Card sorting takes the guesswork out of organizing information. When users can't find what they need, the problem often lies in how content is structured. 

In card sorting, participants group topics into categories that make sense to them, revealing how they naturally think about and organize information.

This UX research technique provides the foundation for intuitive navigation and information architecture. Whether you're designing a new website, reorganizing an app, or validating your current structure, card sorting offers direct insights into your users' mental models.

This guide covers everything you need to know: what card sorting is, when to use different types, how to run effective studies, and how to turn results into actionable design decisions.

Key takeaways

• Card sorting reveals how users naturally organize and label information, taking the guesswork out of navigation design.

• Open card sorting lets users create their own categories – ideal for new projects – while closed card sorting validates existing structures.

• The method works for any information organization challenge, from website menus to app navigation to product taxonomies.

• 15-30 participants typically provide enough data to identify meaningful patterns in how users group content.

• Results translate directly into actionable decisions about site structure, menu organization, and category labels.

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What is card sorting?

Card sorting is a technique where participants organize topics into categories that make sense to them. This user research method helps teams understand how people naturally group and label information, making it invaluable for creating intuitive information architectures.

Definition

Card sorting is a well-established UX method where participants group topics into categories according to criteria that make the most sense to them. During a card sorting session, participants receive a set of cards (either physical or digital) representing different pieces of content, features, or concepts. They then organize these cards into groups that feel logical and meaningful to them.

The beauty of card sorting lies in its simplicity. Rather than asking users to explain complex mental models through interviews alone, card sorting provides a hands-on way for participants to demonstrate their thinking. This makes abstract concepts tangible and reveals patterns that might not emerge through other research methods.

Purpose

Card sorting helps design or improve information architecture (IA) and navigation by revealing how users expect information to be organized. The primary purposes include:

• Validating existing structures: Test whether your current organization makes sense to users.

• Informing new designs: Create navigation systems based on user mental models.

• Reducing cognitive load: Organize content in ways that feel natural to your audience.

• Improving findability: Help users locate information more efficiently.

• Building consensus: Provide objective data to resolve internal debates about organization.

How it works

Users group "cards" (physical or digital) with labels, menus, or content items into categories that make sense to them. You can run a card sorting session in person using physical cards, or remotely using online tools like Lyssna.

The card sorting process typically involves:

1. Preparation: Create cards representing your content or features.

2. Instructions: Explain the task to participants without influencing their thinking.

3. Sorting: Participants organize cards into groups.

4. Labeling: Participants name their categories (in open card sorts).

5. Analysis: Look for patterns across multiple participants' sorts.

Remote card sorts are affordable, simple to create, and easy to recruit and share with participants. Online card sorting tools have reporting capabilities built in, so you can view, sort, and analyze data quickly.

"Lyssna provides some great features to test UX flows, conduct AB testing, card sorting, etc. It's an easy to use software and surveys are very quick and easy to set up."

– Ranjan N., G2 review

What is card sorting used for?

Card sorting helps teams make informed decisions about organizing and presenting information. It reveals how users naturally group content, what terminology resonates with them, and how they expect to navigate through information.

Improving information architecture

Card sorting validates how menus, categories, and content should be structured by revealing the organizational patterns that feel most natural to your users. When you understand how people group related concepts, you can create navigation systems that align with their expectations.

For example, say you're creating an ecommerce furniture website. Would your customers expect to see desks, office chairs, and shelving listed as separate categories? Or are they more likely to navigate to 'home office'? Card sorting helps answer these questions with real user data rather than assumptions.

This method is particularly valuable when:

• Launching new websites or applications

• Restructuring existing navigation systems

• Merging multiple sites or product lines

• Expanding into new content areas or product categories

Testing label clarity

Card sorting reveals whether users understand terms and headings by showing how they interpret and group labeled content. If participants consistently place cards in unexpected categories, it often indicates that your labels aren't communicating what you intended.

