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GRA 6435 Customer Value Analytics

GRA 6435 Customer Value Analytics

Course code: 
GRA 6435
Department: 
Marketing
Credits: 
6
Course coordinator: 
Rutger Daniel van Oest
Course name in Norwegian: 
Customer Value Analytics
Product category: 
Master
Portfolio: 
MSc in Strategic Marketing Management
Semester: 
2025 Spring
Active status: 
Active
Level of study: 
Master
Teaching language: 
English
Course type: 
One semester
Introduction

We witness an increased emphasis on ensuring return on marketing investments, and thus financial sustainability of the marketing discipline. With this, customers should be viewed as assets representing the firm's future cash flow. The objective of this course is to expose our graduate students to the new role of marketing and provide them with quantitative techniques to compute customer value and the financial impacts of various marketing decisions on customer value, and ultimately firm value.

Learning outcomes - Knowledge

The learning outcome of this course is to appreciate the concept of marketing accountability and acquire concrete quantitative techniques to put into practice. The course takes several angles to compute customer value (e.g., survey-based data versus behavioral customer data, contractual versus non-contractual settings, analytical formulas versus empirical analysis, etc.)

Learning outcomes - Skills
  • Being able to think about marketing actions in terms of financial implications.
  • Acquiring some basic but important and frequently used Excel skills to implement the discussed models in Excel.
General Competence

Thinking about marketing in terms of financial accountability and becoming more confident with mathematical and statistical modeling in general.

Course content

Being able to compute customer value and to model aspects impacting customer equity is central to the course. The course will consist of lectures and a group assignment; it will contain a large quantitative component. It should be interpreted as a reasonably advanced marketing research course.

Teaching and learning activities

The course will be a combination of lectures and a group assignment. It will contain a large quantitative component. We will cover topics such as customer selection, customer lifetime value, managing customers as investments, and customer base analysis. 

Software tools
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. The lecturer will assume that students have installed all software (Excel for most lectures, and possibly SPSS) and have downloaded all files made available on ItsLearning before each lecture starts.

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)
Comment: 
Assignment
Exam code: 
GRA 64352
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 64353
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
36 Hour(s)
Group work / Assignments
24 Hour(s)
Prepare for teaching
100 Hour(s)
Includes small homeworks, processing of lecture slides and readings after each lecture, preparing for the exam etc.
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.