The tool
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Inputs (per feature, repeatable rows):
- Feature name (short text)
- Reach (number): how many users affected per time period
- Impact (selector): 3 = massive, 2 = high, 1 = medium, 0.5 = low, 0.25 = minimal
- Confidence (percentage): 100% = high, 80% = medium, 50% = low
- Effort (number): person-months
Output: A scoring table with a calculated RICE score per row, sorted highest to lowest. Formula: (Reach x Impact x Confidence) / Effort. Exportable as a table.
Behavior: Calculates live in-browser as values change, no login.
Prioritization is where roadmaps get political
Without a shared method, the loudest voice wins the roadmap. The feature with an executive behind it jumps the queue, and the quiet, high-value work waits. RICE exists to replace that with a number everyone can see and argue about on the same terms.
It ranks features by expected value per unit of effort: multiply Reach, Impact, and Confidence, then divide by Effort. A wide-reach, high-impact, low-effort feature rises; a risky, expensive one sinks. The point is not false precision, it is a visible basis for the call. For the wider toolkit, the guide on how to prioritize a product backlog and the action priority matrix cover when RICE fits and when a simpler lens is better.
How it works
1. List your features. Add a row for each candidate.
2. Score the four factors. Enter Reach, Impact, Confidence, and Effort.
3. Read the ranking. The calculator sorts by RICE score automatically.
4. Export and discuss. Bring the ranked table to your roadmap review.
A worked example
Two features compete: a redesigned onboarding flow and a niche export option. Onboarding reaches every new user (high Reach), lifts activation (Impact 2), but you are only fairly sure (Confidence 80%) and it is three person-months. The export touches few users (low Reach), is certain (100%), and takes one month. RICE makes the trade explicit: onboarding's score clears the export's despite the higher effort, because reach and impact compound. Where RICE underrates a cheap, certain win, that is your cue to sanity-check, not to abandon the method. Keeping that discipline is also how teams prevent scope creep once the roadmap is set.
From roadmap to design, with Figr
Once RICE tells you what to build next, Figr helps you design it. Figr is an AI product designer that reads your product context, screens, flows, design system, and docs, then reasons through the UX and produces Figma-ready design on your system. So the feature you just prioritized moves into design without losing the context that justified it. For a faster either-or call on scope, pair this with the MoSCoW matrix, and spec the winner with the PRD template generator.
Who this is for
This is for product managers making roadmap calls on a real product, where effort estimates and reach are grounded in something concrete.
What this tool is not
RICE is a lens, not an oracle. The scores are only as honest as the inputs, and a confident-looking number can hide a wild guess on Effort. Use it to structure the debate, not to end it. This is also a free, standalone calculator, not a Figr product feature.
FAQ
Is the RICE calculator free?
Yes, free and no sign-up.
What is the RICE formula?
(Reach x Impact x Confidence) / Effort. The result is the RICE score; higher ranks higher.
What units should I use?
Reach as users per time period, Impact on the standard 0.25 to 3 scale, Confidence as a percentage, and Effort in person-months.
Can I compare many features at once?
Yes. Add a row per feature and the tool ranks them together.
How is this different from Figr the product?
This is a free calculator. Figr the product is an AI product designer that turns product context into UX decisions and Figma-ready design.