MARKETING FOR THE ARTS

This course is positioned as a specialized advanced module within the Master’s Degree program in Management / Economics and Management of Arts and Cultural Activities. It bridges foundational concepts of general management with the unique economic, social, and aesthetic dynamics of the cultural sector. Designed to train future arts managers, cultural marketers, and institutional leaders, the course provides the strategic, analytical, and operational frameworks required to navigate the ecosystem of visual and performing arts, balancing curatorial integrity, public relevance, and long-term financial sustainability.

Upon successful completion of this course, students will achieve the following learning outcomes:

Knowledge and Understanding: Grasp the core theories and strategic frameworks of cultural marketing (including Colbert's product-oriented model) across visual arts, performing arts, heritage, and creative industries.

Applying Knowledge and Understanding: Design and execute data-driven audience development strategies, pricing policies, integrated communications, and digital/AI transformation plans for real-world arts organizations.

Making Judgements: Critically evaluate strategic trade-offs between artistic vision, audience accessibility, ethical sponsorship, and revenue diversification in complex cultural environments.

Communication Skills: Effectively articulate, present, and defend strategic marketing plans and audience engagement projects to professional stakeholders using clear domain-specific terminology in English.

Learning Skills: Conduct independent market research, analyze audience data, and critically assess emerging technological trends shaping the global arts landscape.

Basic knowledge of marketing principles and knowledge of the English language (level B2).

• Introduction to Cultural Marketing
• The Visual Arts Ecosystem, Governance & The Cultural Product
• Environmental & Market Dynamics
• Consumer Behavior in the Visual Arts
• Audience Segmentation, Targeting, and Positioning (STP)
• Marketing Information Systems (MIS) & Audience Research
• The Price Variable & Perceived Economic Value
• Place & Distribution Strategies
• Digital Distribution & Virtual Museum Experience
• Integrated Marketing Communications (IMC)
• Branding, Public Relations, and Media Management
• Revenue Diversification & Corporate Sponsorship
• Strategic Marketing Planning, Implementation & Control
• New Technologies, Generative AI & Digital Transformation in Museum Marketing
• Applications of museum marketing plans

Primary textbook: Colbert, F., & Ravanas, P. (2021). Marketing Culture and the Arts (5th Edition). HEC Montréal.

Altri libri di testo raccomandati:
Jeffrey T. (2023), The Art Business: Art World, Art Market (2nd Edition), Routledge.
Kerrigan, F., & Preece, C. (2023), Marketing the Arts: Breaking Boundaries (2ª ed.), Routledge.
Kotler N.G., Kotler P., Kotler W.I. (2008), Museum Marketing & Strategy (2nd Edition), Jossey Bass Ed.
Lister, C. (2023) – Marketing Strategy for Museums: A Practical Guide, Routledge.
Walter C. (2015), Arts Management: An Entrepreneurial Approach Routledge.

Other recommended readings - scientific articles:
• Avlonitou, C., Papadaki, E., & Apostolakis, A. (2025). A human–AI compass for sustainable art museums: navigating opportunities and challenges in operations, collections management, and visitor engagement. Heritage, 8(10), 422.
• D’Souza, R. E. (2025). AI and institutional transformation: care, access and learning at Tate Britain. Journal of Visual Art Practice, 24(4), 393-425.
• Derda, I., & Predescu, D. (2025). Towards human-centric AI in museums: practitioners’ perspectives and technology acceptance of visitor-centered AI for value (co-) creation. Museum Management and Curatorship, 40(4), 532-554.
• Iervolino, S., & Milne, A. (2026). Curating AI-driven Art: actors, institutional strategies and organisational change. Museum Management and Curatorship, 41(1), 162-181.
• Lai, S., Tian, Y., & Zhang, Q. (2025). The impact of AI-generated technologies-driven digital cultural heritage platforms on users’ offline cultural participation intentions. npj Herit Sci 13 (1): 574.
• Rhee, B. A., Pianzola, F., & Seo, Y. E. (2025). An empirical study of visitors' engagement with a museum robot guide and a mobile audio guide: a case study in South Korea. Museum Management and Curatorship, 1-21.
• Sharma, R., & Singhal, E. (2026). Generative AI and Creative Industries: A Systematic Review on Emerging Trends and Future Research Directions. FIIB Business Review,.
• Xia, T., Wu, Y., Qiu, A., Liu, Z., & Fan, M. (2025). The impact of ai guide language strategies on museum visitor experience: The mediating role of psychological distance in the arousal–topic fit effect. Behavioral Sciences, 15(11), 1569.

