Open card sorting: Discover how users naturally group your content

At its core, open card sorting allows participants to group items into categories that make sense to them, free from predefined labels or structures. This natural, user driven approach uncovers the mental models people bring when exploring a product, website, or app. Rather than assuming how content should be organized, open card sorting gives teams a window into how users truly think. The insights are incredibly valuable for reducing guesswork, improving information architecture, and ensuring that content is understandable and findable. When the right structure mirrors user thinking, products feel easier to navigate, users complete tasks faster, and overall experience quality improves.

Open card sorting is especially powerful because it reveals patterns and expectations you often cannot see through surveys or usability testing alone. Participants may create category labels you would never consider, pair items in unexpected ways, or struggle to group certain content at all. Each action provides important clues about gaps in clarity, competing mental models, or opportunities to simplify. The method scales well across audiences, letting teams compare how different user segments think about the same content. With the rise of remote testing interfaces, participants can complete card sorts anywhere, giving teams fast access to diverse perspectives that strengthen their design decisions.

The most effective open card sorts combine behavioral observation with structured outputs. Watching how users drag, rearrange, and debate card placements reveals the reasoning behind their decisions. Meanwhile, aggregated data highlights patterns across participants, showing which groupings are common, which are controversial, and which require refinement. When teams pair these insights with complementary methods like tree testing or prototype usability studies, they can validate their final information architecture with confidence. Open card sorting is not just about creating categories. It is about discovering the mental pathways users rely on to make sense of your content.

How product teams use open card sorting to create intuitive feature structures

Product teams use open card sorting to ensure that features and content are organized in a way that feels logical to users. Before building new navigation, adding features, or restructuring product menus, product teams run open card sorts to see how users naturally group concepts. These insights reveal whether current labels align with user expectations, where confusion exists, and which features users see as closely related. When product structures align with mental models, adoption improves and onboarding friction decreases. Open card sorting gives product teams the clarity they need to design product ecosystems that feel intuitive from day one.

How research teams use open card sorting to understand mental models at scale

Research teams rely on open card sorting to capture large scale patterns in how users interpret content. Because the method produces both qualitative reasoning and quantitative grouping data, it allows researchers to diagnose inconsistencies, test competing structures, and identify opportunities for clearer categorization. Agreement matrices show where participants align, while outlier groupings help uncover gaps in understanding. Research teams use these insights to guide information architecture decisions across websites, knowledge bases, support portals, and product interfaces. With open card sorting, researchers get both the what and the why behind user behavior, which strengthens their ability to advise on design strategy.

How design teams use open card sorting to build navigation that feels natural

Design teams use open card sorting to craft navigation systems and content hierarchies that match how people think, not how teams internally label information. By giving users the freedom to create their own categories, designers gain access to authentic language, real world logic, and unexpected relationships between content items. Watching participants sort cards reveals moments of hesitation, debate, or confusion, all of which guide clearer labeling and structural decisions. Design teams often pair open card sorting with tree testing to validate whether the proposed structure improves findability. The result is a navigation system that feels intuitive, cohesive, and easy to use.

Introducing Askable Card Sorting

Askable Card Sorting is purpose built to help teams understand how users naturally organize information at scale. With support for open, closed, hybrid, and ranked card sorts, teams can explore mental models from multiple angles. The mobile optimized interface ensures participants can complete sorts easily on any device, increasing both engagement and completion rates. Randomized card order eliminates position bias automatically, while stack ranking adds a powerful layer that lets users prioritize items within groups for deeper insight.

Askable delivers clarity through both recordings and structured analysis. Full session recordings with participant audio let you watch users sort, hesitate, debate, and change their minds in real time. This gives teams the context behind grouping decisions and helps uncover the reasoning behind unexpected patterns. On the quantitative side, built in analysis tools automatically group similar categories, eliminating hours of spreadsheet cleanup. Agreement matrices highlight unanimous and controversial groupings, helping teams confidently shape their information architecture. When it is time to share insights, Askable makes exporting easy, offering presentation ready images and raw CSV files for deeper analysis.

The platform is powered by Askable’s global participant ecosystem, spanning more than 5,300 cities and 15 languages with a 97.8 percent show rate. This ensures that card sorting studies reflect real perspectives from verified participants. Whether you are reorganizing a complex website, simplifying product navigation, or validating a new content model, Askable Card Sorting helps you move from messy data to clear decisions faster.