Segmenting Event Attendees Based on Travel Distance, Frequency of Attendance, and Involvement Measures: A Cluster Segmentation Technique

Abstract

The purpose of this study was to conduct a postevent evaluation for the Great New England Air Show to apply a cluster segmentation technique using travel distance, purchase decision involvement, and frequency of attendance among its current visitors as measures to improve marketing applications and to further examine the economic significance of the event. A cluster analysis procedure identified four groups of attendees: 1) Locals, 2) Highly involved enthusiasts, 3) First timers/nonloyals, and 4) Fringe attendees. Significant differences were identified across the four cluster segments on individual involvement, number of times attended, distance from the event, length of trip, likelihood to return, expenditures per person, average age, and income. A graphic mapping technique was provided to visually depict the dispersion of the markets. Market applications suggestions were made as these segments were identified and to provide this segmentation method as a strategy to more accurately measure the economic significance of the event.