Learning Outcomes of this subject are:
1. Understand Key Market Research Concepts
Comprehend the fundamental principles of market research and the distinction between quantitative and qualitative research methods.
Identify the appropriate research tools based on the nature of data (quantitative or qualitative) and the business problem.
2. Analyse Quantitative Data Using Power BI
Collect and prepare quantitative data from various sources (surveys, sales data, etc.) for analysis.
Build interactive dashboards and visualizations in Power BI to analyse market trends, customer preferences, and key performance metrics.
Use data transformation and DAX functions in Power BI to clean, filter, and summarize data effectively.
Apply statistical methods (e.g., regression, correlation) to make data-driven business decisions.
Interpret and present quantitative insights clearly to stakeholders using Power BI reports.
3. Process and Analyse Qualitative Data Using Atlas.ti
Understand the nature and structure of qualitative data and the contexts in which it is used (e.g., focus groups, interviews, open-ended survey responses).
Collect and organize qualitative data in Atlas.ti, including coding, categorizing, and mapping out key themes.
Apply coding techniques to identify patterns and themes within qualitative data, using Atlas.ti tools for analysis and visualization.
Create network maps and content analyses to visualize relationships and connections in qualitative data.
Derive meaningful insights from qualitative data to support research findings and business strategies.
4. Integrate Quantitative and Qualitative Research Findings
Effectively combine quantitative and qualitative research findings to provide a more comprehensive understanding of market trends.
Utilize both Power BI and Atlas.ti to prepare integrated reports and presentations that align data-driven insights with broader market research objectives.
Evaluate the strengths and limitations of both research methods and tools to choose the most suitable approach for specific research problems.
5. Develop Practical Market Research Skills
Conduct a complete market research project, from data collection to analysis and reporting, using both quantitative and qualitative tools.
Present research findings using visualization and data storytelling techniques that make complex data easy to understand.
Develop the ability to use market research tools (Power BI, Atlas.ti) in professional scenarios for real-world decision-making and problem-solving.
This course on Marketing Research Tools is designed to equip students with the essential knowledge and practical skills needed to conduct effective market research using quantitative and qualitative methodologies. The course is structured into two main blocks, focusing on the theoretical foundations of marketing research and the application of specific analytical tools, including Power BI for quantitative data analysis and Atlas.ti for qualitative data analysis.
1. Basics of Marketing Research
Students will begin with an exploration of the fundamentals of marketing research, distinguishing between marketing research and market research. They will learn the significance of marketing research in the decision-making process and engage in discussions and activities to solidify their understanding of the topic.
2. Research Designs & Methods
The course will delve into various research designs?exploratory, descriptive, and causal?highlighting their applications in different research scenarios. Students will also learn about cross-sectional and longitudinal studies and the types of data collected in marketing research, including quantitative and qualitative data, along with the measurement scales used. Additionally, the course will cover essential data collection methods, providing a comprehensive view of how data is gathered and analysed.
Block 1 - Quantitative Data Analysis Using Power BI (8 Weeks, 32 Hours)
In this block, students will gain hands-on experience with Power BI, a powerful tool for quantitative data analysis. The curriculum will cover:
- Analysing Awareness: Understanding metrics such as brand lift and campaign traction to assess marketing effectiveness.
- Analysing Engagement: Evaluating lead generation and consumer engagement through reach and frequency metrics.
- Analysing Customer Satisfaction: Conducting conversion analysis and reputation evaluation to gauge customer satisfaction levels.
- Analysing Advocacy: Identifying brand advocates and analysing customer-generated content to measure brand loyalty. Through interactive sessions and practical projects, students will develop the ability to create compelling data visualizations and derive actionable insights from quantitative data.
Block 2 - Qualitative Data Analysis Using Atlas.ti (4 Weeks, 16 Hours)
This block will focus on qualitative data analysis using Atlas.ti. Students will learn about:
- Data Reduction: Techniques for managing documents, quoting, coding, and establishing links within qualitative data.
- Transformation and Display of Data: Utilizing networks and co-occurrence tools to visualize and analyse qualitative data relationships.
- Drawing Conclusions: Applying methods like the Object Crawler, generating code outputs, and using memos and networks to derive meaningful insights from qualitative research.
Students will engage in practical exercises that enhance their ability to interpret and present qualitative data effectively.
The course methodology will emphasize practical applications of Power BI for quantitative data analysis and Atlas.ti for qualitative data analysis. The goal is to provide students with hands-on experience in using these market research tools through live demonstrations, step-by-step tutorials, and project-based learning. Regular software assignments will help solidify their understanding of key features and functionality. In addition to the technical training, students will engage with real-world case studies of companies that have utilized market research tools, analysing how data-driven decisions shaped business outcomes. These case studies will be paired with group discussions to foster critical thinking, enabling students to debate the strengths and weaknesses of different research methods. Furthermore, interactive activities such as debates, quizzes, and group projects will encourage collaborative learning, ensuring students not only grasp theoretical knowledge but also develop the skills to apply market research tools effectively in a business environment.
The evaluation for this course will be based on continuous assessment, where students will be evaluated throughout the semester. The final global score will be distributed as follows:
1. Class Attendance, Participation, and Discussions: 15%
2. In-Class Activities and Peer Reviews: 15%
3. Assignment 1: 15%
4. Mid-Term Exam: 20%
5. Final Exam: 35%
To successfully pass the course, students must achieve a minimum score of 5 out of 10. Students who do not attain this score will be required to retake the course next year in 2026-27. This course does not have a re-exam.
One student scoring the highest score will be awarded extraordinary for the course.
Use of AI tools: If AI tools are used in any submission, a paragraph must be included in the submission description stating how the AI was used and what prompts or instructions were given to obtain the results. Failure to do so constitutes a violation of academic honesty policies.
ATTENDANCE POLICY: A minimal attendance of 75% is mandatory for the course. Students failing to attend 75% of the course will be barred from attending the final exam. Medical justification (if any) should be sent to the tutor along with a copy to the professor. The justification needs to be validated by the tutor in order to take it into consideration by the professor. Any other extraordinary situation related to the attendance should be communicated explicitly to the professor in copies to the tutor and degree coordinator in the first four weeks of the course. Any extraordinary request after the initial weeks will not be accepted.
Essentials of Marketing Research, 6th Ed - Joseph Hair, David Ortinau and Dana E. Harrison - McGraw Hill
Marketing Research: An Applied Orientation 7th Ed. - Naresh Malhotra - Pearson
Data Analysis with Microsoft Power BI, 1st Ed. - Brian Larson - McGraw Hill
Qualitative Data Analysis with ATLAS.ti, 3rd Ed. - Susanne Friese - Sage Publications