Card Sorting and Information Architecture for Navigation Redesign
Card sorting planning and analysis to restructure the information architecture of a digital product.
Use card sorting techniques to redesign the navigation structure of a product, based on the actual mental models of users rather than team assumptions.
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Prompt objective
Use card sorting techniques to redesign the navigation structure of a product, based on the actual mental models of users rather than team assumptions.
Real use case
An e-commerce company is restructuring its app navigation which currently has 47 categories in the main menu. Internal tests show that 60% of users rely only on search because they cannot find what they need in navigation. They need to run card sorting with 300 customers to redefine the taxonomy.
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Prompt
Plan and analyze a card sorting study to restructure the navigation of [PRODUCT NAME].\\\\\\\\n\\\\\\\\nCurrent structure: [NUMBER] navigation items organized in [NUMBER] levels.\\\\\\\\nIdentified problem: [NAVIGATION PROBLEM DESCRIPTION].\\\\\\\\n\\\\\\\\n**1) Preparation:**\\\\\\\\n- Complete inventory of content/functionality items (list all cards)\\\\\\\\n- Criteria for including/excluding items from the study\\\\\\\\n- Card sorting type: open, closed, or hybrid (justify your choice)\\\\\\\\n- Card labels: how to write without bias\\\\\\\\n- Ideal number of cards (recommended maximum: 40-60)\\\\\\\\n\\\\\\\\n**2) Execution:**\\\\\\\\n- Recommended tool for online card sorting (Optimal Workshop, UserZoom)\\\\\\\\n- Profile and number of participants per segment\\\\\\\\n- Instructions for participants (ready-to-use text)\\\\\\\\n- Estimated duration per session\\\\\\\\n- Pilot test with 5 people before full launch\\\\\\\\n\\\\\\\\n**3) Quantitative Analysis:**\\\\\\\\n- Similarity matrix (which cards are grouped together >60% of the time)\\\\\\\\n- Dendrogram (hierarchical cluster analysis)\\\\\\\\n- Emerging categories (open) or agreement rate (closed)\\\\\\\\n- Labels suggested by participants vs. team labels\\\\\\\\n- Problematic items (low grouping agreement)\\\\\\\\n\\\\\\\\n**4) Proposed New Architecture:**\\\\\\\\n- Navigation structure with maximum [NUMBER] levels\\\\\\\\n- Main menu: maximum [NUMBER] top-level categories\\\\\\\\n- Subcategories and groupings based on clusters\\\\\\\\n- Breadcrumb strategy\\\\\\\\n- Cross-links for items belonging to multiple categories\\\\\\\\n\\\\\\\\n**5) Validation:**\\\\\\\\n- Tree testing: plan to validate the new structure\\\\\\\\n- [NUMBER] location tasks to measure findability\\\\\\\\n- Success criteria (direct success rate >70%)\\\\\\\\n- Complementary first-click testing\\\\\\\\n\\\\\\\\n**6) Implementation:**\\\\\\\\n- Prioritization: which changes to apply first\\\\\\\\n- Required redirects (SEO)\\\\\\\\n- Communicating the change to users\\\\\\\\n- Post-launch tracking metrics\\\\\\\\n\\\\\\\\nAudience context: primarily [DEMOGRAPHIC PROFILE] and [PERCENTAGE]% access via mobile.
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