GRA 4139 Marketing Analytics

GRA 4139 Marketing Analytics

Course code: 
GRA 4139
Department: 
Marketing
Credits: 
6
Course coordinator: 
Auke Hunneman
Course name in Norwegian: 
Marketing Analytics
Product category: 
Master
Portfolio: 
MSc in Business Analytics
Semester: 
2025 Spring
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

Due to technological developments and the proliferation of high-quality data, marketing is becoming an increasingly quantitative profession. This means that marketing professionals should not only be creative, they also must have a solid background in marketing analytical tools in order to make sense of all the available data. This course aims to cover topics in marketing analytics, an area that is of utmost importance for the development of sound marketing strategies and tactics. It will be particularly useful for students who want to pursue a career in quantitative marketing and marketing consulting.

Learning outcomes - Knowledge
  • Know how to use statistical tools to evaluate the impacts of marketing decisions on relevant outcome variables like revenues, profits or customer lifetime value;
  • Understand which analytical tools are used for which marketing problems;
  • Gain an understanding of the data requirements and limitations of different marketing analytical tools.
Learning outcomes - Skills
  • Being able to use marketing models to support relevant marketing decisions;
  • Determine the effectiveness of several types of marketing investments.
General Competence
  • Becoming more confident with statistical analysis.
  • Understand the limitations of certain types of data (e.g., customer-level data) and certain marketing analytical tools.
Course content

Topics covered in this course include:

  1. Model specification, estimation, validation and use
  2. Market response models
  3. Choice models
  4. Customer base analysis, including latent-attrition models
Teaching and learning activities

-

Software tools
R
SPSS
Additional information

Please note that while attendance is not compulsory in all courses, it is the student’s own responsibility to obtain any information provided in class. 

All parts of the assessment must be passed in order to get a grade in the course.

 

Qualifications

All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.

Disclaimer

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

Assessments
Assessments
Exam category: 
Submission
Form of assessment: 
Submission PDF
Exam/hand-in semester: 
First Semester
Weight: 
30
Grouping: 
Group (2 - 3)
Duration: 
2 Week(s)
Exam code: 
GRA 41392
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Exam category: 
School Exam
Form of assessment: 
Written School Exam - digital
Exam/hand-in semester: 
First Semester
Weight: 
70
Grouping: 
Individual
Support materials: 
  • BI-approved exam calculator
  • Simple calculator
  • Bilingual dictionary
Duration: 
3 Hour(s)
Comment: 
Written examination under supervision.
Exam code: 
GRA 41393
Grading scale: 
ECTS
Resit: 
Examination when next scheduled course
Type of Assessment: 
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
24 Hour(s)
Group work / Assignments
24 Hour(s)
Prepare for teaching
100 Hour(s)
Student's own work with learning resources
12 Hour(s)
Sum workload: 
160

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.

Semester

Oversettelser