"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.
Marketing managers make frequent decisions about product features, prices, distribution options, and advertising budgets. This course provides an understanding of key marketing decisions as well as how data and marketing analytical tools can help managers make better decisions. This course thus takes a user’s perspective and shows how users can enhance their decision-making by translating data and modeling results into action. The course is particularly relevant for students with an interest in quantitative research in marketing and related areas. It is also recommended for practice-oriented students who wish to improve their methodological knowledge. The course also aims to prepare students who are writing their master thesis in marketing and students who wish to pursue a research career by entering a PhD program.
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
Take-home exam (individual)
Portfolio of mandatory work components (group)
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.
There must be an early dialogue between the course coordinator, the student representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.