QUANTITATIVE METHODS FOR SEGMENTATION AND POSITIONING

The course focuses on providing standard statistical methods for business, techniques for evaluating the marketing and data collection environment and surveys on consumer behavior useful for understanding market problems, in accordance with the objectives indicated by the Degree course.

Specifically, lectures will focus on the statistical analysis of data in the marketing environment, highlighting the applicative potential of these tools in business problems such as customer segmentation and positioning.

1. Knowledge and understanding:
1.1 ability to collect and synthesize quantitative and qualitative data relating to marketing problems
1.2 basic knowledge of statistical models in the supervised and unsupervised environment

2. Knowledge and understanding:
2.1 ability to conduct the analysis of the customer base through basic statistical models
2.2 ability to understand basic statistical models in supervised (regression) and unsupervised (dimensionality reduction, grouping, network models)
2.3 ability to operate market segmentation

3. Judgment skills:
3.1 ability to evaluate and compare different techniques
3.2 ability to identify the best tool to be applied to the substantial business problem

Basic statistical concepts (descriptive and inferential)

During the course the following topics will be explored:

- Customer base analysis
- Market segmentation techniques
- Statistical models for supervised learning: linear and logistic regression
- Statistical models for unsupervised learning: dimensionality reduction, clustering and methods for network analysis
- Applications and case studies: business intelligence

Handouts, slides, data and other material provided by the teacher during the lessons.

Additional textbooks:

Agresti, Statistical Methods for the Social Sciences (english version), any edition
Chapters on Linear Regression, Multiple Linear, Logistic Regression.
Previous chapters for references to descriptive and inferential statistics

Written exam

Frontal lectures

Italian

written