Marketing Analytics (BØK345)
How can firms extract useful information out of the vast amount of data? How can firms use data to make informed marketing decisions? This course teaches students how to apply various analytical tools to make sense out of data while exploring real world business challenges. Students will learn to run various models and analyses to provide solutions to marketing problems.
Course description for study year 2023-2024. Please note that changes may occur.
Semester tution start
Number of semesters
Language of instruction
1. Introduction to Marketing Analytics
- A brief statistical review
- A brief review of marketing strategy
- What is an analysis-based solution?
- Introduction to statistical software
2. Dependent variable techniques
- Linear regression analysis
- Logistic regression analysis
3. Inter-relationship techniques
- Cluster analysis
- Principal component analysis
4. Product design analysis
- Conjoint analysis
5. Final Project
- Research design
- Data analysis
- Reporting results
Upon completion of this course, students should gain the knowledge of:
- the fundamental data analytical techniques, such as various regression models, classification and segmentation tools
- how to obtain business insights from data analytics
Upon completion of this course, students will be able to:
- identify and carry out the appropriate analytical method for a given problem
- draw scientifically sound conclusions from analytical results
- use software to conduct statistics analyses
- independently develop and carry out their own research projects and communicate results from such projects
Required prerequisite knowledge
BØK104 Statistics and social science methodology
Students are expected to have completed compulsory levels of mathematics, statistics and economics for bachelor students in business.
Term paper in group and individual digital written exam
|Form of assessment||Weight||Duration||Marks||Aid|
|Term paper in group||45/100||1 Semesters||Letter grades||All|
|Individual digital written exam||55/100||4 Hours||Letter grades|
1. The term paper (45%): work in groups of 3-4 students. Due at the end of the term. There is no possibility of repeating (resit) the exam for the group project. Individual digital exam (55%). All the assessments are given and responded to in English.
The weekly assignments are given in the form of individual questions or group work. Groups are assigned by the instructor. All assignments are mandatory, and students need to "pass" all the assignments in order to write the term paper.
Group work is an important aspect of this course and integrated into the course meetings. Thus, students are required to attend 80% of the course meetings during the semester. Those who cannot meet this requirement should not take this course.
Course coordinator:Robert Kreuzbauer
Course coordinator:Shuai Yan
Method of work
The course will include a combination of lectures, group work sessions, mandatory assignments, and self-study. Students are expected to prepare for the lectures by reading the relevant part of the curriculum that will be covered in each lecture.
The total work load in this course is estimated to be 264 hours.
Lectures and group work sessions: 50 hours
Weekly assignments: 80 hours
Self-study: 80 hours
Final project: 50 hours
Final exam: 4 hours
|Research methods in the social sciences (BRH220_1)||10|