Using the similarity matrix to surface card sorting insights (+template)

Card sorting is a valuable UX research methodology used to understand users' mental models and inform the design of a product's information architecture. By allowing participants to group concepts, ideas, or topics into categories that make sense to them, a card sorting exercise helps designers align their designs with users' real-world experiences. The resulting data can be analyzed using a similarity matrix, which quantifies the frequency with which items are grouped together, offering insights into user-driven relationships between concepts. Different types of card sorting exercises, such as open, closed, and hybrid, each offer distinct benefits and limitations. Open card sorting provides the richest insights by allowing participants to create their own categories, while closed card sorting uses predefined categories that may not capture user preferences as effectively. The similarity matrix, which displays the degree of association between items, aids in spotting patterns and refining categories for better usability and navigation. This method can be enhanced through normalization, conditional formatting, and visualization tools like dendrograms, ensuring a comprehensive analysis of user perceptions. In conclusion, a similarity matrix is an efficient tool for summarizing card sorting data, which can significantly improve the design and user experience of digital products.