Customer churn behaviour prediction in telecommunication using classification algorithms and modelling

Title

Customer churn behaviour prediction in telecommunication using classification algorithms and modelling

Creator

Singh, Garima; Joshi, Hemlata

Description

The cost of obtaining a high-quality client is usually five times more than the cost of keeping an existing customer. This is why it is very important that businesses keep their customers at home. To retain and improve their customers' satisfaction, researchers in various fields such as marketing, information technology, and business intelligence studied various ways to deliver the best possible services. Despite the good performance of the work done before, there is still a considerable gap in their prediction of the churners. In most cases, the training dataset is too large, and the high dimensionality of it causes the classification algorithms to fail. In the present paper, an attempt was made to estimate customer churn with greater accuracy in the membership of cellular wireless services using a call details records dataset consisting of 3333 clients having 21 attributes each. With the advancement of Machine Learning (ML) and artificial intelligence, most popular approaches such as logistic regression, CART, and C5 algorithms have been used with and without using the data balancing technique SMOTE. The performance evaluation of these predictive models is done using the model accuracy, confusion matrix, AUC value, ROC curve, and Cohen's Kappa statistics. The study results indicate that the C5 algorithm could estimate customer churn with an accuracy of more than 92% for both balanced and imbalanced datasets. 2025 Author(s).

Source

AIP Conference Proceedings;Volume;3191;Issue;1;Article No.;40006;

Date

01-01-2025

Publisher

American Institute of Physics

Subject

Churn Prediction; Classification Techniques; Customer Churn; Machine Learning; SMOTE; Telecommunication

Coverage

Singh G., Department of Statistics, CHRIST (Deemed to Be University), Bengaluru, India; Joshi H., Department of Statistics, CHRIST (Deemed to Be University), Bengaluru, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 0094243X; ISBN: 978-073545110-0;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1063/5.0248958

https://www.scopus.com/pages/publications/85218679790?origin=resultslist