This study explores the development of urban branding strategies in the digital age, focusing on the effectiveness of social media marketing content. Specifically, this research aims to systematically determine the optimal level of visual complexity in destination marketing images. Additionally, it investigates whether the type of destination moderates the relationship between these visual complexity elements and user engagement.
This study uses computer vision algorithms to analyze a comprehensive data set of destination marketing content from social media platforms. These algorithms enable the efficient and objective extraction of key visual features, contributing to data-driven insights for optimizing marketing strategies.
The results reveal that feature complexity and color variety are associated with an inverted U-shaped relationship with user engagement, while compositional complexity follows a U-shaped pattern. Destination type significantly moderates the effects of feature complexity and color variety on user engagement, and its effect on the relationship between compositional complexity and user engagement is not statistically significant. The heterogeneity tests confirm that the influence of visual complexity on user engagement differs notably between nature-based and urban tourism destinations.
To the best of the authors’ knowledge, this study is among the first to investigate the effectiveness of destination social media marketing from a visual perspective. By incorporating destination type as a moderating factor, this research provides novel insights into how different types of tourism destinations shape user engagement patterns.
