5 Minute UX podcast

Use Open Card Sorts for New Navigation Structures

11.11.2026
0:00
10:42
15 Sekunden vorwärts
15 Sekunden vorwärts

Learners will apply the open card sort technique to derive user-defined categories for new or significantly revised information architectures. This capability allows you to structure complex content hierarchies, such as intranets or websites, based on natural user mental models rather than predefined assumptions.

Learning Objective: By the end of this lesson, learners will be able to apply the open card sort method to determine a new navigational structure or validate significant changes to an existing one.

Transcript

Defining the Open Card Sort Mechanism

In an open card sort, you hand participants a set of items printed on cards and ask them to group them in a way that makes sense. No categories are provided up front. Instead, the participant creates the groups and gives each one a name. They describe what belongs where based on their own mental model of the content.

This stands in sharp contrast to a closed sort, where the high-level categories are already defined and participants simply place items into those pre-existing buckets. In the open variation, the structure emerges from the people doing the sorting, not from the researcher’s assumptions.

The primary goal is to generate a site map or a hierarchy of content, categories, and subcategories. This structure organizes specific content types like articles, documents, videos, or photos. By letting participants define the logic, you capture how users naturally perceive relationships between different pieces of information.

When the session concludes, you look for common patterns in how people grouped the items. You also note areas of confusion or disagreement. These insights reveal the underlying mental models that should drive your navigational structure.

Key Points:

  • Participants are given items on cards and asked to put them into groups that make sense to them without provided categories

  • Unlike closed sorts, participants make their own groups and title each group themselves

  • The primary goal is to create a site map or hierarchy of content, categories, and subcategories for items like articles, documents, videos, or photos

Selecting the Right Sorting Context

The right moment to reach for an open card sort is when you are determining a new navigational structure from scratch. You might also use it when making significant changes to an existing navigational structure, where the old hierarchy no longer fits the content. The core goal is to create a site map that establishes a clear hierarchy of content, categories, and subcategories. This approach is especially effective for complex content sources, such as a company intranet, where user mental models must drive the organization.

In these scenarios, participants sort items like articles, documents, videos, or photos into groups that make sense to them. Because they create the groups themselves, the resulting structure reflects how people actually think about the information. This direct access to user mental models is why the technique outperforms predefined categories in these contexts. You are building the architecture based on genuine user understanding rather than assumptions. The outcome is a structure that feels intuitive because it emerged from real user behavior.

This context sets the stage for the specific execution methods that follow.

Key Points:

  • Open card sorts are specifically recommended for determining a new navigational structure

  • They are also indicated when making significant changes to an existing navigational structure

  • This technique is excellent for content sources like company intranets where user mental models drive the hierarchy

Executing Individual and Remote Sessions

The standard way to run an open card sort is with a single participant, in person, sorting physical cards. This individual format keeps the mental model pure because the participant is not influenced by others in the room. You can also run these sessions remotely using digital tools that replicate the card-sorting experience. These remote setups allow you to recruit participants who are geographically distributed while still capturing the same individual decision-making process.

Group sorts exist as a variation where participants work together to sort items, but this is not the typical approach for open sorts. In a group setting, the dynamic shifts toward consensus-building rather than individual mental modeling, which can muddy the data you are trying to collect. The primary goal remains understanding how a single user organizes information, so individual sessions are the norm for this technique.

When executing remotely, you need tools that support both the sorting activity and the subsequent analysis. Platforms like OptimalSort or UXtweak provide the interface for participants to drag and drop digital cards into their own groups. These tools also capture the data in a format that makes analysis manageable, which is critical because open sort data is more complex to interpret than closed sort results. You are looking for patterns in how participants named and grouped their categories, not just checking off predefined labels.

Key Points:

  • The standard execution mode is an individual, in-person card sort, though remote tools allow for distributed participation

  • Group sorts exist as a variation where participants work together, but open sorts are typically individual

  • Remote execution requires tools that support both the sorting activity and subsequent analysis

Analyzing Patterns and Confusion Areas

The real challenge with an open card sort isn't the sorting itself, it’s what happens after you collect the data. Since participants create their own groups and name them, you don't have a predefined set of categories to fall back on. This makes the analysis significantly more complex than a closed sort, where you can simply count how many items landed in each of the few provided buckets.

Here, you’re looking for common patterns in how people are sorting the items across different participants. You’re also hunting for common areas of confusion or disagreement, which are your most valuable signals for information architecture decisions. If three different people put the "Help" article into "Pricing" but named that group differently, that’s a structural conflict you need to resolve.

Because there’s no small set of possible categories to focus on, you have to interpret the semantic overlap in the labels participants chose. This is where manual analysis becomes critical, and resources like Donna Spencer’s spreadsheet provide the specific instructions needed to make sense of that open-ended data. The goal is to distill that noise into a coherent hierarchy, identifying where the user’s mental model diverges from your intended structure.

Key Points:

  • At the end of the round, common patterns should emerge in how people are sorting the items

  • Common areas of confusion or disagreement are key outcomes to identify for information architecture decisions

  • Analysis is more complex than closed sorts because there is no small set of possible categories to focus on

Applying Tools for Manual and Digital Analysis

So, when you’re ready to apply appropriate tools and analysis methods to interpret common patterns and confusion areas, you have a specific path. If you’re running the sort remotely, OptimalSort or UXtweak handle both the participant session and the backend analysis for you. They strip away the manual labor of chasing down individual grouping decisions, which is a significant time saver.

For manual analysis, or if you need a more granular view of the data, look to Donna Spencer’s spreadsheet. It’s an excellent resource specifically for interpreting open sort data, and it comes with built-in instructions to guide your process. This is particularly helpful because open sorts lack the predefined high-level categories that make closed sorts easier to analyze.

Here is the decision you face: do you need the speed of a closed sort, or the depth of an open one? Closed sorts are relatively easy to analyze because you can simply count how often items fell into specific buckets. With open sorts, you’re building the map from scratch, so your analysis tools need to handle that complexity. When you sit down to analyze your results, remember that you’re not just counting items; you’re identifying where user mental models diverge. That divergence is your most valuable data.

Key Points:

  • Use OptimalSort or UXtweak for remote sorting capabilities and built-in analysis tools

  • For manual analysis, utilize Donna Spencer’s spreadsheet which includes instructions for interpreting open sort data

  • Compare results against closed sort outcomes, which are easier to analyze due to predefined high-level categories

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