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What is Card Sorting? Complete Beginner's Guide (2025)

Complete beginner's guide to card sorting for UX research. Learn what card sorting is, when to use it, how it works, and why it's essential for user-centered design.

By Free Card Sort Team

What is Card Sorting? Complete Beginner's Guide

Card sorting is a UX research method that reveals how users naturally group and label information. If you've ever wondered "where should this feature go?" or "how should we organize our navigation?", card sorting gives you the answer—directly from your users.

Card Sorting in 60 Seconds

What it is: Users organize cards (representing content, features, or pages) into groups that make sense to them.

Why it matters: Shows you how users think, not how you think.

When to use it: Designing navigation, organizing content, or structuring information.

How long it takes: 2-3 days to run a study, 1 day to analyze.

Cost: Free to $30 (using online tools + small incentives).


The Card Sorting Metaphor

Imagine you're organizing a bookstore.

Your way (insider perspective):

  • Fiction by publisher
  • Non-fiction by publication date
  • Technical books by ISBN

Customer's way (user perspective):

  • Fiction by genre (mystery, romance, sci-fi)
  • Non-fiction by topic (cooking, business, history)
  • Quick finds (bestsellers, new arrivals, staff picks)

Card sorting reveals the customer's way.


How Card Sorting Works

The Traditional Method (Physical Cards)

Historical approach:

  1. Write each item on an index card
  2. Give participants a stack of cards
  3. Ask them to group cards into piles
  4. Have them name each pile
  5. Record results manually
  6. Look for patterns across participants

Problems:

  • Time-consuming to set up
  • Limited to in-person sessions
  • Hard to analyze (manual counting)
  • Small sample sizes (5-10 people max)

The Modern Method (Digital/Online)

Today's approach:

  1. Create digital "cards" in online tool
  2. Send link to 20-40 participants
  3. They drag-and-drop to organize
  4. Software automatically analyzes results
  5. Get patterns, agreement scores, visualizations

Benefits:

  • Setup in 5 minutes
  • Remote participants (worldwide)
  • Automatic analysis
  • Larger sample sizes (20-40 people)
  • Results in days, not weeks

Try it free →


Types of Card Sorting

Open Card Sort

How it works: Users create their own category names.

Best for:

  • ✅ Starting from scratch
  • ✅ Don't know the best categories yet
  • ✅ Want unbiased input
  • ✅ Discovering how users think

Example:

You give participants:
├─ 30 feature cards (no categories)

They create:
├─ "My Stuff" (5 cards)
├─ "Shopping" (8 cards)
├─ "Help & Support" (4 cards)
└─ "Settings" (3 cards)

Output: Natural groupings + category names users would understand

Closed Card Sort

How it works: You provide category names, users sort cards into them.

Best for:

  • ✅ Validating existing structure
  • ✅ Testing specific hypotheses
  • ✅ Comparing option A vs. option B
  • ✅ Making sure your labels work

Example:

You give participants:
├─ Account
├─ Shop
├─ Support
└─ Company

They sort 30 cards into these 4 categories

Output: Which cards fit which categories, agreement scores

Hybrid Card Sort

How it works: Provide suggested categories, but users can create new ones.

Best for:

  • ✅ You have ideas but want flexibility
  • ✅ Testing + discovering simultaneously
  • ✅ Iterative refinement
  • ✅ Balanced approach

Example:

You suggest:
├─ Account
├─ Shop
└─ Support

Users can:
├─ Use your categories
├─ Rename them
└─ Create new ones like "My Orders"

Output: Validation of your ideas + new suggestions


When to Use Card Sorting

Perfect Use Cases

1. Website Navigation

  • Redesigning main menu
  • Too many pages, unclear structure
  • Users can't find what they need

Real example: E-commerce site with 50 product categories. Card sort revealed users wanted to browse by occasion (work, casual, athletic) not just product type.

2. App Information Architecture

  • Organizing features in mobile app
  • Deciding what goes in which menu/tab
  • Reducing complexity

Real example: Banking app with 30 features. Card sort showed users wanted "Move Money" and "See My Money" categories instead of "Transactions" and "Accounts."

3. Content Organization

  • Structuring blog or knowledge base
  • Organizing documentation
  • Creating content taxonomy

Real example: Help center with 150 articles. Card sort revealed users wanted task-based categories ("Getting Started," "Troubleshooting") not feature-based.

4. Product Categorization

  • E-commerce category structure
  • Filtering systems
  • Faceted search

Real example: Furniture store. Card sort showed customers think by room (bedroom, living room) AND by style (modern, rustic), leading to dual-axis navigation.