The Nielsen Norman Group advises against using terms that contain the same words, as participants tend to group these cards together. For example, most participants will group 'Strawberry planting' and 'Strawberry growing' together, because 'Strawberry' is repeated.

This insight helps teams:

• Identify confusing or ambiguous terminology

• Choose labels that resonate with users

• Avoid industry jargon that users don't understand

• Create consistent naming conventions across products

Identifying user mental models

Card sorting shows how users expect information to be grouped by revealing the underlying logic they apply when organizing content. These mental models represent the frameworks people use to understand and navigate information spaces.

Understanding user mental models helps teams:

• Design interfaces that feel intuitive from the first interaction

• Predict where users will look for specific information

• Create logical groupings that reduce cognitive load

• Build navigation systems that support user goals

For instance, how would readers of your food blog expect to see recipes sorted – by meal type, course, cuisine, diet, season, or ingredient? Card sorting reveals which organizational schemes resonate most strongly with your audience.

Optimizing navigation flows

Card sorting informs sitemap design and product taxonomy by providing data-driven insights into how users expect to move through information hierarchies. This helps create navigation flows that support natural user journeys rather than forcing users to adapt to arbitrary organizational schemes.

The method helps teams:

• Design logical page hierarchies

• Create intuitive breadcrumb systems

• Develop effective search and filtering options

• Plan user flows that align with mental models

Closed card sorting

Closed card sorting provides a structured approach to validating existing information architectures by asking participants to organize content within predefined categories.

Definition

In closed card sorting, participants place cards into predefined categories that you provide. Rather than creating their own groups, participants work within the constraints of your existing or proposed organizational structure.

Closed card sorting works well when you have a specific structure in mind and want to test whether users can successfully categorize content within that framework. 

The predefined categories might represent your current navigation menu, proposed new structure, or industry-standard organizational schemes.

Benefits

Closed card sorting is efficient for validating existing structures because it provides clear, comparable data across participants. Key benefits include:

• Faster analysis: Results are easier to quantify and compare since everyone uses the same categories.

• Direct validation: Shows whether your proposed structure works for users.

• Clearer insights: Reveals specific problem areas in existing organizations.

• Stakeholder buy-in: Provides concrete data to support or challenge current approaches.

• Resource efficiency: Requires less time for both participants and researchers.

Limitations

Closed card sorting does not reveal new groupings outside the predefined options, which can limit the insights you gain. Important limitations include:

• Constrained thinking: Participants can't suggest alternative organizational schemes.

• Forced choices: Users might place cards in categories that don't feel quite right.

• Missing opportunities: You might overlook better organizational approaches.

• Confirmation bias: Results might confirm existing structures even when alternatives would be better.

Open card sorting

Open card sorting offers maximum flexibility by allowing participants to create their own categories and labels, revealing natural user mental models without constraints.

Definition

In open card sorting, participants create their own categories and labels for organizing the cards. This approach provides complete freedom for users to group content according to their own logic and terminology.

Open card sorting works particularly well in the early stages of design when you want to understand how users naturally think about your content domain. 

Participants not only organize cards into groups but also create names for those groups, providing insights into both organizational patterns and preferred terminology.

Benefits

Open card sorting reveals user-driven groupings and natural mental models that you might not have considered. Key advantages include:

• Unbiased insights: No predetermined structure influences participant thinking.

• Natural terminology: Discover the words users actually use to describe categories.

• Unexpected patterns: Uncover organizational schemes you hadn't considered.

• Rich qualitative data: Understand the reasoning behind user groupings.

• Innovation opportunities: Identify new ways to organize content that better serve user needs.

For an open card sort, 30–50 cards should allow you to gain useful data about how your audience categorizes the cards without overwhelming participants.

Limitations

Open card sorting is harder to analyze and standardize because each participant creates unique categories with different labels. Challenges include:

• Analysis complexity: Requires more time to identify patterns across diverse groupings.

