0770 Marketing Research Design and Analysis A
Univ.Prof. Dr. Nils Wlömert
  • LV-Typ
  • Semesterstunden
  • Unterrichtssprache
29.09.2020 bis 04.10.2020
Anmeldung über LPIS
Hinweise zur LV
Die Lehrveranstaltung wird nur im WS angeboten.
Planpunkt(e) Master
Wochentag Datum Uhrzeit Raum
Dienstag 06.10.2020 14:00 - 18:00 Online-Einheit
Montag 12.10.2020 13:00 - 18:00 Online-Einheit
Montag 19.10.2020 13:00 - 17:00 Online-Einheit
Dienstag 20.10.2020 14:00 - 17:00 Online-Einheit
Freitag 23.10.2020 09:00 - 14:30 Online-Einheit
Donnerstag 29.10.2020 13:00 - 17:00 Online-Einheit
Montag 02.11.2020 13:00 - 18:00 Online-Einheit
Montag 09.11.2020 13:00 - 17:00 Online-Einheit
Montag 16.11.2020 13:30 - 16:30 Online-Einheit
Montag 23.11.2020 13:00 - 18:30 Online-Einheit
Montag 07.12.2020 13:00 - 19:00 Online-Einheit
Dienstag 15.12.2020 08:30 - 10:30 Online-Einheit

Ablauf der LV bei eingeschränktem Campusbetrieb

In case the of limited activity on campus, this course will be delivered using distance learning while keeping the original timeline. This mode of teaching will include asynchronous materials (e.g., an online tutorial including descriptions in text and video formats) as well as synchronous teaching elements (e.g., web streaming, chats, Q&A sessions). Students are required to familiarize themselves with the content by going through the asynchronous materials on their own. The synchronous teaching elements, such as live streaming sessions, provide ample opportunities to ask questions and clarify points that require further discussion. 

The grading elements will be adjusted according to this model of teaching. The class participation will be replaced by regular short online quizzes. The coaching sessions for the group project will be conducted online and all group presentations should be submitted in the form of recorded videos. The individual assigments will be complemented with asynchronous materials and additional online coaching sessions will be provided. The final exam will be conducted online. 

Inhalte der LV

Effective marketing decision-making requires accurate data, careful analysis of these data, and adequate information on the underlying marketing problem to be solved. This course focuses on how marketing decisions are supported by research techniques. We will discuss different research designs, data collection methods, measurement and scaling techniques, as well as methods for analyzing empirical data (i.e., hypothesis testing, analysis of variance, correlation & regression, factor analysis). The course helps you to acquire a thorough understanding of the marketing research process and the analytical techniques that are frequently used by marketing analysts to support marketing decisions, such as marketing-mix planning, market segmentation, brand positioning, and new product development. Further, we focus on how to use and to interpret the information provided by these techniques in practical business settings.

Lernergebnisse (Learning Outcomes)

The aims of this course are to teach students the methods, principles, and theories of modern marketing research and to apply these to practical business settings. The objectives of the course are:

  • To develop an understanding of the marketing research process and the most commonly used research techniques
  • To learn how information is obtained and delivered to solve marketing problems
  • To enhance your analytical skills, to develop the ability to translate business problems into actionable research questions andto design an adequate research plan to answer these questions
  • To understand methods and tools for data collection and analysis
  • To train your ability to analyze and interpret marketing research data using R, a leading software package for statistical data analysis
  • To improve your communication, presentation and team working skills

Regelung zur Anwesenheit

Attendance of the weekly Q&A sessions and the group coaching sessions via live video streaming (Zoom) is required for the successful completion of the course.


Due to the limited activity on campus, this course will be delivered using distance learning. This mode of teaching will include asynchronous teaching elements (e.g., pre-recorded videos) as well as synchronous elements (e.g., live video streaming, chats). The aim is to equip students with an understanding of the conceptual foundations of the analytical techniques before applying the acquired knowledge to real-world data sets. Students are required to familiarize themselves with the contents by means of self-study (i.e., by going through the materials on their own). This process will be aided by an online learning tutorial featuring textual descriptions of the contents along with R-code snippets and pre-recorded explanatory videos (see The weekly readings will be complemented by case studies and computer exercises, which aim to transfer the acquired knowledge to new business settings. These completed take-home assignments need to be handed in via Learn@WU within the indicated deadlines. Furthermore, the course comprises a group assignment in which students need to design and conduct their own market research project. The results of this project should be submitted in the form of a pre-recorded video presentation. The synchronous teaching elements, such as weekly interactive Q&A sessions and group coaching sessions via live video streaming (Zoom), provide ample opportunities to ask questions and clarify points that require further discussion. To facilitate the interaction among students, there will be an online forum for discussions about the contents.   

The course covers practical applications of data analytics for which the open source software R is required. R is a powerful tool for data analytics and visualization and you need to download and install R on your computer (it's free!). We recommend to use R via the integrated development environment (IDE) RStudio, which is also available for free:

Please also make use of the abundance of web resources regarding R (see here). For students who would like to further train the materials covered in class, we recommend DataCamp (, an online platform that offers interactive courses in data science at different levels. To facilitate the learning process you will obtain full access to the entire DataCamp course curriculum for the duration of the course. 

To be able to follow the curriculum and complete the weekly assignments, you need to read the materials assigned for the respective week. For the interactive Q&A and coaching sessions, it is highly recommended to come with questions or comments about the material that you think might be interesting and helpful to the class. 


Leistung(en) für eine Beurteilung

Grading is based on the following components:

  • Market research group project (questionnaire design, data collection & analysis, reporting & presentations) [weight: 30%]
  • Individual take-home computer exercises (statistical analysis of data sets) [weight: 20%]
  • Final online exam (concepts & methods) [weight: 40%]
  • Class participation (quantity & quality of contributions during the weekly Q&A sessions, contributions in the online forum, etc.) [weight: 10%]

These grading components will be weighted with the respective weights to arrive at the final grade percentage.

Please note that to ensure an equal contribution of group members for the group assignment, a peer assessment will be conducted among group members, which enters into the computation of the individual grades for the project. This means that the members of a group are required to assess other students regarding their relative contribution. 

To successfully pass this course, your weighted final grade needs to exceed 60%.

Teilnahmevoraussetzung(en) und Vergabe von Wartelistenplätzen

This course is designed for students of the WU Master's Program (MSc) in Marketing. Admittance to the program is a prerequisite for successful participation of the course.

Erreichbarkeit des/der Vortragenden

I am happy to answer your questions, so feel free to send me a short email ( Mirza Mujanovic will be the tutor for this course ( We will be available during the weekly Q&A sessions to clarify your questions. Mirza will be your point of contact for questions regarding the group project and the individual assignments. However, please note that before you contact us, you should try to solve problems on your own first (e.g., by using the online tutorial, doing research online, or asking class mates). 

Zuletzt bearbeitet: 15.09.2020