Card Sorting 🗂️ Prompts

Purpose: Card sorting helps design teams understand how users categorise information, enabling clearer IA and navigation.

Design Thinking Phase: Empathise

Time: 45–60 min session + 1–2 hours analysis

Difficulty: ⭐⭐

When to use:Early in the product design process to explore mental modelsWhen redesigning information-heavy interfaces like dashboards or help centresTo validate navigation logic before wireframing or testing

What it is

Card sorting is a qualitative UX research method where participants organise topics into categories that make sense to them. It uncovers user mental models and informs the structure of content or features, typically in navigation design or content-heavy products.

📺 Video by NNgroup. Embedded for educational reference.

Why it matters

Product teams often structure information based on internal logic or legacy models — not how users actually think. Card sorting corrects this by revealing how real users mentally organise tasks or categories. The result is more intuitive navigation, reduced friction, and cleaner information architecture. It’s especially valuable in redesigns, product onboarding journeys, and content-heavy platforms like SaaS tools or education apps.

When to use

• When users are struggling to find information or complete tasks efficiently
• When IA decisions are based on assumptions or internal roles
• In localisation projects where taxonomy may shift across regions or cultures

Benefits

• Rich Insights: Helps uncover user needs that aren’t visible in metrics.
• Flexibility: Works across various project types and timelines.
• User Empathy: Deepens understanding of behaviours and motivations.

How to use it

• Define your goal (e.g., restructure a dashboard menu or streamline a shopping flow).
• Select content items or functionalities to be sorted (10–30 ideal).
• Choose the card sorting type: open (users define categories), closed (you define categories), or hybrid.
• Recruit 5–10 target users per segment for qualitative insight.
• Use tools like OptimalSort or conduct manual sorts with printable cards.
• Observe sessions and note user rationale for grouping decisions.
• Analyse patterns across users to form taxonomy, IA labels, and navigation logic.

Example Output

A fictional example from an edtech dashboard redesign:

• Key groupings (open-sort):
  • “Learning Resources”: videos, quizzes, assignments
  • “Progress Tools”: grades, analytics, feedback
  • “Community”: peer messages, discussion boards
• Label preferences: Users preferred “Progress” over “Reports” by a 6:1 margin
• Navigation implication: Merge ‘Assignments’ and ‘Quizzes’ into a single section under ‘Learning’

Common Pitfalls

• Too few participants: Insights from 1–2 people may be misleading; aim for at least 5–10 per segment.
• Ambiguous items: Vague cards like “Reports” or “Tools” make it difficult for users to sort meaningfully.
• Ignoring category rationale: Observing how users talk through their sort is often more valuable than the final categories.

10 Design-Ready AI Prompts for Card Sorting – UX/UI Edition

How These Prompts Work (C.S.I.R. Framework)

Each of the templates below follows the C.S.I.R. method — a proven structure for writing clear, effective prompts that get better results from ChatGPT, Claude, Copilot, or any other LLM.

C.S.I.R. stands for:

• Context: Who you are and the UX situation you're working in
• Specific Info: Key design inputs, tasks, or constraints the AI should consider
• Intent: What you want the AI to help you achieve
• Response Format: The structure or format you want the AI to return (e.g. checklist, table, journey map)

Level up your career with smarter AI prompts.Get templates used by UX leaders — no guesswork, just results.Design faster, research smarter, and ship with confidence.First one’s free. Unlock all 10 by becoming a member.

Prompt Template 1: “Generate Open Card Sorting Items for Navigation Audit”

Generate Open Card Sorting Items for Navigation Audit

Context: You are a UX researcher conducting a navigation audit for a client’s B2B analytics dashboard.  
Specific Info: The dashboard includes 15 key features spanning data entry, visualisation, exports, and permissions.  
Intent: Create a list of candidate items for an open card sorting session with end users to reveal intuitive groupings.  
Response Format: Return a bulleted list of 20–25 items in clear, user-facing language suitable for usability testing.

If feature naming is unclear, ask clarifying questions before generating items.  
Then, suggest one follow-up prompt for category labelling or IA testing.

Prompt Template 2: “Cluster Card Sort Results into Thematic Groups”

Cluster Card Sort Results into Thematic Groups

Context: You are analysing results from 12 in-depth card sorting sessions with mixed internal/external users.  
Specific Info: Participants grouped 25 cards into 4–7 named categories. User labels varied significantly.  
Intent: Identify common themes, consolidate label overlaps, and recommend clear groupings for IA development.  
Response Format: Provide a table with: Proposed Group, Sample Cards, Frequent Labels, and Notes.

