The intersection of artificial intelligence (AI) and experiential marketing marks a transformative era in consumer engagement, characterized by highly personalized and emotionally resonant experiences. This thesis explores the pivotal role of AI in shaping modern experiential marketing strategies, focusing on its ability to customize interactions, enhance engagement, and optimize performance measurement. The study begins with an introduction to artificial intelligence (AI), experiential marketing, and its transition into a technology-driven paradigm. It then explores AI’s applications across three key areas: personalization, engagement, and performance measurement. The first section investigates how AI leverages consumer data and behavioral insights to craft tailored, hyper-personalized experiences, fostering a sense of individuality and deeper brand connection. The second section highlights AI’s role in enhancing engagement through interactive technologies such as chatbots, gamification, virtual reality (VR), and augmented reality (AR), which elevate consumer interaction and brand immersion. The third section examines AI-powered tools for measuring and optimizing experiential marketing campaigns, including sentiment analysis, emotional impact measurement, real-time feedback loops, personalized KPIs and ROI assessments to maximize strategic effectiveness. Finally, the thesis presents two case studies from North America, showcasing brands that have successfully integrated AI into their experiential marketing initiatives. These real-world examples offer practical insights into AI-driven innovation and its impact on consumer experiences. By addressing these dimensions, this research underscores AI’s transformative potential in redefining experiential marketing, demonstrating how AI-driven activations can create emotionally engaging, consumer-centric experiences that set new standards in the evolving landscape of brand-consumer interaction.

The intersection of artificial intelligence (AI) and experiential marketing marks a transformative era in consumer engagement, characterized by highly personalized and emotionally resonant experiences. This thesis explores the pivotal role of AI in shaping modern experiential marketing strategies, focusing on its ability to customize interactions, enhance engagement, and optimize performance measurement. The study begins with an introduction to artificial intelligence (AI), experiential marketing, and its transition into a technology-driven paradigm. It then explores AI’s applications across three key areas: personalization, engagement, and performance measurement. The first section investigates how AI leverages consumer data and behavioral insights to craft tailored, hyper-personalized experiences, fostering a sense of individuality and deeper brand connection. The second section highlights AI’s role in enhancing engagement through interactive technologies such as chatbots, gamification, virtual reality (VR), and augmented reality (AR), which elevate consumer interaction and brand immersion. The third section examines AI-powered tools for measuring and optimizing experiential marketing campaigns, including sentiment analysis, emotional impact measurement, real-time feedback loops, personalized KPIs and ROI assessments to maximize strategic effectiveness. Finally, the thesis presents two case studies from North America, showcasing brands that have successfully integrated AI into their experiential marketing initiatives. These real-world examples offer practical insights into AI-driven innovation and its impact on consumer experiences. By addressing these dimensions, this research underscores AI’s transformative potential in redefining experiential marketing, demonstrating how AI-driven activations can create emotionally engaging, consumer-centric experiences that set new standards in the evolving landscape of brand-consumer interaction.

Artificial Intelligence and Experiential Marketing: Tailored Emotions for the New Age of Consumption

STRAZZULLA, DILETTA
2024/2025

Abstract

The intersection of artificial intelligence (AI) and experiential marketing marks a transformative era in consumer engagement, characterized by highly personalized and emotionally resonant experiences. This thesis explores the pivotal role of AI in shaping modern experiential marketing strategies, focusing on its ability to customize interactions, enhance engagement, and optimize performance measurement. The study begins with an introduction to artificial intelligence (AI), experiential marketing, and its transition into a technology-driven paradigm. It then explores AI’s applications across three key areas: personalization, engagement, and performance measurement. The first section investigates how AI leverages consumer data and behavioral insights to craft tailored, hyper-personalized experiences, fostering a sense of individuality and deeper brand connection. The second section highlights AI’s role in enhancing engagement through interactive technologies such as chatbots, gamification, virtual reality (VR), and augmented reality (AR), which elevate consumer interaction and brand immersion. The third section examines AI-powered tools for measuring and optimizing experiential marketing campaigns, including sentiment analysis, emotional impact measurement, real-time feedback loops, personalized KPIs and ROI assessments to maximize strategic effectiveness. Finally, the thesis presents two case studies from North America, showcasing brands that have successfully integrated AI into their experiential marketing initiatives. These real-world examples offer practical insights into AI-driven innovation and its impact on consumer experiences. By addressing these dimensions, this research underscores AI’s transformative potential in redefining experiential marketing, demonstrating how AI-driven activations can create emotionally engaging, consumer-centric experiences that set new standards in the evolving landscape of brand-consumer interaction.
2024
Artificial Intelligence and Experiential Marketing: Tailored Emotions for the New Age of Consumption
The intersection of artificial intelligence (AI) and experiential marketing marks a transformative era in consumer engagement, characterized by highly personalized and emotionally resonant experiences. This thesis explores the pivotal role of AI in shaping modern experiential marketing strategies, focusing on its ability to customize interactions, enhance engagement, and optimize performance measurement. The study begins with an introduction to artificial intelligence (AI), experiential marketing, and its transition into a technology-driven paradigm. It then explores AI’s applications across three key areas: personalization, engagement, and performance measurement. The first section investigates how AI leverages consumer data and behavioral insights to craft tailored, hyper-personalized experiences, fostering a sense of individuality and deeper brand connection. The second section highlights AI’s role in enhancing engagement through interactive technologies such as chatbots, gamification, virtual reality (VR), and augmented reality (AR), which elevate consumer interaction and brand immersion. The third section examines AI-powered tools for measuring and optimizing experiential marketing campaigns, including sentiment analysis, emotional impact measurement, real-time feedback loops, personalized KPIs and ROI assessments to maximize strategic effectiveness. Finally, the thesis presents two case studies from North America, showcasing brands that have successfully integrated AI into their experiential marketing initiatives. These real-world examples offer practical insights into AI-driven innovation and its impact on consumer experiences. By addressing these dimensions, this research underscores AI’s transformative potential in redefining experiential marketing, demonstrating how AI-driven activations can create emotionally engaging, consumer-centric experiences that set new standards in the evolving landscape of brand-consumer interaction.
Experience
Marketing
Artificial Intellige
Personalization
Engagement
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/83622