Português
Ciência-IUL
Publications
Publication Detailed Description
Journal Title
Future Internet
Year (definitive publication)
2022
Language
English
Country
Switzerland
More Information
Web of Science®
Scopus
Google Scholar
Abstract
Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.
Acknowledgements
--
Keywords
Telecommunications,Customer segmentation,Data mining,Targeted marketing
Fields of Science and Technology Classification
- Economics and Business - Social Sciences
Funding Records
| Funding Reference | Funding Entity |
|---|---|
| UIDB/04466/2020 | Fundação para a Ciência e a Tecnologia |
| UIDP/04466/2020 | Fundação para a Ciência e a Tecnologia |
Related Projects
This publication is an output of the following project(s):
Contributions to the Sustainable Development Goals of the United Nations
With the objective to increase the research activity directed towards the achievement of the United Nations 2030 Sustainable Development Goals, the possibility of associating scientific publications with the Sustainable Development Goals is now available in Ciência-IUL. These are the Sustainable Development Goals identified by the author(s) for this publication. For more detailed information on the Sustainable Development Goals, click here.
