After this course, the student should be able to:
1.Explain and work with the basic concepts of several standard market response models used to evaluate marketing actions at the market and individual customer level
2.Explain and understand existing marketing models and methods published in the academic literature
3.Evaluate existing marketing models and methods published in the academic literature
4.Understand the difference between several data types, and specify a suitable market response model depending on the data type
5.Estimate a market response using empirical data and statistical software
6.Interpret an estimated a market response in the context of the data underlying
the model, and draw managerial implications
7.Report in writing about the data analysis process and its managerial implications

Analytics in a marketing context is defined as 'a technology-enabled and model-supported approach to harness customer
and market data to enhance marketing decision making' (Lilien 2011). In this course students will be exposed
to a variety of ways in which the data richness available to modern firms can be used to guide the decision
making process of managers, and improve the accountability and impact of marketing. Within the course we focus on the increasingly digital channels through which firms interact with their customers, but also pay attention to traditional marketing instruments to foster a broad understanding of the ways in which firms can reach the market.
Consistent with the definition of analytics in a marketing context, two perspectives will be taken in this course: The market
and the customer perspective. From the market perspective, we will investigate how firms can gain model based
insights in the effectiveness of broad market actions such as (online and offline) advertising and price
promotions in order to improve future decisions. From the individual customer perspective, we will focus on marketing
actions aimed directly to specific customers with the aim to acquire, retain or develop these customers.
Students will be exposed to the existing academic literature on these topics to bring their knowledge up-to-date.
Using real-life datasets students will gain hands-on experience with several methods in each of the two
subfields. An important focus of the course is understanding the data analysis process and its managerial
implications, and communicating the outcomes thereof. In this way data driven insights has an impact on the
decision-making process within firms.

The literature will consist of a bundle of academic papers and book chapters. A detailed literature list will be available on the Eleum site of the course

All students who are admitted to the Master of Science in International Business can follow this course. In the assignments, students will have to use regression analysis and SPSS. So a background in regression analysis and SPSS is necessary.