Rate four evidence sources
User signal, quantitative data, external precedent, and stakeholder alignment are each rated 0-3.
EVIDENCE STRENGTH CHECK
Feature Confidence Rater
Score the evidence behind a feature recommendation across user signal, data, precedent, and stakeholder alignment to see how confident the call really is.
- 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
Get a confidence score
The four ratings sum to a 0-100 confidence score with a low/moderate/high label.
See your weakest input
The result highlights whichever input is dragging the score down the most, so you know what to strengthen first.
Continue learning: MVP feature prioritization
Frequently asked questions
Is this a substitute for user research?
No — it's a way to make explicit how much real evidence backs a recommendation, so weak recommendations don't get built with the same confidence as well-validated ones.
What counts as strong data support?
A measured, sized problem — for example a funnel step with a quantified drop-off rate, not just a general sense that something is off.
Can a feature with low confidence still be worth building?
Yes, for strategic or defensive reasons — but the score is a flag to make that judgment call consciously rather than by default.
How is the score calculated?
Each of the four inputs is rated 0-3; the sum out of 12 is scaled to a 0-100 score. It's simple, transparent arithmetic, not a hidden model.
How We Compare
| Feature | MVPHub | Notion | Google Sheets |
|---|---|---|---|
| Structured evidence framework | Included | Limited | Limited |
| Instant weighted score | Included | Not included | Limited |
| Flags weakest evidence input | Included | Not included | Not included |
| No setup required | Included | Limited | Included |
Notion and Sheets can track evidence in a table, but scoring and weakest-input detection have to be built by hand each time.
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