Checklist against expected table capabilities
Each capability you mark present or missing is weighted by how much it matters at your stated row count — sorting and filtering matter more as row counts grow.
Free MVP data table tool
TableUX
Check a SaaS data table against the capabilities users expect — filtering, sorting, bulk actions, responsiveness, readability — and get a prioritized fix list.
- Calculated instantly from your inputs
- No signup or data submission
- A focused next step for MVP planning
Your entries remain in this browser session and are not sent to MVPHub.
Your inputs
Describe your data table
List one capability per line as Capability | present (yes/no). Include the table capabilities relevant to your product.
Your calculated result
Your result
0/100
Planning score
Recommended next actions
How it works
Row-count-aware scoring
A table with hundreds of rows and no filtering scores worse than the same gap on a 20-row table, since users are far more likely to need help finding a specific row.
Prioritized fix list
Missing capabilities are ranked by expected user impact so you know what to build first rather than tackling every gap at once.
Frequently asked questions
What if my table only ever has a handful of rows?
The row-count weighting reduces the penalty for missing filtering/sorting on small tables — those capabilities matter far less below roughly 20-30 rows.
Does this replace a full accessibility audit?
No — this focuses on data-table interaction patterns (sort/filter/bulk/responsive), not full WCAG compliance. Pair it with a dedicated accessibility review for compliance-critical products.
Should every table have every capability?
No — a simple reference table may never need bulk actions. Only mark a capability relevant if your users would plausibly want it; leave irrelevant ones out of the list entirely.
How is this different from a general UX audit?
TableUX is narrowly scoped to the data-table pattern itself, not the whole product, so it gives a faster and more specific result for this one component.
How we compare
| Capability | MVPHub | Copying a competitor's table layout | A general-purpose AI assistant |
|---|---|---|---|
| Weighs gaps by your actual row count | ✓ | × | — |
| Produces a prioritized fix list | ✓ | × | — |
| Reflects your specific product context | ✓ | × | — |
| Instant, no design engagement required | ✓ | ✓ | ✓ |
MVPHub applies a transparent, row-count-aware checklist to your own table. Copying a competitor risks importing patterns that don't fit your data; a general AI assistant lacks a consistent scoring method.