RICE Score Calculator

RICE Score Calculator

Add your features or ideas below. RICE scores are calculated automatically and sorted by priority.

About the RICE Framework

RICE is a prioritization framework developed by Intercom to help product teams make objective decisions about what to build next. Instead of relying on gut feelings or the loudest voice in the room, RICE provides a quantitative score to rank features.

Formula:

RICE Score = (Reach × Impact × Confidence) / Effort

How to Use RICE:

1. List your features – Add all ideas you're considering
2. Estimate each factor – Be honest, especially with Confidence
3. Compare scores – Higher scores = higher priority
4. Review and adjust – Use RICE as input, not the final decision

Tips for Better Estimates:

• Use the same time period for all Reach estimates (e.g., all monthly)
• Lower your Confidence if you're guessing – it's better to be conservative
• Include all effort: design, development, testing, documentation
• Revisit scores as you learn more about each feature

FAQ

What is the RICE framework?

RICE is a prioritization scoring model that evaluates ideas by four factors: Reach (how many users it affects), Impact (how much it improves their experience), Confidence (how sure you are about the estimates), and Effort (how much work it requires in person-months). The score is calculated as (Reach × Impact × Confidence%) / Effort. It was developed by the product team at Intercom in 2016.

What is a good RICE score?

There is no universal "good" score — it depends entirely on your context. A company with 1 million monthly users will produce much larger scores than a startup with 1,000 users. Focus on comparing features against each other within the same scoring session, not against an absolute benchmark.

Should I always build the highest-scoring feature first?

Not necessarily. RICE is a decision-support tool, not a decision-maker. Consider dependencies, strategic importance, team capacity, and technical constraints alongside RICE scores. If two features score within 10–15% of each other, treat them as effectively tied and use judgment to decide.

How do I estimate Impact?

Use a consistent scale: 3 = game-changer (transforms the experience or removes a critical blocker), 2 = significant improvement users will clearly notice, 1 = noticeable quality-of-life upgrade, 0.5 = minor improvement, 0.25 = barely noticeable. Think about what changes for the user, not what changes in the code.

What if I have no data for Reach?

Use the best proxy available: support ticket volume, survey responses, feature request counts, or the percentage of total users who match the target persona. Then set Confidence to 50% or lower to reflect the uncertainty. Update the estimate as you gather real data.

How is RICE different from ICE scoring?

ICE uses three factors — Impact, Confidence, and Ease — and drops Reach entirely. This means ICE cannot distinguish between a feature that helps 100 users and one that helps 100,000 if per-person impact is the same. RICE's inclusion of Reach makes it more suitable for products with varied audience sizes per feature.

What should Effort include?

Include all work needed to ship: design, development, testing, QA, documentation, and deployment. One person-month means one person working full-time for one month. A feature needing a designer for 2 weeks and a developer for 6 weeks is roughly 2 person-months.

How do I prevent people from gaming RICE scores?

The main defense is honest Confidence scores. If someone inflates Reach or Impact, their Confidence should be lower to reflect the speculation. Calibration sessions — where the team reviews and challenges estimates — also help. When scores are visible to everyone, unreasonable estimates get questioned.

Can RICE be used for bug prioritization?

RICE works less well for bugs because Impact is harder to quantify and urgent bugs bypass prioritization entirely. For non-critical bugs, RICE can help rank them alongside features, but most teams handle critical bugs through severity-based triage instead.

How often should I re-score features?

Score new features as they're proposed. Re-evaluate the full backlog quarterly, or whenever significant new data arrives (user research, experiment results, scope changes). Scores older than 6 months should be considered stale.

For a deeper dive into the framework with worked examples and comparisons to other prioritization methods, see our complete guide to the RICE framework.

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RICE Score Calculator FAQ