Quantitative Marketing Research and Statistical Data Analysis

Quantitative Marketing Research

Objectives

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. Specifically, this course will enable students to:

1. manage sampling methods for quantitative marketing;
2. familiarize with key quantitative marketing research methods and associate them with marketing problems they are suited to answer;
3. become knowledgeable about the most important quantitative marketing research tools (survey and experiment);
4. understand neuromarketing’s core concepts and tools;
5. analyse quantitative data;
6. prepare and understand a research report suitable to support strategic marketing decisions.

Contents

Class content follows the key steps of the research process: research design, sampling, data collection, data analysis, and presentation of the findings.

The Course is organized interactively, and alternates face-to-face lectures with in-class exercise, and group assignments with software-assisted training (SPSS, Qualtrics). It also offers guest lectures and self-assessment moments (i.e. in class exercises).

Assessment

40% group assignment

60% final written exam

References

K. MALHOTRA NARESH, Marketing Research: An Applied Orientation, Pearson Education. (selected chapters).

Selected readings (a detailed reading list will be available on iCorsi).

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