Card sorting

TL;DR

• Definition: Card sorting is a UX research method where participants organize content into groups that make sense to them
• Types: Two main types: open card sorting (users create & name categories) and closed card sorting (predefined categories)
• Tools: Popular options include OptimalSort, UserZoom, and Maze for remote testing
• Applications: Primarily used for designing navigation structures, information architecture, and menu organizations

What is Card Sorting?

Card sorting is a user research technique where participants organize information into logical groups. It helps designers and researchers understand how users think about content organization and create intuitive information architectures. This method reveals users' mental models - their natural way of categorizing and finding information.

Types of Card Sorting

Open Card Sorting

In open card sorting, participants create their own categories and name them. This approach is ideal when you want to:

• Discover how users naturally group your content
• Generate new ideas for menu structures
• Understand users' mental models without imposing existing categories

Closed Card Sorting

With closed card sorting, participants sort items into predefined categories. This method works best when you:

• Want to validate an existing structure
• Need to fit new content into an established organization
• Have specific category names that must be used

Hybrid Card Sorting

Some studies use a hybrid approach where participants can both use predefined categories and create new ones, offering flexibility while maintaining some structure.

Tools for Card Sorting

The landscape of card sorting tools has evolved significantly with technological advancement. Modern researchers now have access to a variety of digital platforms that have replaced traditional physical cards. OptimalSort stands out as a comprehensive solution with robust analysis features, while UserZoom offers seamless integration with other UX research tools. For those seeking a streamlined experience, Maze provides quick setup and automated analysis capabilities. Budget-conscious researchers can utilize free alternatives such as simple spreadsheet templates or basic online sorting tools, though these typically offer limited functionality. The open-source community has also developed alternatives that provide essential features without cost barriers.

Card Sorting vs. Tree Testing

The relationship between card sorting and tree testing is complementary in the UX research process. While card sorting helps determine the initial organization of content by exploring users' natural grouping tendencies, tree testing serves as a validation method for the proposed structure. When used together, these methods create a robust approach to information architecture. Card sorting reveals how users naturally think about and categorize information, providing insights into their mental models. Tree testing then validates whether users can effectively navigate through the resulting structure, identifying potential issues or confusion points in the proposed organization.

Conducting a Card Sorting Session

The process of conducting a card sorting session involves careful planning and execution to ensure valuable results. The preparation phase requires thoughtful selection of content items to sort, making a strategic choice between open or closed sorting methodologies, and determining an appropriate sample size, typically ranging from 15 to 30 participants. During execution, researchers must present cards to participants with clear, unambiguous instructions while carefully observing and documenting the sorting process. The analysis phase focuses on identifying patterns in groupings, examining category names in open sorting scenarios, and considering outliers and unexpected groupings that might reveal important insights about user thinking.

Benefits and Limitations

Card sorting methodology offers significant advantages while also presenting certain challenges. The primary benefit lies in its ability to reveal natural user mental models, providing both quantitative data through sorting patterns and qualitative insights through participant feedback. This method excels at helping create intuitive navigation structures that align with user expectations. However, researchers should be aware of its limitations. The analysis process can be time-consuming, particularly with large datasets or numerous participants. Careful participant selection is crucial for meaningful results, as different user groups may have varying mental models. Additionally, conflicting results between participants can complicate the interpretation process and require additional investigation to resolve.

Future of Card Sorting

The evolution of card sorting continues to be shaped by technological advancements and changing user research needs. AI-powered analysis tools are emerging as powerful allies in processing and interpreting card sorting data, offering faster and more sophisticated insights. Remote testing capabilities have expanded the reach and efficiency of card sorting studies, allowing researchers to gather data from geographically diverse participants. The integration with other UX research methods is becoming more seamless, creating comprehensive research ecosystems. Looking ahead, virtual and augmented reality applications promise to bring new dimensions to card sorting, potentially offering more immersive and engaging ways to understand user categorization preferences.