Course content
The aim of the course is to gain an understanding of how marketing analytics can be used to create customer insights and thereby improve business intelligence to allow for more effective and efficient marketing activities. Specifically, the course aims at (1) providing students with knowledge about different types of marketing analytics and data visualization; (2) giving students an understanding of the core processes, frameworks, and techniques used in marketing analytics; (3) providing students with basic skills to apply different types of statistical and visual analytical techniques and interpret the results; and (4) providing students with knowledge about how different companies employ marketing analytics to create customer insights and business intelligence.
Companies today are facing oceans of data about, for example, customers, sales activities, transactions, markets, or competitors. These data offer numerous opportunities to inform marketing decision-making by providing insights and creating business intelligence. At the same time, however, the risk of information overload has substantially increased. In order to shift from intuitive decision-making to fact-based decision processes, marketers need to adopt an analytical marketing approach.
This course will give students a deeper understanding of how marketing analytics can be used to create customer insights and thereby improve business intelligence to allow for more effective and efficient marketing activities.
Students will learn how to apply different approaches to marketing analytics; learn how to use digital tools, techniques, and frameworks essential for transforming data into relevant information; learn how marketing analytics and data visualization can help companies to understand not only how customers have behaved in the past, but also to make accurate predictions about how customers will behave in the future, which in turn can help to optimize marketing activities.
Analytical techniques that students learn in the course will be based on the open-source statistical platform R. Students do not need to have prior experience with this program/platform.
See course description in course catalogue