Results 11 to 20 of about 856,045 (240)

CUSTOMER CHURN PREDICTION

International Journal for Research in Engineering Application & Management
Our work focuses on applying supervised machine learning techniques to anticipate bank client attrition. We created a straightforward and effective strategy that works with a variety of machine learning techniques. We tested many methods through tests and discovered that the Decision Tree strategy was the most effective in forecasting client attrition.
Lavina Anand Parulekar, Prajkta Shriram Jamsandekar, Sampada Sanjay Parkar, Sawant S.P   +3 more
semanticscholar   +9 more sources

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

IEEE Access
Due to market deregulation and globalisation, competitive environments in various sectors continuously evolve, leading to increased customer churn. Effectively anticipating and mitigating customer churn is vital for businesses to retain their customer ...
Awais Manzoor, M. Atif Qureshi, Etain Kidney, Luca Longo   +3 more
doaj   +2 more sources

Improving bank customer churn prediction with feature reduction using GA [PDF]

Scientific Reports
Customer churn is one complex problem that all banking institutes struggle to deal with. The increased competition in the industry is forcing the banks to maintain customer loyalty by providing apt services to the demanding customers.
Nisha T N, Dhanya Pramod
doaj   +2 more sources

Prediction of Customer Churn Behavior in the Telecommunication Industry Using Machine Learning Models

Algorithms
Customer churn is a significant concern, and the telecommunications industry has the largest annual churn rate of any major industry at over 30%. This study examines the use of ensemble learning models to analyze and forecast customer churn in the ...
Victor Chang, Karl Hall, Qianwen Ariel Xu, Folakemi Ololade Amao, Meghana Ashok Ganatra, Vladlena Benson   +5 more
doaj   +2 more sources

ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering

Algorithms
Customers are the cornerstone of business success across industries. Companies invest significant resources in acquiring new customers and, more importantly, retaining existing ones.
Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani   +7 more
doaj   +2 more sources

CTGAN-ENN: a tabular GAN-based hybrid sampling method for imbalanced and overlapped data in customer churn prediction

Journal of Big Data
Class imbalance is one of many problems of customer churn datasets. One of the common problems is class overlap, where the data have a similar instance between classes.
I Nyoman Mahayasa Adiputra, Paweena Wanchai   +1 more
doaj   +2 more sources

Research on customer churn prediction and model interpretability analysis. [PDF]

PLoS One, 2023
In recent years, with the continuous improvement of the financial system and the rapid development of the banking industry, the competition of the banking industry itself has intensified.
Peng K, Peng Y, Li W.
europepmc   +2 more sources

Customer churn prediction model based on hybrid neural networks. [PDF]

Sci Rep
In today’s competitive market environment, accurately identifying potential churn customers and taking effective retention measures are crucial for improving customer retention and ensuring the sustainable development of an organization.
Liu X, Xia G, Zhang X, Ma W, Yu C.
europepmc   +2 more sources

Predicting Customer Churn on OTT Platforms: Customers with Subscription of Multiple Service Providers

Journal of Information and Organizational Sciences, 2022
No industry can thrive without customers and with customers comes the chances of customer churn. Since customer churn have direct-impact on the revenue, all the industries are focusing in understanding the factors influencing churn and are developing ...
Manish Mohan, Anil Jadhav
doaj   +1 more source

A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy

Connection Science, 2022
Owing to saturated markets, fierce competition, dynamic criteria, along with introduction of new attractive offers, the considerable issue of customer churn was faced by the telecommunication industry.
R. Sudharsan, E. N. Ganesh
doaj   +1 more source