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.