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
Article (5)
Academic (4)
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Gabel, S., Molitor, D., & Spann, M. (2024). The Effect of an Ad Ban on Retailer Sales: Insights from a Natural Experiment. Marketing Science, 43(4), 723-733. https://doi.org/10.1287/mksc.2023.0019
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Gabel, S., & Guhl, D. (2022). Comparing the Effectiveness of Rewards and Individually Targeted Coupons in Loyalty Programs. Journal of Retailing, 98(3), 395-411. https://doi.org//10.1016/j.jretai.2021.08.001
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Gabel, S., & Timoshenko, A. (2022). Product Choice with Large Assortments: A Scalable Deep-Learning Model. Management Science, 68(3), 1808-1827. https://doi.org/10.1287/mnsc.2021.3969
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Gabel, S., Guhl, D., & Klapper, D. (2019). P2V-MAP: Mapping Market Structures for Large Retail Assortments. Journal of Marketing Research, 56(4), 557-580. https://doi.org/10.1177/0022243719833631
Professional (1)
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Gabel, S., Simester, D., & Timoshenko, A. (2024). How Retailers Became Ad Platforms. Harvard Business Review (digital). https://hbr.org/2024/06/how-retailers-became-ad-platforms
Conference proceeding (1)
Academic (1)
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Schrage, R., Kenning, P., Guhl, D., & Gabel, S. (2021). Price Personalisation Technology in Retail Stores: Examining the Role of Users' Trust. In International Conference on Information Systems, ICIS 2020 - Making Digital Inclusive: Blending the Local and the Global, Hyderabad, India, December 13-16, 2020 Article 1900 Association for Information Systems. https://aisel.aisnet.org/icis2020/implement_adopt/implement_adopt/7
Activities
Additional positions (1)
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Schwarz GruppeStart date approval: 01 Apr 2022End date approval: 31 Mar 2025Place: NECKARSULMDescription: Research cooperation
Additional activities (1)
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Workshop on Digital Markets (WDM)Sebastian Gabel (Organiser)12 May 2025 - 13 May 2025
Activity: Attendance > Attending an event (Academic)
Awards
Courses
Topics in Marketing Research A
- Study year: 2024/2025
- Code: BERMASC054
- Level: PhD
IM Research clinic
- Study year: 2025/2026, 2024/2025, 2023/2024
- Code: BM-IM-RC
- Level: Master
Marketing Strategy in the Age of AI: Achieving Sustainable Growth
- Study year: 2025/2026, 2024/2025, 2023/2024, 2022/2023
- Code: BM-IM16CC
- Level: Master
Past courses
Master thesis
- Study year: 2025/2026
- Code: BM-IM-CEMSTHESIS
- Level: Master
IM/CEMS 2024-2025
- Study year: 2023/2024
- Code: BM-IMCEMS2324
- Level: Master
Learning from big data
- Study year: 2023/2024, 2022/2023, 2021/2022
- Code: B3MIN1039
- Level: Bachelor, Bachelor 3, Bachelor 3
Learning from big data
- Study year: 2020/2021
- Code: BKBMIN039
- Level: Bachelor, Bachelor 3, Bachelor 3
