Segmentation of Social Media Users for Destinations: A Clustering Approach

Abstract

This is a study into the segmentation of social media users interested in traveling into groups and aims to ascertain if differences exist in benefits among segments. It is based on a survey that examines the benefits they see social media as having before during and after a trip to a destination using their responses to generate a data-driven segmentation. Data from a total of 218 questionnaires were analyzed using factor and cluster analysis in sequence specifically applying a hierarchical cluster analysis using the Ward method and a K-means algorithm. The analysis led to the identification of four useful types of social media user: info-seeker communication-seeker interaction-seeker and hybrid segments each of which seeks different things from social media and use it in different ways (e.g. to seek information to see what other people have said about a destination or to post their own experiences). As such the implications of our findings offer useful insights for both scholars and destination marketers highlighting the significance of offering appropriate marketing strategies for each type of segment.