Qualitative Marketing Research and Data Analysis
People
Course director
Description
The content of the class follows the key steps of the research process, starting from research design (including the choice of qualitative vs quantitative designs), sampling, data collection, data analysis and presentation of the findings. As part of the course, students collectively carry out a research project, allowing them to gain hands-on, practical experience with each step of the marketing research process.
Objectives
This course will introduce students to the core principles and practice of qualitative marketing research. The course will enable students to
- understand the difference between qualitative and quantitative marketing research designs and to distinguish between the marketing problems that they are suited to answer
- compare sampling methods and design a qualitative sampling plan
- use the most important qualitative marketing research methods (interviews, focus groups, consumer ethnography and discourse analysis)
- carry out marketing research in on-line and real-life contexts
- assess the strengths and limitations of different qualitative research methods
- analyse qualitative data and draw managerial conclusions
- reflect on issues of validity, reliability and research ethics in the context of qualitative marketing research.
Teaching mode
In presence
Learning methods
In this class, students work on a research project in small groups. The teaching methods include lectures and workshops.The lectures give an overview of the particular research step/method. In the workshops, students apply the given step/method to the collective mini-research project. The course ends with the presentation of the research findings.
Examination information
- Final written exam (60 points)
- Individual assignments (30 points)
- Group assignment (10 points)
Pass is from grade 6.
Education
- Master of Science in Communication and Economics in Marketing and Transformative Economy, Lecture, 1st year
- Master of Science in Financial Technology and Computing, Lecture, Elective, 2nd year