When NOT to Use Card Sorting

❌ Testing visual design

  • Card sorting is about organization, not aesthetics
  • Use: Usability testing or A/B testing

❌ Testing workflows or processes

  • Card sorting shows grouping, not sequential steps
  • Use: Task analysis or journey mapping

❌ Getting feedback on ideas

  • Card sorting assumes items are final
  • Use: Concept testing or surveys

❌ Testing findability directly

  • Card sorting shows groupings, not necessarily where users look first
  • Use: Tree testing (validates card sort results)

❌ Less than 15 items to organize

  • Too few items don't provide useful patterns
  • Better: Just ask users directly

The Science Behind Card Sorting

Why It Works

1. Mental Models

Humans organize information in their minds (mental models). Good design matches user mental models, not designer mental models.

Card sorting reveals mental models.

2. Cognitive Psychology

People naturally categorize to make sense of complexity. Card sorting taps into this innate ability.

Example: You instinctively group:

  • Fruits (apples, oranges, bananas)
  • Vegetables (carrots, broccoli, spinach)

Card sorting leverages this.

3. Collective Intelligence

20-30 people reveal patterns better than 1 expert. Patterns with 70%+ agreement indicate strong shared mental models.

What the Research Says

Sample Size Research:

  • 15 participants reveal ~90% of patterns
  • 20-30 participants give confidence
  • 30+ has diminishing returns

Reliability Studies:

  • Test-retest reliability: 85-90%
  • Remote vs. in-person: 85-95% similarity
  • Open vs. closed: Complement each other

Validation Research:

  • IA based on card sorting = 30-40% improvement in findability
  • Reduces navigation confusion by 50%+
  • Increases task completion rates significantly

Step-by-Step: Your First Card Sort

Step 1: Define Your Goal (5 minutes)

Ask yourself:

  • What am I trying to organize?
  • What decision will this inform?
  • Who are my users?

Example goal: "Understand how users would group our 30 product features for the app navigation redesign."

Step 2: Create Your Cards (15 minutes)

Select items:

  • 20-40 items to organize
  • Representative of full content
  • Specific, clear names

Example cards (SaaS product):

- Dashboard
- Analytics Reports
- Team Chat
- File Sharing
- Task Board
- Calendar View
- Time Tracking
- Notifications
- User Permissions
- Integrations
... (20 more)

Tips:

  • Use actual labels users will see
  • Avoid jargon unless your users use it
  • Keep names short (2-5 words)
  • Make each card distinct

Step 3: Choose Study Type (2 minutes)

First time? → Start with Open card sort

Why: Reveals how users naturally think without your bias.

Step 4: Write Instructions (5 minutes)

Template:

Welcome! Thank you for helping us improve [Product].

Please organize these features into groups that make sense to you.
Create category names that describe each group.

This should take 10-12 minutes. There are no right or wrong answers!

Thank you!

Step 5: Set Up Study (5 minutes)

Use a card sorting tool:

  • Free Card Sort (free, easy) [recommended]
  • Optimal Workshop (expensive, comprehensive)
  • UserZoom (enterprise-focused)

Create free study →

Step 6: Recruit Participants (1-2 days)

How many: 20-30 for open sort, 30-40 for closed

Who: Target users (not colleagues!)

Where to find them:

  • Customer email list (best)
  • User research panels (UserTesting, Respondent)
  • Social media
  • Friends/family (last resort)

Incentives: $5-$10 gift cards (optional but recommended)

Step 7: Launch Study (Instant)

Soft launch:

  • Send to 5 participants first
  • Check first few responses
  • Fix any issues
  • Send to everyone else

Monitor:

  • Check responses daily
  • Look for confusion
  • Send reminder after 3 days

Step 8: Analyze Results (4 hours)

Look for:

  • Cards grouped together 70%+ of time (strong relationships)
  • Most common category names
  • Surprising groupings
  • Cards with under 40% agreement (confusing or don't fit)

Most tools auto-generate:

  • Similarity matrix (visual heatmap)
  • Dendrograms (hierarchical grouping)
  • Agreement scores

Step 9: Implement Findings (Ongoing)

Create structure based on patterns:

Example resultsImplementation:

Users grouped:
├─ "My Work" (Dashboard, Tasks, Calendar)
├─ "Team Stuff" (Chat, Files, @Mentions)
├─ "Reports" (Analytics, Time Tracking, Export)
└─ "Settings" (Permissions, Integrations, Account)

Becomes app navigation:
├─ Work
├─ Team
├─ Insights
└─ Settings

Real Example: From Card Sort to Design

Before Card Sort

Internal team's proposed navigation:

├─ Features
├─ Data Management
├─ User Administration
├─ Configuration
└─ Tools & Utilities

Problem: Technical language, unclear what's where.

