Marketing Analytics

Introduction

In today's marketing landscape, data literacy, performance measurement, and analytics skills have become essential for driving growth and efficient resource allocation and marketing decision-making. This course equips students with theoretical concepts and practical skills necessary to transform marketing data into actionable business insights.

Students will learn to apply statistical methods and data analysis concepts to real-world marketing problems within a specified software environment. Students will learn to identify and differentiate between key data sources and types, align marketing decision problems with the most appropriate data and analytical approaches, and understand the theoretical foundations, assumptions, and data requirements that make analyses credible. Through hands-on application with marketing case data, students will develop the ability to interpret and critically evaluate statistical outputs, derive and assess key marketing metrics, and formulate data-driven recommendations.

A central component of the course is bridging the gap between theory and practice by solving concrete marketing business problems. This provides students with the knowledge and skills necessary to generate data-driven insights and support marketing decisions.

Course content

The following gives a brief overview of topics that will be discussed in the course. This list is tentative and could be subject to change.

• Introduction to marketing analytics
• An overview of different types and sources of marketing relevant data
• Marketing response models for optimizing marketing activties and ressource allocation (simple marketing mix models)
• Predictive models for customer selection and targeting
• Managing customer heterogeneity (segmentation, targeting, and positioning)
• Models and metrics that support customer lifetime value (CLV) analysis

In addition, students will be exposed to various marketing metrics that are relevant for decision-making in the analytical contexts we discuss.