How to Avoid Random Market Segmentation Solutions

Abstract

Tourism researchers and the tourism industry rely heavily on data-driven market segmentation analysis for both knowledge development and market insight. Most algorithms used in data-driven market segmentation are exploratory; they do not generate one single stable result. Only when data are well-structured (when very clear, distinct market segments exist in the data) are repeated calculations likely to generate the same segmentation solution. When data lack structure, which is frequently the case in empirical consumer data sets, repeated calculations lead to different solutions. Running a market segmentation analysis once only can therefore lead to an entirely random solution that does not represent a strong foundation for developing a long-term market segmentation strategy. The present study (1) explains the problem, (2) assesses how high the risk is of random solutions occurring in tourism market segmentation studies, and (3) recommends an approach that can be used to avoid random solutions.