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Marketing Analytics
Last Updated: 2026-06-01 11:33:45
Abstract
This lecture dives deep into AI-driven marketing, blending theory with hands-on data analysis from real-world retail scenarios. Students explore a diverse array of predictive analytics tools, engage in a competitive prediction challenge, and receive expert mentorship. Beyond marketing, they will acquire skills impacting various sectors. Perfect for aspiring marketers and AI enthusiasts.
Objective
- Data Insight Extraction: Derive value from real-world customer data. - AI & Analytics: Grasp machine learning and predictive model essentials. - Data Handling: Prepare and process customer data using top tools. - Modeling Mastery: Develop prediction models with diverse methods. - Broad Application: Use skills beyond marketing for predictive analysis. - Concise Documentation: Record methodologies and strategic choices effectively. - Industry Engagement: Network with experts and gain real-world insights.
Content
This lecture provides a holistic learning experience that pushes the boundaries of traditional classroom settings, allowing students to grapple with real-world customer data from an online retailer. The nexus of the future in marketing is at the intersection of Artificial Intelligence and data. In this class, students will be exposed to the dynamic world of machine learning and predictive analytics. They are not confined to a single approach — a vast landscape of statistical methods, software packages, and external data sources awaits their exploration and experimentation. Students will have the unique opportunity to participate in a riveting prediction competition. Their analytical prowess will be tested against real-world outcomes, culminating in a finale where teams present their insights before representatives from a leading online retailer. The curriculum begins with foundational lectures that introduce students to the bedrock principles of marketing analytics and hands-on data processing using industry-leading software packages. Throughout the course, specially scheduled sessions with seasoned lecturers ensure that students receive the mentorship and feedback necessary to refine and optimize their predictive models. While the primary focus lies in marketing, the skills and competencies students acquire in this lecture transcend disciplinary boundaries. They will be equipped with data handling and prediction strategies that can revolutionize decision-making in diverse sectors requiring continuous or binary metric predictions. Students will consolidate their learning and innovative methodologies in a well-crafted paper. This documentation will detail model comparisons, breakthroughs, and the rationale behind each strategic choice. This lecture, designed for aspiring marketers, data science enthusiasts, and AI aficionados alike, offers a seamless blend of theoretical insights and hands-on practice. Students will forge invaluable industry connections, broaden their academic and professional perspectives, and graduate with a universally applicable, state-of-the-art toolkit.
General Information
- Language
- English
- Levels
- MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar |
Marketing Analytics
Irregular lecture
|
|
14 h semesterly |