Exportar Publicação

A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Belchior, L. M., António, N. & Fernandes, E. (2024). Online newspaper subscriptions: Using machine learning to reduce and understand customer churn. Journal of Media Business Studies. 21 (4), 364-387
Exportar Referência (IEEE) 
L. M. Belchior et al.,  "Online newspaper subscriptions: Using machine learning to reduce and understand customer churn", in Journal of Media Business Studies, vol. 21, no. 4, pp. 364-387, 2024
Exportar BibTeX 
@article{belchior2024_1766228248140,
	author = "Belchior, L. M. and António, N. and Fernandes, E.",
	title = "Online newspaper subscriptions: Using machine learning to reduce and understand customer churn",
	journal = "Journal of Media Business Studies",
	year = "2024",
	volume = "21",
	number = "4",
	doi = "10.1080/16522354.2024.2343638",
	pages = "364-387",
	url = "https://www.tandfonline.com/journals/romb20"
}
Exportar RIS 
TY  - JOUR
TI  - Online newspaper subscriptions: Using machine learning to reduce and understand customer churn
T2  - Journal of Media Business Studies
VL  - 21
IS  - 4
AU  - Belchior, L. M.
AU  - António, N.
AU  - Fernandes, E.
PY  - 2024
SP  - 364-387
SN  - 1652-2354
DO  - 10.1080/16522354.2024.2343638
UR  - https://www.tandfonline.com/journals/romb20
AB  - Modelling customer loyalty has been a central issue in customer relationship management, particularly in digital subscription business models. To guarantee news media sustainability, publishers implemented subscription models that need to define successful retention strategies. Thus, churn management has become pivotal in the media subscription business. The present study aims to understand what drives subscribers to churn by performing a Machine Learning approach to model the propensity to churn of online subscribers of a Portuguese newspaper. Two models were developed, tested, and evaluated in two timeframes. The first one considered all Business to Consumer (B2C) subscriptions, and the second only the B2C non-recurring subscriptions. The experimental results revealed important patterns of churners, which allowed the marketing and editorial teams to implement churn prevention and retention measures.
ER  -