Results 1 to 10 of about 9,057 (181)

Customer churn prediction for telecommunication industry: A Malaysian Case Study [version 1; peer review: 2 approved] [PDF]

F1000Research, 2021
Background: Customer churn is a term that refers to the rate at which customers leave the business. Churn could be due to various factors, including switching to a competitor, cancelling their subscription because of poor customer service, or ...
Nurulhuda Mustafa, Lew Sook Ling, Siti Fatimah Abdul Razak   +2 more
doaj   +2 more sources

A Data-Driven Approach to Improve Customer Churn Prediction Based on Telecom Customer Segmentation [PDF]

Future Internet, 2022
Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies.
Tianyuan Zhang, Sérgio Moro, Ricardo F. Ramos   +2 more
doaj   +3 more sources

Customer churn prediction using composite deep learning technique [PDF]

Scientific Reports, 2023
Customer churn, a phenomenon that causes large financial losses when customers leave a business, makes it difficult for modern organizations to retain customers.
Asad Khattak, Zartashia Mehak, Hussain Ahmad, Muhammad Usama Asghar, Muhammad Zubair Asghar, Aurangzeb Khan   +5 more
doaj   +2 more sources

A novel customer churn prediction model for the telecommunication industry using data transformation methods and feature selection. [PDF]

PLoS ONE, 2022
Customer churn is one of the most critical issues faced by the telecommunication industry (TCI). Researchers and analysts leverage customer relationship management (CRM) data through the use of various machine learning models and data transformation ...
Joydeb Kumar Sana, Mohammad Zoynul Abedin, M Sohel Rahman, M Saifur Rahman   +3 more
doaj   +3 more sources

PERANCANGAN SISTEM PREDIKSI CHURN PELANGGAN PT. TELEKOMUNIKASI SELULER DENGAN MEMANFAATKAN PROSES DATA MINING [PDF]

Jurnal Informatika, 2008
The purpose of this research is to design a customer churn prediction system using data mining approach. This system is able to perform data integration, data cleaning, data transformation, sampling and data splitting, prediction model building ...
Rajesri Govindaraju, Tota Simatupang, TMA. Ari Samadhi   +2 more
doaj   +1 more source

Advanced customer churn prediction for a music streaming digital marketing service using attention graph-based deep learning approach [PDF]

Scientific Reports
Customer churn poses a persistent threat to the sustainability of music streaming platforms, where user disengagement often occurs unpredictably. Most existing churn prediction methods fail to integrate relational dependencies among users or address the ...
Haiyan Cheng, Jie He
doaj   +2 more sources

Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning [PDF]

PeerJ Computer Science
Background Imbalanced and overlapped data in customer churn prediction significantly impact classification results. Various sampling and hybrid sampling methods have demonstrated effectiveness in addressing these issues.
I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin   +2 more
doaj   +3 more sources

A predictive analytics approach to improve telecom's customer retention [PDF]

Frontiers in Artificial Intelligence
Customer retention is a critical challenge for telecom companies, and understanding customer churn can significantly improve business strategies. This paper focuses on developing an accurate predictive model to identify potential customer churn using ...
Asem Omari, Omaia Al-Omari, Tariq Al-Omari, Suliman Mohamed Fati   +3 more
doaj   +2 more sources

Combining predictive accuracy and interpretability: a data-driven approach to telecom churn analysis [PDF]

Scientific Reports
Acquiring consumers is a challenge in the telecom industry since it reduces profits and slows growth. Customer churn prediction remains a pivotal challenge for telecommunications companies seeking to retain subscribers and sustain profitability in highly
Pankaj Hooda, Pooja Mittal, Prashant Kumar Shukla, Piyush Kumar Shukla, Ankur Pandey   +4 more
doaj   +2 more sources

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
  +7 more sources