MODERN METHODS OF MARKET SEGMENTATION IN TOURISM MARKETING AND DIRECTIONS FOR THEIR IMPROVEMENT

Abstract

Market segmentation is a fundamental component of tourism marketing, enabling tourism businesses and destinations to identify consumer groups with similar needs, preferences, motivations, and purchasing behaviours. The rapid advancement of digital technologies, evolving tourist expectations, and increasing competition within the tourism industry have highlighted the need for more flexible, adaptive, and data-driven segmentation approaches. This article examines contemporary methods of market segmentation in tourism marketing, including demographic, geographic, psychographic, behavioural, benefit-based, and data-driven approaches. Particular attention is devoted to cluster analysis, machine learning, digital behavioural data, and hybrid segmentation models. The study employs a conceptual and comparative analytical approach to evaluate the strengths and limitations of existing segmentation methods. The analysis suggests that traditional segmentation approaches remain valuable but may be less effective when applied independently in dynamic and heterogeneous tourism markets. Accordingly, the article identifies potential directions for improving tourism market segmentation through the integration of multiple data sources, dynamic consumer profiling, behavioural analysis, personalisation, and continuous assessment of segment profitability. These approaches can support the development of more targeted marketing strategies, enhance customer satisfaction, and strengthen destination competitiveness.