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 and grouping)
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 mathematical and statistical concepts (descriptive and inferential)

During the course the following topics will be explored:

- Statistical Information for Businesses
Quality of statistical information
Economic indicators
Household and consumer behavior surveys
- Sample Surveys
Phases of a sample survey
Sampling
Error profile
Data collection techniques
Acquisition and classification of statistical data
- The Data Matrix and Preliminary Analyses
The data matrix
Data quality and partial non-responses
Analyses of column profiles
Analyses of row profiles
- The Multivariate Linear Regression Model
Multiple linear regression model
Regression with limited dependent variables
- Multidimensional Analysis Techniques and Market Segmentation
Cluster analysis (hierarchical and non-hierarchical methods)
Factor analysis

Agresti, Statistical Methods for the Social Sciences (english version), any edition

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

The final exam, composed of a written test split into two sections, is designed to verify that the student has grasped the fundamental concepts covered in the lectures and can apply this knowledge to solve practical problems.

The first section consists of a quiz with 5 multiple-choice questions. For every correct answer given, you will receive 2 points, while for every incorrect answer given, you will lose 1 point, and for every unanswered question, you will receive 0 points. The first section's total score is made up of the scores from all 5 questions and is responsible for 25% of the final grade.

In the second section, there is a quiz with three open-ended questions that can be both theoretical and practical exercises that utilize the statistical tools discussed during the course. The grade for open-ended questions will range from 0 to 10 points. The second section's total score is based on the sum of points from all 3 questions and will make up 75% of the final grade.

To pass the exam with a minimum score of 18 out of 30, one must correctly answer at least 3 multiple-choice questions and adequately answer all three open-ended questions.

written

Evaluation grid:
A. Scores from 18 to 21 points are awarded if the student demonstrates acquisition of basic knowledge of univariate and bivariate statistics covered in the course.
B. Scores from 22 to 26 points are awarded if the student demonstrates elementary knowledge of multivariate analysis tools covered in the course.
C. Scores from 27 to 30 points are awarded if the student demonstrates knowledge and ability to use multivariate analysis tools covered in the course.
D. "Cum laude" (with honors/distinction) will be awarded if the student demonstrates an advanced understanding and ability to apply the statistical tools covered in the course.

In-class lectures.
During the lesson period, the student is encouraged to complete some exercises and self-assessment tests available on the e-learning platform.
This activity is not mandatory to access the exam.

Accessibility, Disability and Inclusion
Accommodation and support services for students with disabilities and students with specific learning impairments
Ca’ Foscari abides by Italian Law (Law 17/1999; Law 170/2010) regarding support
services and accommodation available to students with disabilities. This includes students with
mobility, visual, hearing and other disabilities (Law 17/1999), and specific learning impairments (Law 170/2010). If you have a disability or impairment that requires accommodations (i.e., alternate testing, readers, note takers or interpreters) please contact the Disability and Accessibility Offices in Student Services: disabilita@unive.it.