AI-driven personalization in advergames: enhancing consumer engagement and brand recall

Abstract

Artificial Intelligence (AI) has the potential to transform advergames by enabling more adaptive, personalized, and data-driven interactions between brands and consumers. While previous research has established the effectiveness of advergames in generating consumer engagement and brand-related responses, less attention has been given to the distinction between user-directed personalization and algorithmic, AI-driven personalization in branded gaming environments. This study examines the intersection of personalization, interactivity, brand integration, and AI in contemporary advergames, with particular attention to consumer engagement, brand recall, and ethical considerations. The study employs a qualitative comparative case study approach. Four prominent branded gaming campaigns NIKELAND, Coca-Cola Zero Sugar Byte, Gucci Garden, and Wendy's Food Fight/Keeping Fortnite Fresh were examined using publicly available secondary sources, including company and platform materials, campaign reports, news and industry articles, performance statistics, and relevant academic literature. The cases were comparatively analyzed across four dimensions: game design and interactivity, brand integration and advertising strategy, consumer engagement and publicly reported performance, and ethical considerations related to personalization and data use. The analysis indicates that successful advergames create engagement primarily through the integration of branded content with interactive gameplay, participation, social interaction, and immersive experiences. The cases demonstrate different forms of user-directed customization, social participation, exclusivity, digital collectibles, and brand integration. These features can strengthen consumer involvement and brand associations, but the publicly available evidence does not establish that all four campaigns employed AI-driven personalization or algorithmic adaptation. The findings therefore distinguish between personalization as a design feature and AI-driven personalization based on real-time behavioral data and algorithmic adaptation. The analysis also highlights privacy, transparency, and consumer autonomy as important considerations when personalization relies on the collection and analysis of player data. The study contributes to the literature by conceptualizing AI-driven personalization in advergames as an intersection of personalization, interactivity, immersion, and algorithmic adaptation rather than treating all forms of customization as AI. The findings suggest that brands can strengthen advergame effectiveness by aligning gameplay mechanics with brand identity and providing meaningful opportunities for participation, while the responsible use of AI requires greater transparency regarding data collection, personalization mechanisms, and user control. The study also identifies the need for future empirical research examining proprietary AI systems, behavioral data practices, and the effects of algorithmic personalization on engagement, brand recall, trust, and consumer autonomy.