Overview of the marketing research process, its importance, and its application in real-world scenarios.

Learning how to accurately identify and articulate marketing problems. Exploring techniques for setting clear and achievable research objectives that guide the research process effectively.

Understanding the components of a comprehensive research brief and how to communicate research needs to stakeholders. Examining criteria and best practices for assessing and selecting appropriate research proposals

Exploring various research designs (exploratory, descriptive, causal) and methodologies. Learning how to choose the most suitable approach based on research objectives and market conditions.

Delving into qualitative research methods such as focus groups, in-depth interviews, and ethnography. Discussing their applicability, execution, and how they provide insights into consumer behavior and attitudes.

Examining quantitative research methods including surveys, experiments, and observation studies. Understanding how to collect and analyze numerical data to support marketing decisions.

Learning about different sampling techniques (probability and non-probability sampling) and determining appropriate sample sizes. Discussing effective data collection methods and managing fieldwork processes.

In-class presentations: Each micro-team will present their findings in a 10-15-minute in-class presentation. The presentation will be followed by a discussion, during which you will need to answer questions and demonstrate a deep understanding of your research.

Understanding concepts of measurement validity and reliability. Exploring various scaling techniques (Likert, semantic differential, rank-order) and their use in capturing consumer perceptions and preferences.

Learning principles of effective questionnaire design, including question wording, sequencing, and formatting. Discussing strategies to enhance response rates and data quality in survey research.

Exploring methods for analyzing qualitative data, such as thematic analysis and content analysis. Learning how to interpret and derive meaningful insights from non-numerical data.

Workshops on performing basic quantitative data analysis, including data cleaning, summary statistics, and creating visualizations. This session will also focus on the correct use of terminology in describing statistical methods and results. Group exercises on preparing research reports and presenting findings effectively using graphs, charts, and tables, with an emphasis on accurate and precise language.

Overall semester wrap-up. Class discussion and summary of what we have learnt together. Group feedback for the final projects.

Last class discussion and summary of what we have learnt together. Group feedback for the final projects.