Segmentation of Social Media Users for Destinations: A Clustering Approach

Abstract

SciVal Topics

Metrics 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 Kmeans 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.