THE IMPACT OF GENERATİVE AI–ENABLED REAL-TİME CONVERSATİONAL MARKETİNG ON DİGİTAL HEALTH EDUCATİON PROCESSES: AN EDUTAİNMENT FRAMEWORK USİNG NO-CODE PLATFORMS
Abstract Advances in digital technologies have fundamentally reshaped health communication and education, giving rise to innovative, interactive, and user-centered learning approaches. In this evolving environment, the edutainment paradigm, which integrates educational content with engaging and entertaining elements, has gained increasing importance as a strategic tool to increase attention, engagement, and sustainable behavioral change in digital health education. In the post-pandemic context, the increased emphasis on health literacy has further intensified the need for timely, reliable, and accessible health information, positioning digital platforms as critical agents for the dissemination of health information. In this process, generative artificial intelligence (AI) technologies, particularly those integrated into real-time conversational interfaces such as chatbots, have become personalized and adaptive. This study has presented new possibilities for delivering responsive health education content. This review article examines the role of generative AI-powered conversational marketing in digital health education processes through an edutainment education and entertainment framework, with a particular focus on the use of no-code platforms. Synthesizing recent interdisciplinary literature encompassing digital health, educational technology, marketing communications, and human-AI interaction, this study conceptualizes how no-code environments facilitate the rapid development and deployment of AI-powered conversational applications without requiring advanced programming expertise. Leveraging example application scenarios integrating commonly used no-code tools (e.g., Glide, Landbot, Tidio) with large language models like ChatGPT, this review evaluates the functional capabilities of educational-entertainment-focused chatbot systems in terms of interaction design, response quality, content personalization, and real-time interaction. Rather than relying on primary user data collection, the analysis is supported by observational assessments and scenario-based testing documented in previous empirical and applied studies. The findings highlight the potential of educational-entertainment-focused, generative AI-powered conversational systems to improve digital health education outcomes, as well as to serve as innovative tools for conversational marketing in health-related contexts. This article contributes to the literature by presenting a structured conceptual synthesis, clarifying the intersection of educational entertainment, generative AI, and no-code development in digital health education. The study provides theoretical insights and practical implications for health educators, digital health designers, and policymakers seeking scalable, ethical, and user-centered solutions for health communication in increasingly data-driven environments.