New approaches to psychographic consumer segmentation Exploring fine art collectors using artificial intelligence, automated text analysis and correspondence analysis

Purpose While the motivation for collecting art has received considerable attention in the literature, less is known about the characteristics of the typical art collector. This paper aims to explore these characteristics to develop a typology of art consumers using a mixed method approach over several studies. Design/methodology/approach This is achieved by analyzing qualitative data, gathered via semi-structured interviews of art collectors, and quantitatively by means of natural language processing analysis and automated text analysis and using correspondence analysis to analyze and present the results. Findings The study's findings reveal four distinct clusters of art collectors based on their Big Five personality traits, as well as uncovering insights into how these types talk about their possessions. Originality/value This paper demonstrates a unique mixed methods approach to analyzing unstructured qualitative data. It shows how text data can be used to identify measurable market segments for which targeted strategies can be developed.