Advanced methods in personalization for marketing decisions
Abstract
Collectively, these three chapters provide marketers and researchers with powerful tools to address personalization challenges commonly encountered in real-time applications, especially when serving a continuous stream of customers on websites, platforms, or mobile devices. The research advances marketing methodology by integrating innovative approaches from machine learning and econometrics to tackle important and practical challenges in marketing. The proposed methods are interpretable, computationally efficient, and can be directly applied to realtime personalization applications. Overall, these contributions not only broaden methodological perspectives in personalization research but also offer actionable solutions for practitioners aiming to implement scalable and effective personalization strategies in today’s competitive and rapidly evolving digital marketplace.
Fields of Study & Subjects
Digital Marketing and Social Media
Recommender Systems and Techniques
Consumer Market Behavior and Pricing
Publication details
- Journal / source
- EUR Research Repository (Erasmus University Rotterdam)
- Publication date
- 27 February 2026
- Language
- EN
- Document type
- Thesis