An Analysis of Customer Churn Prediction in Different Business Industries

Zhengyang Zhao

2024

Abstract

In this article, the currently deployed forecasting techniques are reviewed. Churn is widely used for areas such as web services, gaming and insurance. However, since it is vastly used to improve predictability in various industries, there is a great deal of variation in its definition and usage. This paper categorises the traditional methods of machine learning and deep learning, presents a number of papers related to these two technologies, and discusses and analyses the papers in order to provide more academics with a clear understanding of how these two technologies are used in different industries. The paper brings together definitions of froth in the following areas as business management, Information and communication technology (ICT) and newspaper industry, and explains the differences between them. On the basis of this, churn loss, attribute engineering and predictive modelling are categorised and explained. This study can be conducted by debris integration studies in industrial domains and selecting churn definitions and relevant models suitable for most interest to researchers.

Paper Citation

in Harvard Style

Zhao Z. (2024). An Analysis of Customer Churn Prediction in Different Business Industries. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 781-785. DOI: 10.5220/0012972800004508

in Bibtex Style

@conference{emiti24,
author={Zhengyang Zhao},
title={An Analysis of Customer Churn Prediction in Different Business Industries},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={781-785},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012972800004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - An Analysis of Customer Churn Prediction in Different Business Industries
SN - 978-989-758-713-9
AU - Zhao Z.
PY - 2024
SP - 781
EP - 785
DO - 10.5220/0012972800004508
PB - SciTePress