Feature Prioritization RICE Score
Calculate RICE scores for feature prioritization. Compare Reach, Impact, Confidence, and Effort across multiple features to optimize your product roadmap.
Formula
RICE Score = (Reach × Impact × Confidence%) / Effort
Reach is users affected per quarter. Impact is 0.25-3 scale. Confidence is 0-100% certainty. Effort is person-weeks. Higher scores indicate higher priority features.
Worked Examples
Example 1: E-commerce Search Improvement
Problem:Reach: 50,000 users/quarter (all searchers). Impact: 2 (High - doubles conversion). Confidence: 70% (A/B test suggested). Effort: 4 person-weeks.
Solution:RICE = (Reach × Impact × Confidence) / Effort RICE = (50,000 × 2 × 0.70) / 4 RICE = 70,000 / 4 RICE = 17,500 This is a very high score because: - Large reach (50K users) - High impact (2x conversion) - Decent confidence (70%) - Moderate effort (4 weeks) Recommendation: High priority, schedule for next sprint.
Result:RICE: 17,500 | Critical Priority | Ship next sprint
Example 2: Mobile Push Notifications
Problem:Reach: 20,000 (mobile users). Impact: 0.5 (Low - minor engagement bump). Confidence: 80%. Effort: 2 person-weeks.
Solution:RICE = (20,000 × 0.5 × 0.80) / 2 RICE = 8,000 / 2 RICE = 4,000 Moderate score because: - Good reach - Low impact (only 0.5) - High confidence - Low effort Effort-adjusted: Good ROI despite low impact. Consider if mobile engagement is strategic priority.
Result:RICE: 4,000 | High Priority | Good effort-to-impact ratio
Example 3: Enterprise SSO Integration
Problem:Reach: 500 (enterprise accounts). Impact: 3 (Massive - required for deals). Confidence: 90%. Effort: 6 person-weeks.
Solution:RICE = (500 × 3 × 0.90) / 6 RICE = 1,350 / 6 RICE = 225 Low score despite massive impact because: - Small reach (only 500 accounts) - High effort (6 weeks) BUT: Strategic consideration - May unlock $500K ARR in blocked deals - Revenue per account high RICE undervalues revenue-driving features. Adjust with business impact multiplier or use separate enterprise prioritization.
Result:RICE: 225 | Low Score BUT strategic | Consider revenue impact separately
Frequently Asked Questions
What is the RICE scoring model?
RICE (Reach, Impact, Confidence, Effort) is a prioritization framework developed by Intercom. Score = (Reach × Impact × Confidence%) / Effort. Higher scores indicate features worth building first.
How do I estimate Reach?
Reach is users/customers affected per time period (usually quarter). Use analytics: DAU, feature usage rates, funnel data. For new features, estimate based on similar features or target segment size.
What are the Impact levels?
Standard scale: 3 = Massive (10x improvement), 2 = High (2-5x), 1 = Medium (notable), 0.5 = Low (minor), 0.25 = Minimal. Be honest - most features are 0.5-1, not 2-3.
How do I assess Confidence?
Confidence reflects certainty in Reach/Impact estimates. 100% = data-backed, 80% = strong evidence, 50% = gut feeling, 20% = speculation. Use lower confidence for new markets or innovative features.
What units should Effort use?
Effort is person-weeks or story points. Use consistent units across features. Include design, development, testing, and launch effort. Round to whole numbers (1-10 scale common).
What's a good RICE score?
Depends on your scale. Compare relative scores within your feature list. Scores vary widely by Reach (company size matters). Focus on ranking rather than absolute numbers.
How does RICE compare to other frameworks?
RICE is more quantitative than MoSCoW or Kano. ICE (similar but no Reach) is simpler. WSJF (Weighted Shortest Job First) is SAFe's version. RICE suits product teams with usage data.
What are RICE limitations?
Limitations: subjective inputs, doesn't capture dependencies, ignores strategic fit, and can favor incremental over transformational. Use alongside qualitative judgment and strategy alignment.
Should I use RICE for all decisions?
Best for: feature prioritization, roadmap planning, comparing similar-sized initiatives. Less suited for: bug fixes (just fix them), technical debt, or binary decisions (build vs not).
How often should I recalculate RICE?
Recalculate when: new data available, scope changes, confidence increases (after research), or quarterly planning. Update Effort if implementation reveals complexity.