Quantitative Marketing Research and Statistical Data Analysis
- familiarize with key quantitative marketing research methods and associate them with marketing problems they are suited to answer;
- manage sampling methods for quantitative marketing;
- become knowledgeable about the most important quantitative marketing research tools (survey and experiment);
- prepare and understand a research brief, a research proposal and a research report suitable to support strategic marketing decisions.
Marketing professionals rely on information gathered through marketing research to determine the course of action of a marketing plan. Leveraging upon research to know more about customers, consumers, and citizens is crucial for effective marketing decisions.
In this Course, students will learn how to be smart producers and consumers of information, when it comes to marketing research. They will also learn to be more effective marketing decision makers.
The Course is organized interactively, with lectures and exercises, and a group project. It also offers self-assessment moments.
Evaluation procedures and Grading criteria
- 40% project
- 10% participation
- 50% exam: you must obtain minimum 5 in the individual exam in order that the grade of the project is counted
- K. MALHOTRA NARESH, Marketing Research: An Applied Orientation, Pearson Education Required Chapters:
- CH 4: Exploratory Research Design
- CH 6: Descriptive Research Design
- CH 7: Causal Research: Experimentation
- CH 8: Measurement and Scaling: Fundamentals and Comparative Scaling
- CH 9: Measurement and Scaling: Noncomparative Scaling techniques
- CH 10: Questionnaire and Form Design
- CH 11: Sampling: Design and Procedures
- CH 12: Sampling: Final and Initial Sample Size Determination
- BERGER, J. ET AL. (2020), “Uniting the Tribes: Using Text for Marketing Insight”, Journal of Marketing, 84(1), pp. 1-25.
Statistical Data Analysis
This course addresses market research design, data collection, and data interpretation based-upon quantitative data and techniques.
Methods that are specifically developed along the course include questionnaire design and survey, experiments, and panel data. Data analysis familiarizes participants with statistical data analysis - the art of examining, summarising and drawing conclusions from data. This includes the organisation of a coherent database and its use to produce statistical summaries and inference. Statistical software is essential in this respect. The course builds on students´ knowledge of introductory level statistics, such as frequency, distribution and correlation and introduces new topics like hypothesis testing on means, percentage and regression, multiple regression, logistic regression, factor analysis and cluster analysis