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Market Insights and Analysis

Module name (EN):
Name of module in study programme. It should be precise and clear.
Market Insights and Analysis
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Marketing Science, Master, regulation 01.10.2026
Module code: MAMSc-110
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P420-0556, P420-0557
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2U (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
6
Semester: 1
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam (can be repeated semesterly) and term paper with presentation (can be repeated annually)

[updated 25.08.2026]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

DFMIM-W-201 Management, Master, regulation 01.10.2026 , semester 2, optional course
MAMSc-110 (P420-0556, P420-0557) Marketing Science, Master, regulation 01.04.2025 , semester 1, mandatory course
MAMSc-110 (P420-0556, P420-0557) Marketing Science, Master, regulation 01.10.2026 , semester 1, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 180 hours (equivalent to 6 ECTS credits).
There are therefore 135 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Tatjana König
Lecturer: Prof. Dr. Tatjana König

[updated 12.03.2026]
Learning outcomes:
Learning outcomes/skills:
 
After successfully completing this module students will:
•        be able to evaluate empirical studies and, based on the underlying measurement levels and research questions, identify and apply appropriate methods for the given dataset
•        be able to evaluate the application and quality of various empirical methods (including those used for construct measurement, first generation) based on the relevant quality criteria
•        be able to interpret the results of various empirical methods (e.g., multivariate analysis)
•        be able to process analytical results into information and present and visualize them clearly for both academic and practical audiences
•        be able to derive recommendations for action in academia and/or practice based on the findings obtained and, where applicable, current scientific and/or practical discussions
•        be able to critically reflect on their progress in developing their skills and to be able to acquire new knowledge independently
•        be able to approach group work in a solution-oriented manner, assess their own contribution as well as that of other team members, and coordinate efforts in a way that maximizes benefits
 


[updated 25.08.2026]
Module content:
•        Methodology of empirical surveys
•        Refresher on market research:  scales, scale levels, survey methods, and hypothesis testing.
•        Designing survey instruments (questionnaires)
•        Basic concepts and overview of (multivariate) methods, as well as procedures, specific considerations when using them in SPSS, and their benefits for marketing decisions, e.g., regarding:
 
-        T-test for independent samples
-        Regression analysis
-        Analysis of variance
-        Factor analysis and reliability analysis
-        Cluster analysis
-        Conjoint analysis


[updated 25.08.2026]
Teaching methods/Media:
Lecture with exercises (project work) using SPSS, supported by e-learning (e.g., Moodle): Specially prepared documents (for example: lecture notes) / self-study media (for example: videos) on technical and methodological knowledge

[updated 25.08.2026]
Recommended or required reading:
- Backhaus, K., Erichson, B., Plinke, W., Weiber, R. (aktuelle Auflage): Multivariate Analysemethoden – Eine anwendungsorientierte Einführung, Hamburg.
- Hair, J.F. (Jr.), Black, W., C., Babin, B.J., Anderson, R.E., Tatham, R.L. (aktuellste Aufl.): Multivariate Data Analysis, Upper Sadle River, New Jersey.
- Herrmann, A., Homburg, Ch., Klarmann, M. (Hrsg.): Handbuch Marktforschung –Methoden, Anwendungen, Praxisbeispiele, aktuelleste Auflage, Wiesbaden.
- Rudolf, M., Müller, J. (aktuellste Aufl.): Multivariate Verfahren, Göttingen u.a.
- Sarstedt, M., Mooi, E. (aktuellste Aufl.), A Concise Guide to Market Research: The Process, Data, Methods, Using IBM SPSS Statistics, Springer
 


[updated 25.08.2026]
 
[Fri Sep 11 05:50:56 CEST 2026, CKEY=mmiaa, BKEY=msm4, CID=MAMSc-110, LANGUAGE=en, DATE=11.09.2026]