Clustering Consumer Navigation Paths to Identify Visitor Types in the Context of Travel Booking Website
(A2023-113982)

AUTHORS

Boshuo Guo, the University of Leeds; Catarina Sismeiro, Imperial College Business School

ABSTRACT

Navigation paths record a website visitor’s page-by-page movements. Categorising path information is useful for identifying visitor’s types. Past studies on categorising path information usually describe paths as a sequence of webpages viewed, which lacks detailed information about what exactly customers are doing on the page. We develop a new approach of categorising navigation paths, which describes a customer’s navigation path as a sequence of browsing actions. This approach cares not only about the type of page but also what the customer does at each page. We identify five different types of visitors in the context of online airline booking: Airport Searcher, Filterer, Active Searcher, (outbound/return) Date Searcher, Repeated Viewer. We identify Airport Searcher, Filterer and Active Searcher as visitors of high purchase rate. This approach is particularly useful for the businesses of online travel bookings where accurate recognition of visitor type is exceptionally important.