MARKETING ANALYTICS

The teaching belongs to the activities characterizing the Master's degree program in Marketing Management; the course aims at learning the main analytical and conceptual tools for Database Marketing and Machine Learning, trying to explain the usefulness and potential of these methodologies in the selection, design and management of business systems. The student will understand the need to transform the available data into information and learn some techniques to extract information and knowledge from the data. The course will be delivered in blended mode: 5 lessons out of 15 will be asynchronous lessons. For these lessons the teacher will provide videos, slides, exercises, self-assessment quizzes.

Knowledge and understanding skills.
In keeping with the general objectives of the degree program, the course aims to provide students with the following skills:
- learn the analytical and conceptual tools necessary to examine and solve specific decision-making problems in marketing context;
- learn and understand some techniques useful for designing a database in a marketing environment;
- learn and understand some techniques useful for transforming data into information.

Ability to apply knowledge and understanding.
Through the individual study, the study of the material made available by the teacher, the interaction with external experts, the conduct of exercises, the student will acquire the following skills to apply the knowledge learned:
- know how to use software to collect and analyze data and transform it into information;
- know how to use information extracted from data to make decisions.

Judgment skills, communication skills, learning skills.
Regarding the independence of judgment, communication skills and learning skills, always through the discussion of business cases and interaction with external experts, the student will learn how to:
- know how to choose between the different techniques of data analysis proposed the most appropriate to address the problem considered;
- know how to use the results achieved to feed the data collection and analysis process.

Some (few) basic knowledge in Mathematics are appreciated. For a reference course in mathematics (at the bachelor level) see http://www.unive.it/data/course/257915/programma

The main topics addressed during the course are the following:
- Database and systems for the management of Relational Database.
- Business Intelligence and Database Marketing.
- Marketing Analytics.
- Machine Learning and mathematical methods in Machine Learning.

The main reference texts are the following:

- "Business Intelligence: modelli matematici e sistemi per le decisioni", C. Vercellis, McGraw Hill, 2006.
- "Data Mining Techniques", Berry, Linoff, Wiley Computer Publishing, 1997.
- "Data Mining", P. Giudici, McGraw Hill, 2001.
- "Advanced Analytics e Artificial Intelligence per il Marketing", Suriano S., Di Domenica N., Fusi M., Capone L., Pearson, 2023

Other teaching material prepared by the theacher will be made available on the Moodle platform of the course.

The assessment is based on a written test and 5 multiple choice quizzes to be carried out during the course.

In the 5 ongoing quizzes, a maximum of 5 points can be obtained (1 points per quiz). Each quiz will consist of multiple choice questions.

Written exam: students will be offered three open theoretical questions or exercises on the contents of the lessons in the classroom. The maximum achievable score will be 25.

The exam is assessed on a 30-point basis. 18 points is the minimum level to receive 6 credits for the course.

written

Regarding the grading scale (criteria for assigning grades):
A. Scores in the 18-22 range will be assigned in the presence of:
- Sufficient knowledge and understanding of the course program;
- Limited ability to apply knowledge and formulate independent judgments;
- Sufficient ability to communicate using the appropriate technical language of the subject.
B. Scores in the 23-26 range will be assigned in the presence of:
- Fair knowledge and understanding of the course program;
- Fair ability to apply knowledge and formulate independent judgments;
- Fair ability to communicate using the appropriate technical language of the subject.
C. Scores in the 27-30 range will be assigned in the presence of:
- Good to excellent knowledge and understanding of the course program;
- Good to excellent ability to apply knowledge and formulate independent judgments;
- Good to excellent ability to communicate using the appropriate technical language of the subject.
D. Honors will be awarded in the presence of outstanding knowledge and applied understanding of the program, excellent judgment skills, and exceptional communication abilities.

The course consists of 15 lessons and will be delivered in blended mode: 5 lessons will be asynchronous. For these, the teacher will make available in advance videos, slides, exercises, self-assessment quizzes. The remaining lessons will be synchronous. The course is accompanied by an online platform offered on Moodle where the teacher will upload material and exercises to be carried out during the course.

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.