Search Results - subject:"Churn prediction"

Deep dive into churn prediction in the banking sector : the challenge of hyperparameter selection and imbalanced learning

Gkonis, Vasileios; Tsakalos, Ioannis - In: Journal of forecasting 44 (2025) 2, pp. 281-296

Persistent link: https://www.econbiz.de/10015374022

Proaktives Kundenbindungsmanagement im Werbeartikelhandel: Entwicklung eines Machine-Learning-Modells zur Prognose von Kundenabwanderungen

Schemm, Jan; Schwarz, Christian; Strickrodt, Marc - 2024

provides an empirical case study for the development of a churn prediction model in non-contractual B2B customer relationships …

Persistent link: https://www.econbiz.de/10015117582

A framework to improve churn prediction performance in retail banking

Brito, João B. G.; Bucco, Guilherme B.; Heldt, Rodrigo; … - In: Financial innovation : FIN 10 (2024), pp. 1-29

preprocessing, we use XGBoost and elastic net methods for churn prediction. We validated the proposed framework with a dataset of …

Persistent link: https://www.econbiz.de/10014532015

A high-performance turnkey system for customer lifetime value prediction in retail brands

Yan, Yan; Resnick, Nicholas - 2024

Persistent link: https://www.econbiz.de/10015127375

Investigating customer churn in banking : a machine learning approach and visualization app for data science and management

Singh, Pahul Preet; Anik, Fahim Islam; Senapati, Rahul; … - In: Data science and management : DSM 7 (2024) 1, pp. 7-16

Customer attrition in the banking industry occurs when consumers quit using the goods and services offered by the bank for some time and, after that, end their connection with the bank. Therefore, customer retention is essential in today's extremely competitive banking market. Additionally,...

Persistent link: https://www.econbiz.de/10014518030

Predicting customer abandonment in recurrent neural networks using short-term memory

Beltozar-Clemente, Saul; Iparraguirre-Villanueva, Orlando; … - In: Journal of open innovation : technology, market, and … 10 (2024) 1, pp. 1-9

Customer retention, a critical business priority, has become a growing concern, especially in the telecommunications industry. This study addresses the need to anticipate and understand customer churn through the application of Deep Learning models. The central focus of the research was the...

Persistent link: https://www.econbiz.de/10014518907

Explaining and predicting customer churn by monotonic rules induced from ordinal data

Szeląg, Marcin; Słowiński, Roman - In: European journal of operational research : EJOR 317 (2024) 2, pp. 414-424

Persistent link: https://www.econbiz.de/10014635819

Proaktives Kundenbindungsmanagement im Werbeartikelhandel : Entwicklung eines Machine-Learning-Modells zur Prognose von Kundenabwanderungen

Schemm, Jan; Schwarz, Christian; Strickrodt, Marc - 2024

provides an empirical case study for the development of a churn prediction model in non-contractual B2B customer relationships …

Persistent link: https://www.econbiz.de/10015099136

Online newspaper subscriptions : using machine learning to reduce and understand customer churn

Belchior, Lúcia Madeira; António, Nuno; Fernandes, … - In: Journal of media business studies 21 (2024) 4, pp. 364-387

Persistent link: https://www.econbiz.de/10015178020

User churn model in e-commerce retail

Fridrich, Martin; Dostál, Petr - In: Scientific papers of the University of Pardubice 30 (2022) 1, pp. 1-12

In e-commerce retail, maintaining a healthy customer base through retention management is necessary. Churn prediction …-making associated with churn prediction efforts, e.g., retention campaign design. …

Persistent link: https://www.econbiz.de/10013206075