Executive Master of Management

Applied Marketing Analytics

This course teaches you to find and extract important marketing data, how to know what is working or not working in terms of marketing in your own firm, as well as teaching you how to employ analytics in practice in a simple way.

WHY APPLIED MARKETING ANALYTICS? 

In the fast-paced market, where competition is fierce, rate of technology-change wild and consumers empowered and unpredictable, it has become more crucial than ever to understand the trade-offs between elements that are driving business performance.

While data availability is overwhelming, managers are struggling in analysing the increasing amount of information they have. Never before did managers have this much information on customers, partners and competition at disposal to make informed, smarter decisions; yet they are more than ever criticised about the lack of actionable insights that derive from it.

This course aims to teach basic skills in marketing decision-making based on a systematic approach to exploit data that help managers to increase the effectiveness of marketing decisions.

TOPICS AND SCHEDULE

Day 1:

  • Introduction to the course and background for software use
  • Segmentation (classification of customers), targeting and positioning (perceptual-maps creation) tools (Cluster analysis, Latent-classes, Perceptional Mapping) – explanations, hands-on exercise in Excel

Day 2:

  • Designing and developing customer-centric new products and services and forecasting the sales of new products/services (Conjoint analysis, Diffusion models) - explanations, hands-on exercise in Excel

Day 3:

  • Understanding individual choices customers make and the main drivers (Choice models: single choice to buy or not, choosing between several brands) - explanations, hands-on exercise in Excel

Day 4:

  • Understanding customer value through Customer Lifetime Value (CLV) metrics - explanations, hands-on exercise in Excel

Day 5:

  • Measuring impact of digital marketing and social media investments on business performance - explanations, hands-on exercise in Excel

Day 6:

  • Optimisation of resource allocation across different marketing instruments, customer segments, products and channels – explanations, hands-on exercise in Excel

WHO IS THIS PROGRAMME FOR?

This course is intended for business managers interested in driving business performance, whether you have an extensive marketing background or not.

It is tailored towards managers who are not trained as computer engineers, but rather as business professionals who have to use data to improve marketing decision-making in their everyday tasks.

Faculty

Matilda Dorotic

Matilda Dorotic is an Associate Professor in the Department of Marketing at BI. Her research interests include customer engagement, customer value management, effectiveness of rewarding and loyalty programmes. Recently, she has also focused on how leaders can analyse the effect of big data and social media. 

Contact us

Please don’t hesitate to contact us if you have any questions or would like further information about our Executive Programmes.

Administration

With all of our master programmes, you will have a direct contact person who will be available from the time of application until the final exam.

Oslo: Djordje Maric:
Telephone - +47 98 25 17 85 - E-mail: djordje.maric@bi.no

Practical information

Start date and schedule

Oslo 2018/2019

Online «kick-off»: 15 Oct
Module 1: 22 -23 Oct
Module 2: 26 – 27 Nov
Module 3: 10 -11 Jan

Exam: 18 – 21 Jan
Project delivery: 15 Feb


This course is conducted through a combination of campus and online learning process. The campus module will consist of 3 sessions x 2 days. The online module will combine online content, videos and excercises to support the learning, both individually and in groups. The combination of campus and online learning process equals 75 lecturing hours over one semester.

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 that is not included on the course homepage or other course materials.

In each session, students will have an opportunity to learn hands-on different tools in Excel software with add on modules. In-class and online exercises will include working on available datasets and case study datasets. 

Participating in the course will require access to a pc/laptop with Microsoft Excel installed.

Please note that the licence for the add-in to the windows version of microsoft excel is required for this course! This add-in to Microsoft Excel adds statistical analysis features to basic Microsoft Excel functionality. The costs of a student's academic subscription to the software and business cases for six months is approximately 45 US dollars (around 370 NOK, subject to exchange rate fluctuations).

The individual licences for the software are paid by the students!

Interested students can find more details about the software at http://www.decisionpro.biz/students. Note: Mac users can obtain the same functionalityas Windows users by using the Windows virtual machine software.

In addition, the course may use selected Harvard business cases for which participants can obtain a student access from Harvard Business Publishing (HBP). Up to four cases could be used in the course and students are required to pay for the access to the case studies from HBP (the average price per case for students is around 4.5 US dollars (around 35 NOK per case)).

Exam fall 2018

The students are evaluated through an individual home assignment and a (final) term paper. The term paper accounts for 60% of the total grade, and may be written individually or in groups of maximum three persons. The individual 72 hour home assignment accounts for 40% of the total grade. All evaluations must be passed to obtain a certificate for the course.

Both the term paper and home assignment are based on the application of the concepts and tools learned in the course and provides an opportunity to implement the learned skills on your firm’s data in the final project.

Admission requirements

Read the admission requirements for this programme.

Apply now