Factor Analysis of Card Sort Data: An Alternative to Hierarchical Cluster Analysis

Abstract

Software and product designers use card sorting to understand item groups and relationships. In the usability community, a common method of formal statistical analysis for open card sort data is hierarchical cluster analysis, which results in a tree of the items sorted into distinct, nested clusters. Hierarchical cluster analysis is appropriate for highly structured settings, like software menus. However, many situations call for softer clusters, such as designing websites where multiple pages link to the same target page. Factor analysis summarizes the categories created in card sorts and generates clusters that can overlap. This paper explains how to prepare card sort data for statistical analysis, describes the results of factor analysis and how to interpret them, and discusses when hierarchical cluster analysis and factor analysis are appropriate.