Pinto, Diego CostaNeves, Andreia Isabel Carvalho2025-07-082025-06-26http://hdl.handle.net/10362/184927Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing IntelligenceThe widespread adoption of Artificial Intelligence (AI) has transformed the social media environment dramatically. Advertising a cornerstone of this ecosystem, has been notably influenced by AI's capacity to personalise content, target people with pinpoint accuracy, and optimise user engagement. The aim of this study is to investigate the impact of personalized recommendations, specifically the exploitation of the Fear of Missing Out (FOMO) cognitive bias, on consumer purchasing behavior. I intend to study how Amazon utilizes AI-powered algorithms to trigger FOMO and drive impulsive buying. This research will contribute to a deeper understanding of digital addiction and the role of cognitive biases in consumer behavior. For these analyses, a study (1 PLS-SEM) was conducted with 230 participants, demonstrating how different consumer segments perceive and respond to personalized ads, leading individuals to ocasional impulse purchases driven by the fear of missing out, consequently causing regret. The present research provides an empirical contribution by increasing our knowledge of how cognitive biases like FOMO interact with AI-driven personalized advertising to influence consumer decision-making. Practically, the findings provide useful insights for marketers and digital platform designers by emphasising the ethical consequences of exploiting such biases, especially when they lead to impulsive purchases and consumer regret. These insights may guide the development of more responsible recommendation systems and advertising strategies.engPersonalized RecommendationsArtificial IntelligenceFOMOImpulsive BuyingConsumer BehaviorSDG 9 - Industry, innovation and infrastructureSDG 10 - Reduced inequalitiesSDG 12 - Responsible production and consumptionmaster thesis203968654