MG4F2 Half Unit
Marketing Analytics II: Analytics for Managing Innovations, Products and Brands
This information is for the 2024/25 session.
Teacher responsible
Pavel Kireyev
Availability
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 and Society. This course is available with permission as an outside option to students on other programmes where regulations permit.
This course may be capped/subject to controlled access. For further information about the course's availability, please see the MG Elective Course Selection Moodle page (https://moodle.lse.ac.uk/course/view.php?id=3840).
Course content
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.
Teaching
30 hours of seminars in the WT.
In its Ethics Code, ÐÓ°ÉÂÛ̳ upholds a commitment to intellectual freedom. This means we will protect the freedom of expression of our students and staff and the right to engage in healthy debate in the classroom.
Formative coursework
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).
Indicative reading
• 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
Assessment
Take-home assessment (55%) and group project (45%) in the WT.
Key facts
Department: Management
Total students 2023/24: 48
Average class size 2023/24: 49
Controlled access 2023/24: Yes
Value: Half Unit
Course selection videos
Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.
Personal development skills
- Leadership
- Self-management
- Team working
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Commercial awareness
- Specialist skills