Using Personas to Model Museum Visitors

It is widely agreed that museums and other cultural heritage venues should provide visitors with personalised interaction and services such as personalised mobile guides, although currently most do not. Since museum visitors are typically first-time visitors and since their visit is for a relatively short session, personalisation should use initial interaction data to associate the user with a particular persona and thereby infer other facts about the user's preferences and needs. In this paper we report a questionnaire-based study carried out with 105 visitors of a Science and Technology Centre to examine the minimal features needed to identify visitor personas. We find that museum visitors can be clustered by their visit motivation and perceived success factors; these clusters are found to correspond both with Falk's visitor categorisation and a prior classification of exploration styles. Consequently, these two features can be used to reliably identify the visitor persona, and therefore, can be used for user modeling.