The purpose of this paper is to investigate the experience of visitors to UK markets by analysing their Tripadvisor reviews to identify perceived experiential dimensions with a view to informing actions by those responsible for market management to provide a better consumer experience.
This research analysed 41,071 Tripadvisor reviews of 61 UK markets. A latent Dirichlet allocation machine learning algorithm was conducted to identify the experience dimensions of visitors. A text analysis was performed to indicate salience and valence of commonly used words.
Five dimensions of experience are identified: atmosphere, merchandise, local variety, food and disappointment, together with the underlying factors that drive positive experience.
Place and market managers should assess and position their market informed by diverse experiential dimensions. They should also improve and enhance the experience of visitors according to the underlying factors of each dimension.
Retail markets have historically played an important role in the development of urban places. However, the ability to continue performing this role requires a greater understanding of how markets are perceived by those who use them. One way to achieve this is to use emergent technologies to inform decision-making by those responsible for their management. It demonstrates the potential of a new analytical technique using digital technologies to improve one of the oldest forms of retailing.
