Prioritize with confidence, not guesswork

RICE scoring is a prioritization framework developed at Intercom to help product teams make objective decisions about which features to build next. The acronym stands for Reach, Impact, Confidence, and Effort—four factors that combine to produce a single score for comparing initiatives. Unlike gut-feel prioritization or HiPPO (Highest Paid Person's Opinion) methods, RICE forces teams to quantify assumptions and surface the trade-offs between opportunity size and implementation cost.

The formula multiplies Reach (how many people are affected) by Impact (how much each person benefits) and Confidence (how sure you are about your estimates), then divides by Effort (how long it takes to build). This creates a ratio that naturally favors high-impact, low-effort work while penalizing speculative bets with uncertain outcomes. RICE scores make it easier to defend roadmap choices to stakeholders and help teams avoid over-investing in pet projects that deliver marginal value.

Reach should reflect the number of people who will encounter or benefit from the feature in a given time period—typically per quarter or per month. For a new onboarding flow, you might count monthly signups; for an existing feature improvement, you would look at active users of that feature. Avoid inflating reach by counting your entire user base unless the change truly affects everyone. Pull actual usage data from analytics rather than guessing.

This scale forces you to compare the depth of benefit. A cosmetic tweak might be minimal; a feature that removes a critical pain point or enables a new workflow would be high or massive. The standardized scale ensures consistency when comparing different types of initiatives.

Confidence accounts for uncertainty in your reach and impact estimates. If you have strong customer research and usage data, confidence is high (80-100%); if you are extrapolating from a handful of conversations or making educated guesses, lower it (30-50%). This prevents overconfident teams from prioritizing speculative bets over validated opportunities.

Count the total team time: if two engineers spend six weeks each, that is three person-months. Include design, QA, and deployment time. The calculator supports multiple effort units—hours, days, weeks, months—so you can enter what feels natural and it will normalize the score to person-months. Be realistic: teams often underestimate effort by 30–50%, so pad conservatively or use historical velocity to calibrate.

RICE scores are most useful when comparing initiatives of similar scope or domain. A score of 450 for a mobile app feature and a score of 380 for a backend platform upgrade tells you which has better ROI, but only if you trust the inputs. Resist the temptation to manipulate scores to justify a desired outcome—gaming the system undermines the framework's value. Instead, run sensitivity checks: if you lower confidence by 20% or increase effort by one person-month, does the ranking change? If a small adjustment flips the order, you need better data.

When prioritizing across product areas or customer segments, use consistent time periods for reach (all quarterly or all monthly) and the same impact scale definitions. Document your scoring rubric so that "high impact" means the same thing for sales features as it does for retention features. Some teams run RICE workshops where cross-functional stakeholders debate the inputs together, which surfaces hidden assumptions and builds buy-in for the final roadmap.