Module Details

Artificial intelligence and marketing: artificial intelligence and marketing: module 2

MF0636

Course
Artificial intelligence and marketing: artificial intelligence and marketing: module 2
Code
MF0636
Academic Year
2024/2025
Curriculum Year
2023/2024
Degree Programme
ARTIFICIAL INTELLIGENCE AND DIGITAL INNOVATION
Curriculum
A015 - Economico-Aziendale
Course coordinator
-
Lecturers
Credits
5
Lecture Hours
40
Scientific Disciplinary Sector (SSD)
SECS-P/08 - Corporate Finance
Course Type
Single-subject learning activity
Course Delivery
OBB - Obbligatoria
Year
2
Teaching period
Secondo Semestre
Campus
VERCELLI
Teaching language
Italian
Course Contents
The course focuses on the study of marketing and the applications of Artificial Intelligence in marketing. In particular, it analyzes the fundamentals of marketing in light of the evolution the discipline has undergone in recent years, both in terms of approach and in terms of tools and channels. Additionally, it explores topics related to Artificial Intelligence through models and examples, addressing them not only from a theoretical perspective but also from a practical standpoint.
Reference Texts
"Advanced Analytics e Artificial Intelligence per il marketing", edizione Pearson di Sergio Suriano, Nico Di Domenica, Marco Fusi, Luigi Capone
Learning Outcomes
1.Knowledge and Understanding:
Understand marketing, its evolution, and marketing processes.
2. Ability to Apply Knowledge and Understanding:
-Apply marketing models to study the logic and design of campaigns and implement AI in marketing.
3. Autonomy of Judgment:
- Comprehend the impact and role of AI in marketing.
4. Learning Skills:
-Understand the application of AI in marketing and grasp its future applications.
Prerequisites
There are no prerequisites. Attendance is not mandatory but is highly recommended. Students who have not had Marketing during their bachelor's degree are advised to inform the instructor.
Teaching Methods
The main teaching method takes place through lectures supported by slides. Active participation is encouraged through spontaneous discussions with students on the topics covered, as well as through sessions dedicated to student presentations and case analyses. Subject to the course schedule, there may be guest lectures from industry professionals responsible for activities related to the course content. Dates and times for these guest lectures will be communicated during the course.
Additional Information
Slides will be available on DIR.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/servicesstudents-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.
Assessment Methods
20% Participation
20% Project – Development of a marketing campaign applying AI. Submission at the end of lectures before the first exam session.
25% Written Exam
25% Oral Exam
The written exam consists of three parts: the first with multiple-choice questions; the second with open-ended content questions; the third with open-ended reasoning questions. The duration of the exam is one hour.

The oral exam takes place on the same day.

Students that CANNOT ATTEND class should contact the professor for the complete info over extra readings and tasks necessary for the final assessment.
Detailed Syllabus
Part I: Understanding Marketing Processes
What is marketing; understanding its evolution
Designing strategy, the role of marketing, the marketing mix

Part II: Analyzing Consumers and Markets
Micro and macro environment
Marketing research

Part III: Designing and Managing Marketing
Market segmentation, targeting, positioning, and differentiation
Retail and trade marketing
Digital marketing

Part IV: Artificial Intelligence
Enhancing marketing activities through a data-driven approach
Main approaches to measuring marketing activities
Attribution models in digital marketing
Expected Learning Outcomes
Be capable of applying concepts related to core marketing activities to campaigns while integrating them with AI models.
Last update:09-09-2026 00:14:31