Card Sort Results

30 participants sorted 35 features. Patterns emerged:

Strong groupings (over 75% agreement):

├─ "My Projects" / "Work Space"
│  └─ Project list, Tasks, Files
├─ "Team" / "People"
│  └─ Members, Chat, Activity
├─ "Reports" / "Analytics"
│  └─ Dashboards, Data Export, Charts
└─ "Settings" / "Account"
   └─ Profile, Permissions, Billing

Implemented Design

Final navigation (based on card sort):

├─ Projects (most common user label)
├─ Team
├─ Insights (more approachable than "Reports")
└─ Settings

Results

  • 45% reduction in navigation confusion
  • 62% faster to find features
  • 28% increase in feature adoption
  • 4.1 → 4.7 star app rating

Common Beginner Mistakes

Mistake #1: Testing with Wrong People

Wrong: Ran card sort with 10 coworkers Right: Ran with 25 actual users

Impact: Coworker results reflect internal thinking, not user thinking.

Mistake #2: Too Many Cards

Wrong: 80 cards, 45-minute study Right: 35 cards, 12-minute study

Impact: Fatigue leads to rushed, unreliable results.

Mistake #3: Vague Card Names

Wrong: "Resources," "Platform," "More Options" Right: "Video Tutorials," "Dashboard," "Account Settings"

Impact: Users don't understand cards, create random groupings.

Mistake #4: Expecting 100% Agreement

Wrong: "Only 65% agreed, the study failed!" Right: "65% shows the primary pattern. 35% indicates some variation, which is normal."

Impact: Unrealistic expectations lead to ignoring valuable data.

Mistake #5: Skipping Validation

Wrong: "Card sort showed this structure, ship it!" Right: "Card sort suggests this. Let's validate with tree testing before building."

Impact: Card sorting shows groupings, not necessarily findability.


Card Sorting Tools

Free Card Sort (Recommended for Beginners)

Pros:

  • ✅ Free plan (3 studies)
  • ✅ 5-minute setup
  • ✅ No credit card required
  • ✅ Easy for participants (no login)
  • ✅ Mobile-friendly
  • ✅ Automatic analysis

Cons:

  • ❌ Free plan limited to 50 responses per study

Best for: First-timers, small teams, freelancers

Start free →

Optimal Workshop

Pros:

  • ✅ Industry standard
  • ✅ Advanced analytics
  • ✅ Multiple research methods

Cons:

  • ❌ Expensive ($149-$449/month)
  • ❌ Steeper learning curve
  • ❌ Overkill for simple projects

Best for: Large organizations, research agencies

DIY (Google Forms + Spreadsheets)

Pros:

  • ✅ Completely free
  • ✅ Full control

Cons:

  • ❌ Manual everything
  • ❌ Poor participant experience
  • ❌ Time-consuming analysis
  • ❌ No similarity matrix

Best for: Extremely tight budgets (but not recommended)


Frequently Asked Questions

Q: How is this different from surveys? A: Surveys ask opinions. Card sorting reveals mental models through behavior. More reliable for structure/organization questions.

Q: Can I run card sorting in-person? A: Yes, but online is faster, cheaper, and gets more participants. Reserve in-person for when you need follow-up questions during the activity.

Q: How long does a study take to complete (for participants)? A: 8-15 minutes for 30-40 cards. Keep it under 20 minutes to avoid fatigue.

Q: What if people disagree on groupings? A: Some variation is normal and valuable. Look for patterns with 60-70%+ agreement. Disagreement under 40% means cards may be unclear.

Q: Do I need to pay participants? A: Not always. Engaged customers often participate for free. General public usually needs $5-$10 incentive.

Q: Can I test multiple navigation ideas? A: Yes! Run multiple closed card sorts (one per option) or use hybrid sort.

Q: What software do I need? A: Online card sorting tool (Free Card Sort recommended), no other software needed.

Q: How many participants is enough? A: 20-30 for open sort, 30-40 for closed. Patterns emerge around 15-20, more gives confidence.


Next Steps

Learn More

Want to dive deeper?

Run Your First Study

Ready to try it?

  1. Create free account (2 minutes)
  2. Add your cards (5 minutes)
  3. Send to participants (1 minute)
  4. Get results (2-3 days)

No credit card required. No risk. Just valuable insights into how your users think.


Summary

Card sorting reveals how users naturally organize information.

Why it matters: Matches your design to user mental models.

When to use: Designing navigation, organizing content, structuring information.

How long: 2-3 days for study, 1 day to analyze.

Cost: Free to $30.

Getting started: Run your first study now →


Related Resources

Ready to Try It Yourself?

Start your card sorting study for free. Follow this guide step-by-step.

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