Ask if you'd like help visualising these clusters as a site map or navigation sketch.

Prompt Template 3: “Write Interview Questions for Card Sort Think-Aloud”

Write Interview Questions for Card Sort Think-Aloud

Context: You are running a moderated card sorting session with new users on a mental health app.  
Specific Info: They're sorting 20 self-care features into categories that make sense to them.  
Intent: Develop 8–10 think-aloud and clarification questions to surface users' decision-making process.  
Response Format: Return a bullet-point checklist of interview questions to use in the session.

Suggest follow-up ways to synthesise user comments into insights or friction points.

Prompt Template 4: “Compare Label Preferences by Segment”

Compare Label Preferences by Segment

Context: You’re analysing open-sort feedback across two regions for a travel booking dashboard.  
Specific Info: Participants from AU and SG used different terminology for identical cards.  
Intent: Help detect label differences and suggest harmonised IA labels suitable for both markets.  
Response Format: Create a comparison table with: Term (AU), Term (SG), Recommended Label, Rationale.

Offer guidance on how to validate harmonised labels in follow-up usability tests.

Prompt Template 5: “Simulate a Closed Card Sort Evaluation”

Simulate a Closed Card Sort Evaluation

Context: You designed five initial categories for a closed card sort and now want AI feedback first.  
Specific Info: You have labelled groups based on established IA: Files, Reports, Tools, Settings, Help.  
Intent: Validate category logic by simulating a closed sort with hypothetical new users.  
Response Format: Return simulated card placement across categories with reasoning per placement.

Ask what assumptions each placement might challenge in real-world behaviour.

Prompt Template 6: “Draft Card Descriptions for Clarity”

Draft Card Descriptions for Clarity

Context: You are preparing a hybrid card sort and need clear, non-jargon card text.  
Specific Info: The cards represent internal tools, features, and settings currently labelled by internal teams.  
Intent: Rewrite items in plain, user-facing language for external testers.  
Response Format: Return a table with: Original Label, Revised Label, Short Description.

Highlight terms likely to generate confusion or ambiguity.

Prompt Template 7: “Create a Pilot Plan for Remote Card Sorting”

Create a Pilot Plan for Remote Card Sorting

Context: You're planning to conduct unmoderated card sorts remotely using OptimalSort or a similar tool.  
Specific Info: You’re trialling with 3 users before launching fully.  
Intent: Map out a step-by-step pilot process to validate study clarity, time, and tech environment.  
Response Format: Return a checklist of activities before, during, and after the pilot.

Suggest what participant feedback to prioritise during pilot evaluation.

Prompt Template 8: “Turn Sort Data into Navigation Sketch”

Turn Sort Data into Navigation Sketch

Context: You just completed a card sort analysis for a redesigned retail platform.  
Specific Info: You have five consensus groups and preferred labels from 12 users.  
Intent: Help sketch a draft top-level nav structure using groupings as nav items and aligned sub-sections.  
Response Format: Return a visual outline in text format with nav > sub-nav hierarchy.

Offer one follow-up tip for validating the nav in click tests or tree testing.

Prompt Template 9: “Check for Bias in Card Sorting Plan”

Check for Bias in Card Sorting Plan

Context: You’re preparing a card sort activity at a stakeholder-led workshop.  
Specific Info: Stakeholders pre-selected items and categories based on internal taxonomy.  
Intent: Identify where bias may impact participant behaviour or results.  
Response Format: Provide a bias review checklist with mitigating techniques.

Ask what changes could increase user neutrality in sort behaviour.

Prompt Template 10: “Summarise Insights for Stakeholder Report”

Summarise Insights for Stakeholder Report

Context: You are preparing a deck to share card sort results with design and product stakeholders.  
Specific Info: You ran 10 sessions, identified 4 high-consensus groups, and derived new IA.  
Intent: Write a 1-page summary covering user behaviour, key patterns, and next steps.  
Response Format: Return a structured summary with: Overview, Themes, Recommendations, and Impact.

Suggest a visual or quote to add cred to the stakeholder deck.

Recommended Tools

• OptimalSort – Card Sorting Tool
• UserZoom – Remote UX Research Platform
• UserTesting – Think-Aloud Video Analytics
• CardSort App (simple open/closed utility)

Learn More

• NNGroup: UX Research & Design Articles
• Interaction Design Foundation – Topics
• Google Design Sprint Kit