Describe your content and categories
Enter total content/feature items, how many categories they naturally group into, and the size of the largest category.
INFORMATION-ARCHITECTURE RECOMMENDATION
Info Arc
Enter your content/feature item count and how many distinct categories they naturally group into, and get a flat-vs-nested information-architecture recommendation.
- Uses your inputs in a transparent calculation
- Instant result with practical next steps
- No signup required
Planning guidance only. Validate important decisions with customer evidence and your delivery team.
YOUR INPUTS
Build your result
Complete every field. The result updates only when you choose Calculate.
How it works
We apply IA threshold rules
Real rules of thumb — a small, evenly distributed set stays flat, a crowded category or a large total pushes toward nested sub-categories — decide the recommendation.
Get a structure and a depth/breadth score
You get a named structure recommendation (flat, nested, or mixed) plus a 0-100 score reflecting item count, category load, and item-to-category ratio.
Continue learning: MVP design: features, flows, or screens first? · MVP navigation design: keeping it simple enough
Frequently asked questions
Does Info Arc parse my actual content or sitemap?
No. Info Arc recommends a structure using threshold rules applied to the item and category counts you enter. It does not parse an uploaded sitemap, CMS export, or product content, and does not run a real AI/LLM generation step.
How is Info Arc different from Nav Sketch?
Info Arc organizes content and feature items into categories and decides how flat or nested that organization should be — it is about grouping and labeling. Nav Sketch recommends the navigation pattern (tab bar, sidebar, hybrid) for moving between a product's interactive features and workflows — it is about wayfinding. Use Info Arc to decide how your content is categorized; use Nav Sketch to decide how users get around your app.
Why does one crowded category matter more than the average?
Users scan the largest category, not the average one — a category with 15+ items feels overwhelming even if every other category has 3. The score weights the largest-category size directly for that reason.
What if my categories are very uneven in size?
Uneven categories usually mean one or two topics deserve their own top-level category instead of being lumped together, or one large category needs internal sub-grouping — the next-steps list will flag whichever situation your numbers show.
Should I trust this over user testing?
No — this is a fast structural starting point based on counts, not a substitute for a card sort or tree test with real users, which remains the most reliable way to validate an information architecture.
How We Compare
| Feature | MVPHub | Miro | Figma |
|---|---|---|---|
| Flat-vs-nested recommendation from threshold rules | Included | Not included | Not included |
| Depth/breadth scoring | Included | Not included | Not included |
| Visual card-sorting and grouping canvas | Not included | Included | Limited |
| Design the actual navigation/menu UI | Not included | Not included | Included |
Miro is where teams run a visual card sort to group content by hand, and Figma is where the resulting menus and pages get designed. Info Arc runs before either — a quick numeric read on whether your content set needs a nested structure at all, before you invest time in a full card-sorting session.
Related tools
Embed this tool
Add this tool to your site with the canonical iframe below. It remains hosted and maintained by MVPHub.