TBC

This course is available on the CEMS Exchange, Global MSc in Management, Global MSc in Management (CEMS MIM), Global MSc in Management (MBA Exchange), MBA Exchange, MSc in Management (1 Year Programme), MSc in Marketing and MSc in Strategic Communications. This course is available with permission as an outside option to students on other programmes where regulations permit.

Marketing managers need to make a variety of decisions about, for example, product features, prices, advertising (online and offline), distribution, and sales compensation plans. In making these decisions, managers choose from among alternative courses of action in a complex and uncertain world. Increasingly, in this age of big data, companies that emerge as market leaders tend to be the ones that employ sophisticated marketing analytics. This course in marketing analytics will entail a deep-dive into state-of-the-art marketing analytics models that allow managers to make evidence-based decisions regarding launching new products or innovations and managing more mature products and brands.

The course will focus upon the use of cutting-edge data analytic techniques to understand and inform managerial decision making with a primary focus on the formulation of dynamic marketing policies. The course is structured to enable the students to gain familiarity and deepen their knowledge and skills. The course will introduce techniques for advanced data visualisation, multiple regression analysis (including interaction effects), discrete choice modelling, and causal inference through A/B testing. Other topics may include panel data techniques, instrumental variables,difference-in-differences approach, regression discontinuity design, probability models for customer management, and propensity score matching. Applications and case studies will come from recent research in marketing and cover topics from commercial, social, and political marketing.

30 hours of lectures in the WT.

Students will be engaged in analysing several data sets using the techniques learned in class. This will set the stage for their group project (gathering and analysing data) as well as the take-home assignment (which will involve analysing data sets given to them).

• Mooi, E., Sarstedt, M., Mooi-Reci, I. Market Research: The Process, Data, and Methods Using Stata. Springer, 2017.

• Malhotra, N. Marketing Research: An Applied Orientation, Global (7th) Edition. Pearson, 2019.

• Angrist, J., Pischke, J.-S. Mastering Metrics: The Path from Cause to Effect. Princeton University Press, 2017

Take-home assessment (55%) and group project (45%) in the WT.