• Inconsistent terminology: Different participants use different words for similar concepts.

• Difficult comparison: Harder to quantify and compare results across participants.

• Implementation challenges: Translating diverse mental models into a single navigation system.

How to choose between open and closed card sorting

Selecting the right card sorting approach depends on your research goals, project stage, and available resources. Understanding when to use each method helps ensure you gather the most valuable insights for your specific situation.

When to use open card sorting

Open card sorting works best for early exploration or when building information architecture from scratch. Choose this approach when:

• Starting new projects: You're designing a completely new website or application.

• Exploring possibilities: You want to understand all possible ways users might organize content

• Questioning assumptions: Your team has different opinions about the best organizational approach.

• Discovering terminology: You need to understand what words users prefer for categories.

• Innovation focus: You're open to completely new organizational schemes.

Pro tip: Open card sorting provides the richest insights when you have the flexibility to implement whatever organizational structure emerges from user data.

When to use closed card sorting

Closed card sorting is ideal for validating or refining an existing information architecture. Use this method when:

• Testing current structures: You want to evaluate how well your existing navigation works.

• Comparing alternatives: You have specific organizational options to evaluate.

• Refining categories: Your basic structure is solid but needs fine-tuning.

• Limited flexibility: Technical or business constraints limit your organizational options.

• Quick validation: You need fast, quantifiable results to inform immediate decisions.

Factors to consider

Several factors should influence your choice between open and closed card sorting:

• Stage of design

• Project goals

• Available resources

• Team consensus

• Implementation constraints

Hybrid card sorting

Hybrid card sorting combines elements of both open and closed approaches. Participants start with predefined categories you provide, but they can also create new groups if needed.

If certain cards don't fit well into the existing categories, participants simply create their own groups with custom labels. This gives you the structure of closed sorting with the flexibility to discover unexpected organizational patterns.

When to choose hybrid card sorting: Choose hybrid card sorting when you have some solid organizational ideas but suspect you're missing something, or when you're refining an existing structure while staying open to improvements.

Benefits

Hybrid card sorting balances validation and discovery by providing some structure while remaining open to new insights. Benefits include:

• Structured flexibility: Provides guidance without completely constraining thinking.

• Validation plus discovery: Tests existing ideas while remaining open to new ones.

• Easier analysis: More structured than pure open sorting but more flexible than closed.

• Practical insights: Reveals both what works in current thinking and what's missing.

Moderated card sorting

Moderated card sorting involves a facilitator who guides participants through the process, asking questions and gathering qualitative insights alongside the sorting data.

Definition

In moderated card sorting, a moderator guides participants live, asking clarifying questions and encouraging participants to think aloud as they work.

This approach combines the quantitative data of card sorting with rich qualitative insights about participant reasoning.

The moderator can probe deeper into participant thinking, ask about difficult decisions, and understand the logic behind groupings. This makes moderated sessions particularly valuable for understanding not just what participants do, but why they do it.

Pro tip: You can do hybrid card sorting in Lyssna by creating a self-recruitment link and interviewing a participant as they take the test.

Benefits

Moderated card sorting provides rich qualitative insights and explanations that help teams understand the reasoning behind participant decisions. Key advantages include:

• Deep understanding: Learn why participants make specific grouping decisions.

• Real-time clarification: Ask follow-up questions when participants seem uncertain.

• Contextual insights: Understand how participants' backgrounds influence their thinking.

• Problem identification: Spot confusion or difficulty as it happens.

• Relationship building: Create stronger connections with users through direct interaction.

Limitations

Moderated card sorting is more time-intensive and resource-heavy than unmoderated approaches. Challenges include:

• Scheduling complexity: Coordinating times that work for both researchers and participants.

• Facilitator bias: Moderator questions or reactions might influence participant behavior.

• Limited scale: Practical constraints limit the number of participants you can include.

