K-means Cluster Analysis of Unique Selling Proposition, Destination Brand Image, and Loyalty in the Tourist Perspective

The tourism industry is becoming increasingly competitive, and a destination must differentiate itself from competitors through a strong image and unique qualities that can attract tourists. However, the process of creating such an image is highly complex due to the overlap between brands, corporate services, tourism products, and the diversity of stakeholders involved. This research aims to delve into the analysis of tourist preferences towards destination attributes, such as unique selling proposition, destination brand image, and destination brand loyalty, utilizing the K-Means Cluster method. The total sample, derived from the data provided by the Central Statistics Agency of Batu City, consists of 271 respondents distributed across five tourist destinations: Alun-Alun Wisata Kota Batu, Jatim Park II, Jatim Park III, Jatim Park I, and Eco Green Park. The K-Means Cluster analysis results reveal patterns of variance in tourists' assessments of specific destinations. Particularly, these findings underscore the dominant role of the unique selling proposition, especially in destinations that emphasize environmental values and the uniqueness of attractions. This discovery simultaneously contributes significantly to understanding the factors influencing tourist preferences across various destinations. In the theoretical context, the findings of this research indicate that tourists' responses to specific attributes can vary significantly depending on the destination visited. For destination marketers, understanding tourist clusters can help destination managers design more targeted marketing strategies tailored to the preferences and behaviors of specific tourist groups.