Customer Churn Prediction in Telecommunications Industry Based on Data Mining

Nowadays, many businesses and organizations have begun to collect data on their future and current customers to evaluate churning rate and prevent the loss of potential customers while also keeping the current customers and making them happy. The challenging part, however, is not gathering the data,...

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Bibliographic Details
Main Authors: Khalid, Lawchak Fadhil, Mohsin Abdulazeez, Adnan, Zeebaree, Diyar Qader, Ahmed, Falah Y. H., Zebari, Dilovan Asaad
Format: Conference Proceeding
Language:English
Subjects:
Current measurement
Customer Churn
Customer Segmentation
Data Mining
Focusing
Industries
Organizations
Prediction algorithms
Predictive models
Telecommunications
Online Access:Request full text
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Summary:Nowadays, many businesses and organizations have begun to collect data on their future and current customers to evaluate churning rate and prevent the loss of potential customers while also keeping the current customers and making them happy. The challenging part, however, is not gathering the data, rather, it arises when these data are processed, and consumers are segmented based on the information collected. This paper aims to investigate the potentials of Data Mining in identifying potential churners from a business and more especially focusing on the Telecom industry. Many experiments are carried out, and various classification algorithms are tested to assess their impact and capability in predicting the potential churners, as this is a crucial information for businesses to keep their customers happy and subscribed to their services.
ISSN:2472-7660
DOI:10.1109/ISIEA51897.2021.9509988