Due to technological developments and the proliferation of high-quality data, marketing is becoming an increasingly quantitative profession. This means that marketing professionals should not only be creative, they also must have a solid background in marketing analytical tools in order to make sense of all the available data. In this course, you will learn how to analyze secondary data using multivariate techniques with the purpose of enhancing marketing decisions.
The focus in the course is be able to determine which marketing problem requires which particular analytical approach. The students will solve real-life marketing problems through the analysis of secondary data. They will have to come up with managerial recommendations based on their findings and they will learn how to communicate these findings effectively to a management audience with the use of Powerpoint presentations and by means of a written report. Hence, this course is not just a statistics course; the emphasis is on the managerial aspects of the statistical tools.
Given the rapidly changing technological environment, as indicated by the buzzwords "Big Data", marketing accountability, data science, etc., this course will summarize the most recent developments in marketing research in general and introduce the students to state-of-the-art analytical methods in particular.
Students should have working knowledge of SPSS or an equivalent software package (e.g. JMP/R) before the course starts.
- A refresher in univariate statistics
- Exploratory data analysis
- Analysis of Variance and related methods
- (Logistic) Regression analysis
- Factor analysis
- Conjoint analysis
- Presentation and write up of findings
This course outline may be subject to changes.
Learning outcome knowledge
The overall learning goal is to be able to see the benefits of analytical decisions in marketing, namely how it can lead to better decisions contributing to the firm's goals. Closely related to this ability is the ability to discern and choose between possible techniques as well as the ability to apply this technique appropriately, given a particular marketing problem. Finally, the aim is to convincingly communicate the findings to the firm's decision makers in an understandable, non-technical language.
To achieve the learning outcomes, the students must be able to:
1) Explain the differences and similarities between key techniques.
2) Understand each technique in terms of:
- Its data requirements
- The type of problems it can be used for
- The underlying statistics
- The assumptions/limitations
- Its relationship with other techniques
3) Interpret the outputs (results) and derive managerial implications
4) Oral and written communication of the results
- Written assignment: 20%
- Written assignment: 20%
- Written exam: 60%