Excerpt from course description

Research for Marketing Decisions II

Introduction

Technological developments and the growing availability of high quality data are transforming marketing into an increasingly quantitative profession. While creativity remains important, marketing professionals must also be able to analyze data and draw meaningful insights to support better decisions. This requires a solid understanding of marketing analytics and the tools used to interpret complex datasets.

In this course, you will learn how to analyze secondary data using multivariate techniques in order to address marketing problems and support managerial decision making. The focus is on understanding which analytical approach fits a particular marketing question. Students will work with real data, develop managerial recommendations, and learn how to communicate their insights clearly. The course therefore emphasizes the managerial use of analytical tools rather than statistics for its own sake. It also introduces recent developments in marketing research and familiarizes students with analytical methods that are increasingly important in modern marketing practice.

Course content

Course outline:

  • Refresher in inferential statistics

  • Analysis of variance (ANOVA) and related methods

  • (Logistic) regression analysis

  • Principal components analysis

  • Cluster analysis

  • Conjoint analysis

  • Presentation and written reporting of findings

NB: This course outline may be subject to change.

 

Module 2: Synthesis and Communication

Purpose: Focus on bringing everything together into a compelling, ethical, and business-relevant narrative.

Topics

  • Structuring and writing research reports

  • Visualizing and presenting findings to decision-makers

  • Critical evaluation of sources and claims

  • Meta-analysis and systematic review basics

  • Transparency and limitations in research

 

Connections: Reinforces that research is not done until it is communicated clearly and ethically. Encourage synthesis across qualitative and quantitative insights.

Disclaimer

This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.