AI-Driven Marketing Analytics (SoSe 2026)
Veranstaltungszeitplan
| Tag | Zeit | Häufigkeit | Datum | Raum |
|---|---|---|---|---|
| Dienstag | 10:00- 14:00 Uhr | wöchentlich | 14.04.2026- 19.05.2026 | Scharnhorststr. 100, SCH 100.3 |
| Mittwoch | 16:00- 18:00 Uhr | wöchentlich | 15.04.2026- 20.05.2026 | Juridicum, JUR 498 |
Hinweis
In today’s increasingly digital marketplace, firms continuously seek new ways to build and sustain competitive advantage. One of the most powerful levers for doing so is marketing analytics: the systematic use of data to inform brand strategy and improve customer experience. This course provides a comprehensive introduction to how data-driven insights can be used to analyze, guide, and optimize marketing decisions.
Participants will learn how diverse data sources — including social media content, online reviews, and customer interaction data — can be leveraged to measure and improve key outcomes such as brand awareness, customer satisfaction, and loyalty. The course also covers practical application areas such as extracting actionable brand insights from review text, identifying optimization potential in customer feedback, customer segmentation, and loyalty enhancement strategies.
A central focus of the course is AI-driven marketing analytics, including methods such as text classification and image classification. In addition, foundational concepts necessary for sound data-driven decision-making (such as causal reasoning and interpretation of analytical results) are introduced and discussed.
In the accompanying exercise sessions, participants will apply core concepts using state-of-the-art analytical tools in R. The emphasis is on conceptual understanding and correct interpretation of analytical methods rather than programming depth. At the same time, additional programming support is provided for students who wish to further develop their technical skills.
The course also addresses ethical and societal implications of marketing analytics. Topics such as data privacy, security, and responsible AI use are discussed to ensure participants understand both the opportunities and responsibilities associated with data-driven marketing.
By the end of the course, participants will have a strong foundation in AI-enabled marketing analytics and will be equipped to use data effectively to support strategic decision-making, strengthen brand performance, and design more meaningful customer experience.
Dozenten
- Prof. Dr. Jens Paschmann (verantwortlich)