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Information architecture that actually works. Navigation, taxonomy, hierarchy, search, and labeling, framed around the principle that if users can't find it, it doesn't exist.
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SOC 職業分類に基づく
WCAG 2.1/2.2 guidelines, ARIA patterns, and inclusive design principles. Use when auditing accessibility, implementing ARIA, reviewing color contrast, or designing for screen readers, keyboard users, and cognitive accessibility.
Opinionated design critique framework grounded in business outcomes, named principles, and specific actionable feedback. Use when reviewing designs, running critique sessions, or giving feedback that actually improves the work.
Deceptive patterns (dark patterns), ethical design frameworks, persuasive vs. manipulative design, GDPR/consent UX. Use when reviewing designs for manipulation, designing consent flows, or evaluating ethical implications of design decisions.
Usability heuristics for catching real problems in interfaces, not generating busywork. Nielsen's 10 and Shneiderman's Golden Rules, reframed around business outcomes with practical severity scoring.
Design process philosophy and frameworks. When to use JTBD, Design Sprints, Double Diamond, IDEO. How to run outcome-driven design, effective critique, and recognize when process is theater. Use when planning design work, structuring discovery, or choosing the right level of rigor for the problem.
Design systems architecture - tokens, components, documentation, governance. Use when building or scaling a design system, defining component APIs, establishing token architecture, or creating contribution guidelines.
| name | information-architecture |
| description | Information architecture that actually works. Navigation, taxonomy, hierarchy, search, and labeling, framed around the principle that if users can't find it, it doesn't exist. |
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IA is the invisible work that determines whether your product feels intuitive or confusing. You'll never hear a user say "the information architecture is great." But you'll absolutely hear "I can't find anything on this site." That's an IA problem. And "I can't find it" is a conversion problem.
Bad IA is the root cause of more product failures than bad visual design. You can have the most beautiful interface in the world, but if users can't find what they're looking for, none of it matters.
All three have to align. Most IA failures happen because the team designs for content and context but ignores users. They organize things in a way that makes sense to the business, not to the person trying to use the product.
The best navigation is invisible. Users shouldn't be thinking about navigation at all. They should be thinking about their task, their content, their goal. If they're thinking about how to navigate, you've already failed.
If your navigation uses words your team invented instead of words your users use, you're designing for yourselves. Card sort it. It takes 2 hours and saves 6 months of confusion.
Flat is almost always better. Every click you add to find something is a user you lose. Research consistently shows that users prefer broader, shallower menus over narrow, deep ones.
But there's a breaking point. If you have 200+ items in a flat list, you don't need deeper hierarchy. You need faceted filtering. Let users narrow down by multiple dimensions simultaneously instead of making them drill through categories.
The exception: truly hierarchical content where the relationships between levels carry meaning (like a file system or org chart). But for most products, especially e-commerce and content sites, flat with good filtering wins.
For any product with more than about 50 items of content, search isn't a nice-to-have. It's primary navigation for most users.
This is the thing teams consistently underinvest in. They spend months on navigation menus that 40% of users will ignore in favor of the search bar. Then they ship a search that returns garbage results and wonder why engagement is low.
If your search is broken, your IA is broken. Period.
What good search looks like:
Search is also a goldmine for IA research. Your search logs tell you exactly what users are looking for and what words they use. If you're not reviewing search logs quarterly, you're ignoring your best source of IA insight.
| Method | What It Reveals | When to Use |
|---|---|---|
| Card sorting (open) | How users naturally group content | Early, when discovering user mental models |
| Card sorting (closed) | Whether your categories make sense to users | After defining categories |
| Tree testing | Whether users can find content in your hierarchy | After defining structure, before building nav |
| First-click testing | Where users expect to find things | Evaluating nav labels and placement |
Most teams skip IA research because it feels slow. Then they spend 6 months building navigation that doesn't work and redesigning it. The research is faster.
An open card sort takes half a day to set up, a few days to collect responses, and an hour to analyze. A tree test is even faster. Compare that to the cost of rebuilding your navigation after launch because users can't find anything.
A practical approach:
Total time: about 2 weeks. Total cost of skipping it: months of iteration post-launch and lost conversions in the meantime.
laws-of-ux - Cognitive principles (Chunking, Miller's Law, Mental Model)interaction-patterns - Navigation pattern selection