More information

Profile

I am an assistant professor at the Rotterdam School of Management. My research is located at the intersection of quantitative marketing, machine learning and econometrics. I develop and validate new machine learning methods for modeling the behavior of individual customers. My current projects focus on methodological research in Deep Learning that can be applied to promotion personalization, recommender systems, pricing, and assortment optimization in large-scale retailing settings. In my industry work, I collaborate with leading marketing solution providers and grocery retailers to design and implement advanced machine learning systems for scalable and automated marketing personalization. These marketing solutions have helped retailers to increase their revenue, return on advertising spend, and conversion rates.

For more information, please visit www.sebastiangabel.com.

Publications

Academic (3)

Academic (1)
  • Schrage, R., Kenning, P., Guhl, D., & Gabel, S. (2020). Price Personalisation Technology in Retail Stores: Examining the Role of Users' Trust. In Proceedings of the 41st International Conference on Information Systems, ICIS 2020, Making Digital Inclusive: Blending the Locak and the Global, Hyderabad, India, December 13-16, 2020 Association for Information Systems. https://aisel.aisnet.org/icis2020/implement_adopt/implement_adopt/7

Courses

Learning from big data

  • Study year: 2022/2023, 2021/2022
  • Code: B3MIN1039
  • Level: Bachelor, Bachelor 3, Bachelor 3

Marketing Strategy in the Age of Artificial Intelligence

  • Study year: 2022/2023
  • Code: BM-IM16CC
  • Level: Master

Past courses

Learning from big data

  • Study year: 2020/2021
  • Code: BKBMIN039
  • Level: Bachelor, Bachelor 3, Bachelor 3