• Higher costs: Requires more researcher time and often participant incentives.

• Analysis burden: Qualitative data requires additional time to process and synthesize.

Unmoderated card sorting

Unmoderated card sorting allows participants to complete the sorting process independently, typically through online platforms, making it a scalable and efficient research method.

Definition

In unmoderated card sorting, participants complete the sort independently, usually via online tools, without a researcher present. Participants receive instructions and complete the task on their own schedule, submitting results through the research platform.

Unmoderated card sorting leverages technology to scale research efforts, allowing teams to gather data from many participants quickly and cost-effectively. Participants can complete the task when convenient for them, removing scheduling barriers that often limit research participation.

Benefits

Unmoderated card sorting is scalable, fast, and cost-efficient, making it accessible for teams with limited research resources. Key advantages include:

• Scale efficiency: Collect data from many participants simultaneously.

• Cost effectiveness: Lower per-participant costs than moderated sessions.

• Scheduling flexibility: Participants complete tasks when convenient for them.

• Reduced bias: No moderator present to influence participant behavior.

• Quick turnaround: Results available as soon as participants complete the task.

• Geographic reach: Include participants from diverse locations easily.

Limitations

Unmoderated card sorting provides less qualitative feedback compared to moderated sessions, limiting your understanding of participant reasoning. Constraints include:

• Limited context: No opportunity to ask why participants made specific decisions.

• Unclear motivations: Difficult to understand the logic behind groupings.

• No clarification: Can't help participants who might be confused by instructions.

• Surface-level insights: Results show what participants did but not their thought process.

• Technical issues: Participants might encounter problems without support available.

How to run an unmoderated card sort

Running an effective unmoderated card sort requires careful planning and clear execution. Follow these steps to ensure you gather meaningful insights that inform your design decisions.

The below interactive demo also gives a picture of how to run a card sort in Lyssna.

Step 1: Define your goal

Before creating your card sort, clarify what you want to learn about labels, information architecture, or categories. Clear goals guide every other decision in your research process.

Common card sorting goals include:

• Testing current navigation: Understand how well your existing structure works for users.

• Exploring new organization: Discover how users naturally group your content.

• Validating proposed changes: Test whether planned restructuring makes sense to users.

• Comparing alternatives: Evaluate different organizational approaches.

• Understanding terminology: Learn what words users prefer for categories.

Step 2: Select a tool

Choose a card sorting tool that meets your research needs and budget. Lyssna offers comprehensive card sorting capabilities with built-in analysis tools and participant recruitment options.

Step 3: Create cards

Begin by brainstorming your cards and categories. Pull together all the information you can, like your sitemap or product inventory list. You might even find it beneficial to run a content audit on your site to get a full list of your existing content.

Use realistic items like menu options, product categories, or feature names that represent your actual content. Make sure each card is easy to understand and represents a single concept. The information you provide on each card needs to be clear. If your participants don't understand the meaning, you're likely to end up with inconsistent categories.

Card creation best practices:

• Use familiar language: Write cards in terms your users understand, avoiding internal jargon.

• Keep cards focused: Each card should represent one clear concept or piece of content.

• Make cards scannable: Use concise labels that participants can quickly process.

• Ensure clarity: Test card labels with colleagues to identify potential confusion.

• Consider context: Include enough information for participants to understand what each card represents.

Images can be a good way to illustrate concepts or items, or help to clarify text when cards might be ambiguous or unfamiliar to participants.

While the Lyssna test builder supports a maximum of 100 cards and 30 categories, we recommend showing around 30–40 cards per participant to maintain engagement and avoid cognitive overload.

Step 4: Recruit participants

Target the right audience for relevance by recruiting participants who match your actual user base. The quality of your participants directly impacts the value of your insights.

Recruitment strategies:

• User database: Invite existing customers or users who know your product.

• Social networks: Share with relevant communities and groups.

