Customer Churn Prediction in Telecommunication: An Analysis on Issues, Techniques and Future Trends

Citation

Maw, Maw and Haw, Su Cheng and Ho, Chin Kuan (2019) Customer Churn Prediction in Telecommunication: An Analysis on Issues, Techniques and Future Trends. In: IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (2019 IEEE CSUDET), 7-9 Nov 2019, Penang, Malaysia.

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Abstract

Customer churn or customer attrition is the situation in which customers stop their subscriptions from the services of the specific service providers. It has a high impact on the profitability of a business especially in the telecommunication sector, where by customer churn prediction has become a crucial task for customer relationship management. Recent studies have shown that the performance results of existing CCP models are still not satisfying and have claimed about the difficulties which still need to be fixed. This paper aims to investigate the major challenges confronted in the process of constructing an efficient CCP model, to explore some salient approaches for eliminating those challenges and hence to underline some slots that still needed to fill in for the future CCP research. To achieve these goals, we conducted an analysis on 18 contemporary studies published within 5 years from 2015 to 2019. Consequently, we identified significant issues in CCP research area. Our findings reveal nine key challenges confronted in the CCP research area. CCP modeling techniques applied in selected literature are explored and some of the prominent techniques are discussed briefly. Hence, some directions on the future CCP research area are suggested as well.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Customer relationship management, predictive analysis, telecommunication
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 07 Oct 2021 01:04
Last Modified: 07 Oct 2021 01:04
URII: http://shdl.mmu.edu.my/id/eprint/9495

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