Information Architecture Card Sort Plan

You are an information architecture specialist who has restructured websites and apps serving millions of users based on rigorous card sorting research.

Product: [WHAT YOUR PRODUCT OR WEBSITE IS]
Content to organize: [DESCRIBE THE TYPE OF CONTENT - pages, features, settings, products]
Current structure: [HOW THINGS ARE ORGANIZED NOW]
Problem: [WHY THE CURRENT STRUCTURE ISN'T WORKING]
Participant pool: [WHO WILL DO THE CARD SORT]

Create a complete card sorting research plan:

**1. Study Design**
- Sort type decision and rationale:
  - Open sort: participants create their own categories (discovery)
  - Closed sort: participants sort into pre-defined categories (validation)
  - Hybrid sort: pre-defined + option to create new categories
- Number of cards: 30-60 recommended (list each card)
- Card labels: clear, jargon-free, consistent detail level
- Moderated vs unmoderated decision
- Participant count: 15-30 for statistical significance

**2. Card List**
- List every card with:
  - Card label (what participants see)
  - Card description (optional tooltip for ambiguous items)
  - Current location in the product
  - Category hypothesis (where you think it should go)
- Cards should represent:
  - Pages or sections
  - Features or tools
  - Settings or preferences
  - Content types or topics
- Exclude: duplicate concepts, overly technical items

**3. Participant Criteria**
- Recruitment screener questions
- Experience level targets (mix of new and experienced users)
- Demographic distribution
- Incentive recommendation
- Session length estimate (15-30 min for unmoderated)

**4. Facilitator Script (for moderated)**
- Introduction and purpose explanation
- Think-aloud instructions
- What to observe during sorting
- Probing questions ("Why did you put these together?")
- What to do when participants are stuck
- Closing questions about difficulty and confidence

**5. Analysis Method**
- Similarity matrix: which cards were grouped together most often
- Dendrogram: hierarchical clustering visualization
- Category analysis: what names participants created
- Agreement score: how much consensus exists
- Outlier analysis: items nobody agreed on
- Cross-tabulation: differences between user segments

**6. From Results to Navigation**
- How to interpret clusters as navigation categories
- Category naming: use participant language, not internal terms
- Handling disputed items (cards that were split across categories)
- Primary vs secondary placement decisions
- Validating results with tree testing

**7. Tree Testing Follow-Up**
- Create proposed tree structure from card sort results
- Write 5-10 findability tasks
- Success metrics: directness, time, success rate
- Iterate: adjust tree based on tree test results

**8. Deliverables**
- Similarity matrix heatmap
- Recommended navigation structure (3-level hierarchy)
- Category labels with confidence levels
- Items requiring further research
- Before/after comparison
- Implementation recommendations

Provide the actual card list with 30-50 items specific to the described product. Include analysis interpretation guidelines.