Sebastian Gabel


Marketing Strategy in the Age of AI, MSc (2023, 2024)

Successful managers need to understand how big data and marketing analytics can inform marketing strategy and marketing tactics. The objective of this course is to showcase the benefits of using a systematic and analytical approach to marketing decision-making. The course familiarizes students with concepts and methods they can use to tackle marketing problems. Example applications allow students to experience the value of quantitative methods in marketing even if they have little or no coding background. After completing this course, students will be able to solve marketing analytics problems in a scientific and process-driven manner.

Learning from Big Data, BSc (2021, 2022, 2023)

Every day, millions of consumers voice their opinions in product-review websites, blogs, and chat rooms. At the same time, retailers collect rich data sets that contain valuable information from their loyalty programs. In this era of big data, the availability of new, larger, and more diversified data sets creates exciting opportunities for marketing practitioners. This course first teaches how to formalize marketing problems as statistical models. It then shows how to solve marketing problems by complementing classical econometric techniques with modern machine learning methods. Students learn the needed tools and conceptual frameworks needed to identify and exploit the opportunities that big data sources create.

Machine Learning in Marketing: Theory and Applications, MSc (2020)

The course teaches students to solve real-world marketing problems using modern quantitative methods. It first reviews theoretical foundations in marketing, statistics, and probability theory, and then shows how to formalize marketing decisions as machine learning problems. It also equips students with the necessary tools to implement machine learning pipelines efficiently.