Search Results - subject:"Customer churn"

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

An adaptive analytics framework for customer retention through integrative feature optimization and ensemble learning

Syah, Rahmad B. Y.; Elveny, Marischa - 2025

An adaptive analytics workflow is presented for customer churn prediction, combining Principal Component Analysis for …

Persistent link: https://www.econbiz.de/10015506769

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

industry. This study addresses the need to anticipate and understand customer churn through the application of Deep Learning … predicting customer churn, providing companies with a valuable tool to improve retention and mitigate associated losses. …

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

Determinants of churn in telecommunication services : a systematic literature review

Ribeiro, Hugo; Barbosa, Belem; Moreira, António Carrizo; … - In: Management review quarterly 74 (2024) 3, pp. 1327-1364

Persistent link: https://www.econbiz.de/10015125058

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

Managing customer retention is critical to a company's proftability and frm value. However, predicting customer churn … perspective, the framework provides managers with valuable information to predict customer churn and develop strategies for …

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

Preventing customer churn with artificial intelligence-based analytics : teaching case study

Yigit, Anil; Korherr, Philipp; Kanbach, Dominik K. - 2024

Persistent link: https://www.econbiz.de/10014483352

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

Extreme gradient boosting trees with efficient Bayesian optimization for profit-driven customer churn prediction

Liu, Zhenkun; Jiang, Ping; De Bock, Koen W.; Wang, Jianzhou - In: Technological forecasting and social change : an … 198 (2024), pp. 1-16

Persistent link: https://www.econbiz.de/10015076450

Exploiting time-varying RFM measures for customer churn prediction with deep neural networks

Mena, Gary; Coussement, Kristof; De Bock, Koen W.; De … - In: Annals of Operations Research 339 (2023) 1, pp. 765-787

performance in modeling sequential unstructured data. However, little is known about their merit to model customer churn with time … customer churn prediction (CCP) using time-varying behavioral features in the form of recency, frequency, and monetary value …

Persistent link: https://www.econbiz.de/10015327899

Exploiting time-varying RFM measures for customer churn prediction with deep neural networks

Mena, Gary; Coussement, Kristof; De Bock, Koen W.; De … - In: Annals of Operations Research 339 (2023) 1, pp. 765-787

Persistent link: https://www.econbiz.de/10015402125