Enter build cost and post-launch impact
Developer-days spent, adoption rate, retention lift, conversion lift, and monthly revenue impact are each entered.
POST-LAUNCH FEATURE ROI
Feature ROI
Enter a feature's build cost and post-launch impact numbers and get a calculated ROI score comparing effort to actual return.
- 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 calculate an effort-adjusted ROI score
An impact index from adoption, retention, and conversion lift is discounted by how long the feature takes to pay back its estimated build cost.
Get a payback period and next step
The result shows estimated build cost, payback period in months, and whether to invest further, iterate, or reconsider the feature.
Continue learning: What affects MVP development cost after launch · Which MVP metrics matter?
Frequently asked questions
How is build cost calculated?
It's developer-days spent multiplied by an assumed day rate, giving a rough dollar figure comparable to the feature's revenue impact. This is an approximation for prioritization purposes, not an exact accounting figure.
Why does payback period affect the ROI score so much?
A feature with strong adoption but a 24-month payback period is a much weaker bet than one with similar adoption and a 1-month payback. Discounting the impact index by payback time keeps the score reflecting real return on investment, not just raw usage numbers.
What if a feature has good adoption but no measurable revenue impact yet?
The tool still credits the adoption and retention/conversion lift components, but the ROI score will be capped lower until a revenue link is measurable — this reflects genuine uncertainty rather than assuming revenue impact that hasn't been observed yet.
Is this a replacement for a full product analytics attribution model?
No. It's a fast, manual check using your own estimates. A dedicated attribution or product analytics platform can isolate a feature's causal impact more precisely using experiment data.
How We Compare
| Feature | MVPHub | Amplitude | Productboard |
|---|---|---|---|
| Quick single-feature ROI and payback check | Included | Limited | Limited |
| Effort-adjusted scoring (build cost vs. impact) | Included | Not included | Not included |
| Automated feature analytics and causal attribution | Not included | Included | Limited |
| Roadmap prioritization and stakeholder voting | Not included | Not included | Included |
Amplitude and Productboard track feature usage and roadmap prioritization automatically once integrated. MVPHub gives a fast, manual ROI check for one feature using estimates you already have.
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