The course aims to illustrate the statistical techniques for the processing
of information of business interest, considering several variables at the
same time, and in particular those of a quantitative type. These
techniques include: linear regression model, logistic regression,
hierarchical and non-hierarchical cluster analysis, principal component
analysis, data can be from internal sources, such as those relating to sales of goods or services produced, or they can be obtained through
sample surveys (market research) or obtained from the Web. The goal of
multidimensional data analysis is to provide rational cognitive support for
decisions regarding the marketing strategies to be pursued.
The skills taught in the course include both methodological aspects,
essential for understanding the techniques and interpreting the results,
and the use of the learning by doing approach. Participation in classroom
activities and carrying out exercises, through the use of the statistical
environment R, will increase the student's ability to independently
process relevant data for the solution of marketing and digital marketing
problems. At the end of the course, students will have to become familiar
with the statistical methods indicated above, to perform descriptive and
predictive analyzes, identify customer segments to contact, analyze
customer behavioral data to identify and prevent customers churn with
ad hoc marketing strategies.