Multiple choice written text to access the final oral exam.
A marketing plan group project work is optional and recommended.

written and oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

The final grade is expressed on a 30-point scale (from 18/30 to 30/30 cum laude) and is calculated by weighting class participation (10%), the individual case study analysis (30%), and the group project with final presentation (60%). The breakdown of grade ranges is structured as follows:

18 – 22 (Sufficient / Satisfactory): Elementary knowledge of basic cultural marketing concepts; basic application of analytical frameworks; limited class participation; essential yet structurally sufficient group project.

23 – 26 (Good / Very Satisfactory): Good understanding of the theoretical concepts of the Colbert model; adequate capacity to analyze case studies; active contribution to class discussions; good overall quality of the group project.

27 – 29 (Very Good / Excellent): Broad mastery of the subject matter and specialized domain terminology in English; capacity for critical reflection; excellent application of analytical frameworks; well-structured and innovative final project.

30 – 30 cum laude (Outstanding): Extraordinary theoretical and methodological mastery; strong independent judgment; rigor in market research, brilliant integration of emerging technologies (AI), and a professional-grade group project presentation.

The course adopts a participatory and applied pedagogical methodology, delivered entirely in English (30 contact hours in total), structured through the following modalities:

Lectures and Interactive Sessions: Presentation of theoretical frameworks in cultural marketing and management, supported by real-world case examples and visual materials.

Guided Case Study Discussions (Case-based Learning): In-class critical analysis of actual management scenarios concerning international museums, galleries, theatres, and cultural festivals.

Collaborative Learning and Project Work: Group work aimed at developing an integrated strategic marketing and audience development plan, incorporating practical problem-solving and professional simulations.

Presentations and Pitching: Oral presentation and defense of the strategic project during the final session, featuring a Q&A segment and peer review.

1. General Principles
Ca’ Foscari University encourages innovation and the critical engagement with digital tools while upholding academic integrity, intellectual honesty, and transparency. Generative AI tools (e.g., ChatGPT, Claude, Midjourney) are recognized as valuable learning aids, but they cannot replace original critical thinking, curatorial judgment, or rigorous scholarly analysis.
Students remain fully and solely responsible for the accuracy, authenticity, and academic quality of all submitted work.
2. Permitted vs. Prohibited AI Usage
• Permitted Uses (AI as a Collaborative Assistant):
o Brainstorming & Ideation: Generating initial concepts for exhibition themes, audience engagement campaigns, or strategic marketing frameworks.
o Language & Editing: Polishing grammar, style, and tone in written drafts (especially helpful for non-native English speakers).
o Code & Analytics: Assisting in basic data structuring or visualizing mock audience segmentation data.
• Prohibited Uses (Academic Dishonesty):
o Unattributed Content Generation: Submitting whole or substantial sections of essays, reports, or slides generated directly by AI as your own work.
o Unverified Citations & Data: Including AI-generated references, quotes, or market metrics without independent verification (uncritical reliance on "hallucinated" data).
o Assessment Integrity Violations: Using AI tools during closed-book evaluations or in any unauthorized manner during group presentation development.
3. Mandatory AI Disclosure Statement
In accordance with university guidelines, transparency is mandatory. Every written submission (Individual Case Study) and group deliverable (Final Presentation) must include a dedicated "AI Usage Declaration" on the title page or appendix using the following format:
AI Usage Declaration Template:
"In preparing this assignment, [I / Our Group] used [Name of Tool, e.g., ChatGPT-4o / Midjourney] for [specific purpose, e.g., proofreading English text / generating preliminary mockup concepts]. The prompts used included [brief description]. All underlying research, strategic analysis, data verification, and final drafting were conducted independently by the author(s)."
(If no AI tools were used, state: "No Generative AI tools were utilized in the preparation of this assignment.")
4. Enforcement & Consequences
Submitting undisclosed AI-generated work, passing off synthetic text as original writing, or failing to report AI usage constitutes plagiarism and academic dishonesty under Ca' Foscari's disciplinary regulations. Cases of suspected non-compliance will be evaluated through faculty review and institutional anti-plagiarism protocols.

This subject deals with topics related to the macro-area "Human capital, health, education" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development