IBM Telco Customer Churn Prediction with Survival Analysis

DOI

10.2991/978-94-6463-566-9_25How to use a DOI?

Keywords

Survival analysis; Churn; Business; Customer behavior

Abstract

Customer churn or attrition occurs when customers stop engaging with a company or product. A high churn rate can be a serious threat to a company’s sustainability. In the competitive telecommunications industry, churn analysis is key to developing customer retention strategies. This research will conduct churn analysis on the IBM Telco public dataset using the survival analysis method with two competing risks in the dataset, namely internal company deficiencies and external factors. The results of the subscription duration analysis show that customers who stop tend to have shorter subscription durations and spend less. Kaplan-Meier revealed significant differences in probability distributions for variables such as contract type, additional services, and demographic factors. The stratified Cox method confirms the significant impact of variables such as the presence of a partner, type of contract, multiple lines, and additional services on the risk of churn. The Goodness of Fit test validates the ability of the survival analysis model to differentiate churn cases overall, with a concordance value reaching 0.867. The CIF Plot shows that certain factors, such as gender and tele-phone service, are not significant in differentiating between events caused by internal company deficiencies or better offerings from other providers. The research results show that churn analysis using the survival analysis method can provide a basis for companies to optimize business strategies in facing competitive challenges so that they can make better decisions in the future.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hafiz Rahman
AU  - Ridho Pandhu Afrianto
AU  - Farisi Mohammad
AU  - Dhia Alif Tajriyaani Azhar
AU  - Ratih Ardiati Ningrum
PY  - 2024
DA  - 2024/11/01
TI  - IBM Telco Customer Churn Prediction with Survival Analysis
BT  - Proceedings of the  International Conference on Advanced Technology and Multidiscipline (ICATAM 2024)
PB  - Atlantis Press
SP  - 386
EP  - 412
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-566-9_25
DO  - 10.2991/978-94-6463-566-9_25
ID  - Rahman2024
ER  -