Using archetypes to create user panels for usability studies: Streamlining focus groups and user studies

Area of Science:

• Ergonomics and Human Factors
• Product Design
• Biomechanical Engineering

Background:

• Product designers prioritize user comfort, necessitating reliable user panels for accurate comfort studies.
• Current methods for user panel selection are often costly and time-consuming, relying on extensive human geometry analysis.
• A need exists for efficient and representative user sampling methods in the early stages of product development.

Purpose of the Study:

• To propose and validate a methodology for establishing a reliable user panel representative of large populations.
• To develop a framework for predicting comfort factors, specifically physical fit, using archetypal user profiles.
• To offer an alternative to traditional, resource-intensive methods for user sample selection in product testing.

Main Methods:

• Analysis of 200 head scan data points to identify distinct clusters representing user archetypes.
• Clustering algorithms were employed to derive 9 archetypal individuals from the ear and head database.
• Validation of the identified archetypes through physical fit assessments with 20 participants and 6 different headsets.

Main Results:

• Identification of 9 distinct archetypes from a database of 200 individuals, effectively representing population diversity.
• Successful validation of these archetypes in predicting physical fit comfort for new headset designs.
• Demonstration that the proposed archetypal method is more efficient than traditional large-scale geometric analysis.

Conclusions:

• The proposed methodology provides a reliable and efficient approach to forming user panels for product comfort studies.
• Archetypal representation derived from geometric data can accurately predict user comfort, particularly physical fit.
• This framework offers a cost-effective and time-saving alternative for selecting representative user samples in product development.