What Is RICE Scoring?
RICE scoring is a prioritization method that ranks ideas by four factors: Reach, Impact, Confidence, and Effort. You multiply Reach, Impact, and Confidence, then divide by Effort, so the score reflects total value per unit of work. The highest scores move to the top of the backlog.
RICE earns its keep when your candidate experiments touch very different audience sizes. By pricing in Reach and dividing by Effort, it stops a flashy idea that helps a handful of users from outranking a quieter one that helps thousands.
The RICE formula
RICE turns four estimates into one number: (Reach × Impact × Confidence) ÷ Effort.
- Reach: how many people or events the change affects in a fixed period, such as users per quarter. Use a real count, not a feeling.
- Impact: how much it moves the metric per person. Teams usually fix a scale, for example 3 for massive, 2 for high, 1 for medium, 0.5 for low, 0.25 for minimal.
- Confidence: a percentage that discounts the estimate when evidence is thin. 100 percent for solid data, 80 percent for some signal, 50 percent for a hunch.
- Effort: the total work to ship and measure, counted in person-months or person-weeks across design, build, and analysis.
The output is value per unit of effort. Like ICE, the number only means something as a relative ranking, so keep your scales constant across the backlog.
How to score an experiment with RICE
Estimate fast, but anchor Reach and Effort on real numbers.
R. Reach
Count how many users or events the change touches in a set window. Pull it from analytics where you can. A pricing-page test reaches every visitor; a power-user feature reaches a slice.
I. Impact
Rate how much the metric moves per affected person using a fixed scale. Reserve the top of the scale for changes you genuinely expect to be transformative, not merely nice.
C. Confidence
Discount the estimate by how much evidence backs it. Prior wins and clear data sit near 100 percent; a guess sits at 50 percent. This is where wishful thinking does the most damage.
E. Effort
Total the person-months to ship and analyze, then divide by it. Because Effort is a divisor, underestimating it inflates the score, so budget for instrumentation and analysis, not only the build.
Worked example
Three candidates scored with RICE. The trust-logo test wins on huge reach and tiny effort, even though its per-person impact is the lowest of the three.
| Experiment | Reach (qtr) | Impact | Confidence | Effort (pm) | RICE |
|---|---|---|---|---|---|
| Pricing page trust logos | 5,000 | 0.5 | 100% | 1 | 2,500 |
| Onboarding checklist | 2,000 | 2 | 80% | 4 | 800 |
| Power-user dashboard | 300 | 3 | 50% | 6 | 75 |
Read by gut, the power-user dashboard looks strongest because its impact is a 3. RICE reshuffles it to last: low reach and high effort sink the score. That reshuffle is the whole point.
RICE vs ICE: when to use which
RICE and ICE are close cousins, and the difference comes down to two axes.
- ICE scores Impact, Confidence, and Ease, each 1 to 10. It is fast and unit-free, and it works well when candidates affect similar audience sizes.
- RICE adds Reach and swaps Ease for Effort. The swap matters: Ease is a thing you want more of, so it multiplies, while Effort is a cost, so it divides. That is why RICE scores look nothing like ICE scores.
The practical rule: start with ICE for speed, and graduate to RICE when reach differences between ideas start distorting your ranking. Both choose the next test. ROTI, the return-on-time review lens, grades the last one and feeds the lesson back.
Common mistakes
- Mixed time windows. Reach for one idea measured per month and another per quarter makes the ranking meaningless. Pick one window and hold it.
- Confidence as hope. A 90 percent confidence with no evidence behind it is the fastest way to a misleading queue. Tie the percentage to data.
- Effort optimism. The planning fallacy lives in the divisor. A halved Effort estimate doubles the score, so pad for the parts teams forget.
- Treating the score as a forecast. RICE ranks bets; it does not predict outcomes. Re-score when you learn something new.
Frequently asked questions
What does RICE stand for?
RICE stands for Reach, Impact, Confidence, and Effort. You multiply Reach, Impact, and Confidence, then divide by Effort, so the score represents the expected value of an idea per unit of work.
What is the RICE scoring formula?
The formula is (Reach times Impact times Confidence) divided by Effort. Reach is a count of affected users or events, Impact is a fixed per-person scale, Confidence is a percentage, and Effort is the total work in person-months. The result ranks ideas relative to each other.
What is the difference between RICE and ICE?
ICE uses three factors, Impact, Confidence, and Ease, on a 1 to 10 scale, and is faster. RICE adds Reach and replaces Ease with Effort, dividing by it instead of multiplying. RICE is the better choice when candidate ideas reach very different numbers of users.
Who created RICE scoring?
RICE was developed by the product team at Intercom, who published it as a way to bring consistency to their roadmap decisions. It has since become a common prioritization framework for product and growth teams.
Related terms
Go deeper
- ICE Score Prioritization Tool
- Experiment Prioritization Guide
- ICE Scoring: The Complete Guide
- Growth Experimentation: The 2026 Ultimate Guide
About GrowthLab
GrowthLab is an experiment management tool where AI drafts the hypotheses, ICE and ROTI prioritize them, and every learning compounds into the next batch.
