MKT 520: Market Research

This module gives an overview of the market research process and deals with methods for data analysis and interpretation. The emphasis is on multivariate methods of data analysis. In presenting those analytical methods, a special focus is on discussing strengths and weaknesses of different methods and on possible fields of application in market research projects. Moreover, the application of different methods by means of common statistical software packages will be demonstrated.

Learning outcomes
Participants gain a sound knowledge of how market research projects are conducted and are able to critically evaluate market research projects. Especially, students will have an understanding of the data analysis methods used in market research and how these are applied by means of statistical software. The students are familiar with the strengths and weaknesses of the presented methods and know their fields of application within market research projects.

Necessary prerequisites

Recommended prerequisites
Module CC 503, Basic marketing and statistic knowledge on Bachelor level / B.Sc. Business Administration

Forms of teaching and learningContact hoursIndependent study time
Lecture2 SWS9 SWS
Exercise class2 SWS5 SWS
ECTS credits6
Graded yes
Form of assessmentWritten exam (60 min)
Restricted admissionno
Further information
Performing lecturer
Prof. Dr. Florian Kraus
Prof. Dr. Florian Kraus
Frequency of offeringSpring semester
Duration of module 1 semester
Range of applicationM.Sc. MMM, M.Sc. WiPäd, M.Sc. VWL, M.Sc. Wirt. Inf., LL.M., MAKUWI
Preliminary course work
Program-specific Competency GoalsCG 1, CG 4
Course outline1. Market Research Basics
1.1. Fundamentals of market research
1.2. Determination of the data collection method
1.3. Sampling
1.4. Design of the research instrument
1.5. Data collection
1.6. Editing and coding of data
2. Market Research Methods: Multivariate Data Analysis
2.1. Analysis of Interdependence
2.1.1. Exploratory Factor Analysis
2.1.2. Confirmatory Factor Analysis
2.1.3. Cluster Analysis including Market Segmentation
2.2. Analysis of Dependence
2.2.1. Analysis of Variance
2.2.2. Multiple Regression Analysis
2.2.3. Structural Equation Modeling
2.2.4. Conjoint Analysis