Marketing Analytics (MSB202)
"The world’s most valuable resource is no longer oil, but data" - The Economist
Marketing is not just an art; it requires the use of data and quantitative techniques to support marketing decisions and strategies in a rapidly changing market environment. As data has become one of the key factors shaping today’s businesses, firms are increasingly seeking managers and analysts with advanced background in marketing models to make effective data-driven marketing decisions.
Course description for study year 2023-2024. Please note that changes may occur.
Semester tution start
Number of semesters
Language of instruction
Upon completion of the course, students will have knowledge of:
- Key analytical models in marketing
- The strengths and weaknesses and when to employ the different models
- The challenges and necessary considerations for various model specifications
After completion of this course, students will be able to:
- Analyze marketing data and apply marketing models using programming language R
- Interpret results from marketing models and support managerial recommendations with justifications
- Demonstrate ability to communicate results and recommendations effectively
- Evaluate the strengths and weaknesses of different models in a marketing decision context
Required prerequisite knowledge
Take-home exam (individual) and Portfolio of mandatory work components (group)
|Form of assessment||Weight||Duration||Marks||Aid|
|Take-home exam (individual)||1/2||14 Days||Letter grades|
|Portfolio of mandatory work components (group)||1/2||7 Days||Letter grades|
The final grade is based on a take-home exam (individual) and a portfolio of mandatory work components, including group assignments.Students failing the portfolio evaluation will be granted the opportunity of taking a deferred exam. This exam will take the form of new written individual assignments.
The following are mandatory course requirements: class participation (70%), lab exercises, and presentations. In order to take the exams, students must pass all coursework requirements.
70% attendance at all mandatory sessions starting from week 1 of teaching.
Course teacher:Mainak Sarkar
Course coordinator:Mainak Sarkar
Study Program Director:Yuko Onozaka
Method of work
Lectures and tutorials, labs, group work, and independent study. The estimated distribution of ECTS hours are as follows:
1. Lectures and tutorials: 50 hours
2. Group work and labs: 110 hours
3. Independent study of course material 120 hours
|Advanced Marketing Analytics (MØA202_1)||10|