develop classification models to identify churn determinants at the clusters with the highest churn level. The contribution of this paper resides in the development of the structured approach to churn management using clustering and classification, which was tested on the churn dataset with a rich variable structure. The proposed approach is continuous since the results of market segmentation and rules for churn prediction can be fed back to the customer database to improve the efficacy of churn management.
format	article
author	Mirjana Pejić Bach Jasmina Pivar Božidar Jaković
author_facet	Mirjana Pejić Bach Jasmina Pivar Božidar Jaković
author_sort	Mirjana Pejić Bach
title	Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
title_short	Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
title_full	Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
title_fullStr	Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
title_full_unstemmed	Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees
title_sort	churn management in telecommunications: hybrid approach using cluster analysis and decision trees
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/f6842e11f5954ba884ddc5b455d48bac
work_keys_str_mv	AT mirjanapejicbach churnmanagementintelecommunicationshybridapproachusingclusteranalysisanddecisiontrees AT jasminapivar churnmanagementintelecommunicationshybridapproachusingclusteranalysisanddecisiontrees AT bozidarjakovic churnmanagementintelecommunicationshybridapproachusingclusteranalysisanddecisiontrees
_version_	1718411596717359104

Churn Management in Telecommunications: Hybrid Approach Using Cluster Analysis and Decision Trees

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