Comparison of tourists’ perceptions and destinations’ self-presentation through image recognition

With the rapid development of the internet, social media platforms enable tourists to extensively research, compare, and evaluate potential destinations. Concurrently, these platforms have provided new channels for destinations to present themselves and engage with potential visitors. Therefore, the closer destinations’ self-presentation is to the actual experience of the tourists, the higher the likelihood that tourists’ expectations are met. This study presents an approach for analyzing customer preferences and comparing them with the self-representation of tourism destinations or providers, based on images uploaded to Instagram. Compared to existing approaches, the proposed methodology enables a more fine-grained analysis of preference profiles for individual customer segments by applying clustering techniques to the multidimensional preference profile and executing a cluster-specific congruence analysis. The results demonstrate that the data reveal distinct segments within the tourist groups of the studied destinations and differences between the external perception and self-presentation for specific customer segments could be identified, constituting a valuable input to a refinement of marketing strategies for tourism destinations.