MG4F2 Half Unit
Marketing Analytics II: Analytics for Managing Innovations, Products and Brands
This information is for the 2018/19 session.
Prof Om Narasimhan NAB.5.06
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 make ongoing decisions about product features, prices, advertising (online and offline), distribution, sales compensation plans, and so on. 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 sequel course in Marketing Analytics will entail a deep-dive into the state-of-the-art Marketing Analytics models that allow managers to make scientific decisions regarding launching new products or innovations and managing more mature products and brands.
This 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 student to gain familiarity with techniques for scraping the web for data, sentiment analysis, multivariate regression, discrete choice modelling, probability models for customer management, causal inference through A/B testing, classification and regression trees, and introductory machine learning.
30 hours of lectures in the LT.
Students will be engaged in analysing a number of 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).
• Lilien GL, Kotler Ph, Moorthy KS. Marketing Models. Prentice Hall: Englewood Cliffs, 1992
• Leeflang PSH, Wittink DR, Wedel M, Naert PA. Building Models for Marketing Decisions. Kluwer Academic Publishers: Dordrecht / Boston 2000.
• Hanssens DM, Parsons LJ, Schultz RL. Market Response Models: Econometric and Time Serie Analysis. Kluwer Academic Publishers, Boston 2001.
• Lilien GL, Rangaswamy A. Marketing Engineering, 2nd edition. Prentice Hall: Upper Saddle River, NJ, 2003.
• Little JDC. Models and Managers: The Concept of a Decision Calculus. Management Science 1970; 16: B466-B485.
Other (45%), other (45%) and class participation (10%) in the LT.
Individual Take-home assignment (45%), due within 1 week of when it is assigned.
Group project (45%)
Individual Class participation (10%)
Total students 2017/18: 65
Average class size 2017/18: 65
Controlled access 2017/18: Yes
Value: Half Unit
Personal development skills
- Team working
- Problem solving
- Application of information skills
- Application of numeracy skills
- Commercial awareness
- Specialist skills