AI in Tourism: Profiling Indonesian Domestic Tourists for Targeted Marketing Communication - Puspita, Virienia; Patria, Raden Laskarko; Fitrianah, Devi; Luthfia, Amia (Journal of Indonesian Tourism and Development Studies, 2025)
The clustering algorithm used in this study, based on demographic, psychographic, travel preferences, travel behavior, and technology usage patterns, aims to identify Indonesian tourism consumers and classify them into clusters based on their characteristic groups. This study provides a comprehensive analysis of how artificial intelligence (AI) can contribute to enhancing tourism segmentation, offering insights for the hospitality and tourism industries in designing communication strategies tailored to the preferences of tourism consumers in Indonesia. Using survey data from 1,030 Indonesian domestic tourists, clustering techniques were applied to identify their tourism segments. The results are mapped into five clusters of the Indonesian domestic tourist. These profiles reveal clear differences between clusters in planning styles, spending patterns, and digital engagement. By translating these profiles into a conceptual model for tourism communication and empowerment, the study provides actionable strategies for tourism marketers to design more personalized campaigns, strengthen engagement, and align with sustainable tourism goals. This research contributes to the study of segmentation by integrating technology adoption and sustainability values into the profiles of travellers, while providing a systematic marketing communication framework for tourism destinations and organizations to tailor messages and services for diverse groups of tourism consumers.