Quantifying customer engagement : a biometric and visual analysis of responses to generated digital adverts

Abstract

The rapid evolution of artificial intelligence (AI) has revolutionised digital advertising, driving the adoption of AI-generated content to capture customer attention and enhance engagement. This study explores the effectiveness of AI-generated, traditional, and mixed advertisements in fostering customer engagement, with a focus on cognitive and emotional responses. While previous research highlights the growing use of generative AI in advertising, limited evidence exists regarding its impact compared to traditional or hybrid approaches. Grounded in the Stimulus-Organism-Response (SOR) framework, the study employs biometric tools such as Galvanic Skin Response, eye-tracking, Heart Rate Monitoring and Self Report, along with a questionnaire Dial to measure customer engagement. A controlled blind experimental design was conducted with 52 participants exposed to three advertisement types: AI-generated, traditional, and mixed. Regression modelling analysed hypothesised relationships, incorporating insights from a self-administered questionnaire. Findings reveal that AI-generated advertisements excel in attention capture and physiological arousal but lack the perceived authenticity and emotional resonance achieved by traditional advertisements. Mixed advertisements demonstrate moderate but inconsistent effectiveness, highlighting the importance of thoughtful integration between AI and human creativity. Perceived authenticity and emotional resonance emerged as critical predictors of customer engagement, emphasising the need for balanced design strategies. The study underscores the potential for biometric and subjective measures to optimise advertising strategies, offering actionable insights for marketers aiming to leverage AI tools while preserving the human touch. Recommendations for future research include the exploration of dynamic content, such as video-based advertisements, and the use of neuroscientific tools like EEG and fMRI for deeper insights into consumer decision-making.