• Professional networks: Reach out through LinkedIn or industry connections.

• Research panels: A recruitment panel – like the Lyssna research panel – can be a quick and easy option, especially if you're looking for a large testing group or participants with specific demographics.

Participant requirements:

• Relevant experience: Participants should have experience with your type of product or content.

• Representative demographics: Match your actual user base in key characteristics.

• Adequate sample size: Plan for 15-30 participants for meaningful patterns.

• Clear expectations: Communicate time requirements and task complexity upfront.

Step 5: Run the test

Launch the card sort online and monitor participation to ensure you're gathering quality data. Most unmoderated card sorts run for several days to allow participants to complete the task when convenient.

During the test:

• Monitor completion rates: Track how many participants start and finish the task

• Watch for patterns: Look for early signs of confusion or technical issues

• Provide support: Be available to answer participant questions if they arise

• Maintain momentum: Send gentle reminders to participants who haven't completed the task

Step 6: Collect and analyze data

Look for grouping patterns, similarities, and disagreements across participants to identify meaningful insights for your information architecture decisions.

The results of an open card sort in Lyssna

Card sorting best practices

Following established best practices helps ensure your card sorting studies generate reliable, actionable insights that inform better design decisions.

Keep cards clear and concise

Avoid jargon and overly complex labels that might confuse participants or bias their sorting decisions. Clear, understandable cards lead to more reliable results.

Guidelines for clear cards:

• Use plain language: Write in terms your users understand, not internal terminology.

• Avoid ambiguity: Each card should have one clear meaning.

• Test comprehension: Review cards with colleagues to identify potential confusion.

• Consider context: Provide enough information for participants to understand each card's meaning.

• Maintain consistency: Use similar language patterns across all cards.

Limit the number of cards

Research shows that 30 to 40 cards work best for engagement and meaningful results. Too few cards (under 30) don't provide enough data for patterns, while too many cards (over 40) overwhelm participants and reduce data quality.

Pro tip: If you have more content, run multiple smaller studies focused on specific areas rather than one overwhelming study.

Recruit the right users

Match test participants to your actual user personas to ensure insights reflect real user behavior rather than random preferences.

Recruitment criteria:

• User experience: Participants should have relevant experience with your type of product.

• Demographics: Match key characteristics of your actual user base.

• Motivation level: Choose participants who are genuinely interested in helping improve the product.

• Availability: Ensure participants can complete the task within your timeline.

Run a pilot test

Test your card sort with a small group first to ensure clarity and fix potential confusion before launching to your full participant group.

Pilot testing steps:

• Internal review: Have team members complete the sort to identify obvious issues.

• Small external test: Run with 3-5 external participants to catch real-world problems.

• Instruction clarity: Verify that participants understand what they're supposed to do.

• Technical functionality: Ensure the tool works properly across different devices and browsers.

• Time estimation: Confirm that the task takes a reasonable amount of time to complete.

Combine with other methods

Use card sorting alongside other research methods for stronger information architecture validation. Card sorting shows how users want to organize information, while other methods test whether they can actually find what they need.

Complementary research methods

4 card sorting examples

These practical examples demonstrate how card sorting applies across different industries and use cases, showing the versatility and value of this research method.

1. Ecommerce store

Grouping product categories helps online retailers create intuitive navigation that matches customer shopping patterns. For example, an electronics retailer might discover that customers group items by use case rather than technical specifications.

Common ecommerce card sorting applications:

• Product categorization: Understanding how customers naturally group products.

• Filter organization: Determining which filtering options are most important.

• Menu structure: Creating top-level navigation that matches shopping behavior.

• Search categories: Organizing search results in meaningful ways.

Example insight: Customers might group "laptop bags," "laptop stands," and "wireless mice" together as "laptop accessories" rather than separating them into "bags," "furniture," and "peripherals."

3. SaaS dashboard

Organizing features into intuitive menus helps software companies create interfaces that match user mental models of functionality and workflow.

