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EBA 3640 Marketing Analytics

EBA 3640 Marketing Analytics

Course code: 
EBA 3640
Course coordinator: 
Stefan Worm
Course name in Norwegian: 
Marketing Analytics
Product category: 
Bachelor of Data Science for Business - Programme Courses
2025 Spring
Active status: 
Level of study: 
Teaching language: 
Course type: 
One semester

This course aims to teach basic skills in marketing decision-making based on a systematic analytical approach to harnessing data that help managers to increase the effectiveness of marketing decisions. The course is tailored towards students who are not trained as computer engineers but rather as business professionals who have to acquire know-how in using data to improve marketing decision-making in their everyday tasks (e.g. deciding which customer segments should be targeted, how to evaluate the potential costs versus return-on-investing in different marketing activities e.g. from online or offline campaigns, or testing how to develop a new product and improve the existing one).

We use an “Explain-Show-Do-Practice” approach to learning that encompasses explanations in the lectures followed up by a combination of class discussion, case study analysis and practical hands-on exercises with practice datasets in using statistics software. We do not go deeply into the statistics and mathematics behind the methods used in the academic models behind the tools, but rather provide you with an understanding of what the model could be used for, intuitively how it works and which data do you need to have as an input and how to evaluate the output that you would get from the software. We use an add-on module in Excel to make this course highly relevant and applicable to manager’s actual decision-making.

Learning outcomes - Knowledge

After completed course students shall:

  • Understand how different analytical approaches can inform specific marketing decisions.
  • Know which type of data are needed for each method and understand how to structure such data.
  • Understand the key intuition behind different analytical methods.
  • Understand how to find, interpret, reconcile, and assess key numbers from statistical output.
Learning outcomes - Skills

After completed course students shall be able to:

  • Select the appropriate analytical approach to answer specific managerial questions
  • Structure and clean data required
  • Run data analysis using statistical software
  • Validate, assess, interpret, and present the results
  • Articulate an analysis' limitations and strengths
  • Formulate strategy recommendations
General Competence


Course content
  • Customer Value Assessment and Valuing Customers
  • Segmentation and Targeting
  • Positioning
  • Forecasting
  • Analyzing brand-, offering-, and relationship-based competitive advantage
  • Market Response and Marketing Mix Models
  • Online Marketing Data and Analytics
  • Experimentation and A/B-testing

(the above list is tentative and could change)

Teaching and learning activities
  • Participants will learn how to carry out marketing analytics using real-life data and a statistical analysis package (e.g., Enginius).
  • Participants/study groups are required to submit their solutions to written assignments in written.
  • Participants will perform asynchronous learning activities throughout the semester.
Software tools
Software defined under the section "Teaching and learning activities".
Additional information

According to BI's policy, students have to purchase access to the marketing analysis suite (e.g., Enginius) at their own cost.


Higher Education Entrance Qualification


Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge
  • Introductory statistics
  • Introduction to Marketing
Mandatory courseworkCourseworks givenCourseworks requiredComment coursework
Mandatory53Participants will submit 5 different work requirements (i.e., exercises) over the course of the semester. They will need to get approved for 3 of these in order to participate in the final exam.
Mandatory coursework:
Mandatory coursework:Mandatory
Courseworks given:5
Courseworks required:3
Comment coursework:Participants will submit 5 different work requirements (i.e., exercises) over the course of the semester. They will need to get approved for 3 of these in order to participate in the final exam.
Exam category: 
School Exam
Form of assessment: 
Structured Test
Exam/hand-in semester: 
First Semester
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
2 Hour(s)
Final exam: At the end of the course, there will be a final exam compromising a mixture of open- and close-ended questions.
Exam code: 
EBA 36401
Grading scale: 
Examination every semester
Type of Assessment: 
Ordinary examination
Total weight: 
Student workload
36 Hour(s)
Feedback activities and counselling
6 Hour(s)
Review of assignments in plenary
Student's own work with learning resources
108 Hour(s)
30 Hour(s)
20 Hour(s)
Sum workload: 

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.