A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners

A Manzoor, MA Qureshi, E Kidney, L Longo - IEEE Access, 2024 - ieeexplore.ieee.org
Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

[HTML][HTML] Empirical analysis of tree-based classification models for customer churn prediction

FE Usman-Hamza, AO Balogun, SK Nasiru, LF Capretz… - Scientific African, 2024 - Elsevier
Customer churn is a vital and reoccurring problem facing most business industries,
particularly the telecommunications industry. Considering the fierce competition among …

Factors, Predictability and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature

D Freire, D Mauricio, JLC Sequera, D Fiallo - IEEE Access, 2024 - ieeexplore.ieee.org
The telecommunications sector has experienced exponential growth since the year 2000,
reaching 5.31 trillion users by 2022, generating 1.07 trillion in revenue for …

Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries

HA Mengash, N Alruwais, F Kouki, C Singla… - Biomimetics, 2023 - mdpi.com
Customer churn prediction (CCP) implies the deployment of data analytics and machine
learning (ML) tools to forecast the churning customers, ie, probable customers who may …

[HTML][HTML] New Artificial intelligence approaches for brand switching decisions

B Erkayman, E Erdem, T Aydin, Z Mahmat - Alexandria Engineering Journal, 2023 - Elsevier
The problem of customer complaints occurs in almost every business and solutions are
offered to reduce these complaints. When companies do not pay necessary attention to the …

The Implementation of hybrid methods in data mining for Predicting customer churn in the telecommunications sector

RH Herdian, AS Girsang - Jurnal Mantik, 2023 - iocscience.org
In recent years, the telecommunication industry is growth and become very competitive
where has reached the point maintaining customer is very essential than acquiring new …

The Comparison of Random Forest and Artificial Neural Network for Customer Churn Prediction in Telecommunication

AF Ramadhan, SD Permai… - 2023 3rd International …, 2023 - ieeexplore.ieee.org
Customer churn is a significant issue that can affect a company's revenue, particularly in the
telecommunication sector. Companies today are working hard to survive in this competitive …

A flexible framework for customer behavior prediction based on ensemble learning

TM Nguyen, TA Le, TH Nguyen - … of the 12th International Symposium on …, 2023 - dl.acm.org
Predicting customer behavior is crucial for businesses, including churn and purchasing
behavior. We propose a tailored model for this purpose, applied to two types of problems …

Churn Prediction Model Based on Logistic Regression in the Telecommunications Industry: Big Data Analysis

FD Winati, M Arifin, AY Pratama… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
The telecommunications industry faces fierce competition and rapid customer growth, but
also a pressing challenge: customer churn. This phenomenon, where customers switch …

Improved Decision Tree, Random Forest, and XGBoost Algorithms for Predicting Client Churn in the Telecommunications Industry.

ME Saleh, N Abd-Alsabour - International Journal of …, 2024 - search.ebscohost.com
Traditional machine learning models, especially decision trees, face great challenges when
applied to highdimensional and imbalanced telecommunication datasets. The research …