SaaS card sorting applications:

• Feature organization: Grouping related functionality for easier discovery.

• Menu design: Creating navigation that supports user workflows.

• Settings organization: Structuring configuration options logically.

• Help content: Organizing support materials by user needs.

Example insight: Users might group "user management," "permissions," and "security settings" together as "team administration" rather than spreading them across different menu sections.

3. News website

Testing article sections helps media organizations structure content in ways that match reader interests and browsing patterns.

News website applications:

• Content categorization: Organizing articles into meaningful sections.

• Topic organization: Grouping related subjects for better discoverability.

• Archive structure: Creating logical ways to browse historical content.

• Personalization options: Understanding how users want to customize their experience.

Example insight: Readers might prefer "local news" as a primary category that includes politics, sports, and business from their area, rather than separating local content across topic-based sections.

4. Mobile banking app

Sorting transactions, accounts, and services helps financial institutions create mobile experiences that align with customer mental models of banking.

Banking app applications:

• Service organization: Grouping banking services by customer needs.

• Transaction categorization: Creating meaningful ways to organize financial activity.

• Account management: Structuring account-related features logically.

• Help and support: Organizing assistance options by common problems.

Getting started

Lyssna has a library of card sorting templates to help you get started. Each template includes a link to example test results, showing you what successful card sorting studies look like in practice.

"Previously, a lot of UX tools would only let you run one study type at a time - Lyssna changed the game here. Being able to run a card sort and a tree test or first click task within a single study for example helps to get to navigation insights much quicker at a lower cost than trying to do all of these separately."

– Verified User in Hospitality, G2 review

How to analyze card sorting data

Card sorting analysis reveals patterns in how users organize information. Your goal is to identify common groupings, understand disagreements, and translate findings into practical navigation structures.

Look for grouping patterns

Examine which cards consistently appear together across multiple participants' sorts. These patterns reveal the strongest associations in user mental models.

What the patterns mean:

Pattern analysis techniques:

• Frequency analysis: Count how often specific cards appear together.

• Cluster identification: Look for groups of cards that consistently co-occur.

• Outlier identification: Note cards that participants sorted inconsistently.

Use similarity matrices and dendrograms

Statistical tools quantify how often pairs of cards appear together, regardless of category names participants used.

In Lyssna:

• Agreement matrix shows the percentage of participants that placed each card into a category.

• Similarity matrix (open card sorts) shows how often pairs of cards are sorted into the same category.

Understanding the scores:

• High scores – Cards participants consistently group together.

• Low scores – Cards participants rarely place in the same category.

• Moderate scores – Cards with some association but not universal agreement.

Identify disagreements

Cards that users sorted inconsistently often indicate problems with labels, unclear concepts, or genuine differences in how users think.

Translate into IA recommendations

Turn findings into actionable navigation structures by using card sorting insights to inform your information architecture decisions. Here’s how the process might look like:

1. Identify high-level patterns: Look for the strongest groupings across participants.

2. Standardize categories: Combine similar category names that participants created.

3. Use built-in reporting tools: Leverage platform analytics to quantify relationships.

4. Define categories: Create proposed navigation structures based on patterns.

5. Balance with business needs: Consider technical and business constraints alongside user preferences.

6. Validate with testing: Plan follow-up research to test your proposed information architecture.

Implementation considerations:

• Business constraints: Balance user preferences with technical limitations.

• Content strategy: Ensure your IA supports content goals and user needs.

• Navigation design: Create menu structures that reflect user mental models.

For detailed guidance on analyzing your results, refer to this Lyssna help center article that explains how to view and analyze your card sorting test results in Lyssna.

Ready to understand your users' mental models? 

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FAQs about card sorting

What is card sorting in UX research?

What is the difference between open and closed card sorting?

What is hybrid card sorting?

How many participants do you need for a card sort?

How do you analyze card sorting results?