Using K-Mode Clustering to Identify Personas for Technology on the Trail
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Abstract
Hiking is a widely-used term used differently by different people, and technology has an increasing role in the hikes that people take. Given the tremendous growth in technology capabilities for fitness, navigation, and communication, the breadth of devices and applications has expanded. Use of technology differs based on not only individuals but also the kinds of tasks performed. This research seeks to understand the different perspectives of the hikers and the technology they carry with them on the trail through a survey, analysis, and persona creation. 40 self-described hikers participated in a survey that asked about demographic data, hiking preferences, and would-you-rather preferences asking participants to choose between envisioned hiking and technology scenarios. The collected data were clustered into 6 clusters using K-Mode clustering, and descriptive analysis identified unique characteristics for each cluster. Five personas were crafted using the identified characteristics based on the analysis, taking into account the correlation between hiking preference and age, preferred activities and motivation, and maximum expenses they spend on the tech they carry. These personas seek to act as a guide to those who purchase, design and use hiking related products for both commercial and research purposes.