RICE Calculator - Prioritise Your Product Decisions Easily
Calculate RICE scores for product prioritization using Reach, Impact, Confidence, and Effort to make data-driven decisions.
What is RICE Calculator?
A RICE calculator is a free tool for Product Managers that helps you make data-driven product prioritisation decisions by scoring your features objectively.
Input four values: Reach, Impact, Confidence, and Effort, and instantly get a numerical score showing which projects deliver the best return on investment.
This calculator helps you:
Compare multiple initiatives side-by-side using quantifiable metrics
Eliminate endless debates about feature priorities
Justify decisions to stakeholders with data-backed scores
Identify quick wins and avoid low-value projects
No complex spreadsheets or manual calculations required, just straightforward scoring that works for any product backlog.
What is RICE Score?
RICE score is a prioritization framework that evaluates features based on four factors: Reach, Impact, Confidence, and Effort. Originally created by Intercom's product team, this scoring model helps product managers make objective prioritization decisions.
The RICE framework balances:
Potential value (reach and impact)
Resource requirements (effort)
Certainty levels (confidence)
This prevents teams from chasing impractical ideas while surfacing high-value opportunities. When every feature has a RICE score, you can rank them objectively and build roadmaps that maximize impact per unit of effort.
The RICE Scoring Formula
The formula for calculating your RICE score is:
RICE Score = (Reach × Impact × Confidence) / Effort
Each component plays a specific role:
Reach: The number of users or customers affected within a specific timeframe
Impact: How much this initiative will benefit each person
Confidence: Your certainty level about the reach, impact, and effort estimates
Effort: The total amount of work required from your team
This formula ensures you're considering both the potential value (reach and impact) and the practical constraints (effort) while accounting for uncertainty through the confidence factor.
How to Use This RICE Calculator
Using this calculator is straightforward. You'll input values for each of the four RICE components, and the tool will automatically compute your final score.
Step-by-Step Guide
1. Enter Reach (scale 1-10):
Think about how many people will encounter or benefit from this feature within a specific period, typically one month or quarter. For example, if 500 users will interact with a new feature per month, you might rate this as a 5.
2. Input Impact (scale 1-10):
Assess how much this initiative will improve the user experience or contribute to your product goals. Consider using this scale:
Minimal impact: 1-2
Low impact: 3-4
Medium impact: 5-6
High impact: 7-8
Massive impact: 9-10
3. Set Confidence (scale 0.01-10):
Rate how confident you are in your reach and impact estimates. High confidence backed by data might be 8-10, medium confidence based on research could be 5-7, and low confidence from assumptions might be 2-4.
4. Define Effort (scale 1-10):
Estimate the total person-months required to complete this initiative. A quick fix might be 1-2, while a complex feature requiring multiple team members could be 8-10.
Once you have entered all four values, the calculator instantly shows your RICE score. You can then compare scores across multiple features to determine which initiatives deserve priority on your product roadmap.
Understanding Each RICE Component
Let's dive deeper into what each component means and how to estimate it accurately.
1. Reach: Who Will Be Affected?
Reach measures the number of people who will experience your initiative within a defined time period. This could be users, customers, transactions, or any relevant metric for your product.
How to estimate reach accurately:
Use analytics data from similar past features
Review user research and feedback volume
Consider your total user base and typical adoption rates
Be specific about the timeframe (monthly, quarterly)
For example, if you are adding a notification feature and 2,000 of your 10,000 monthly active users will receive these notifications, your reach is 2,000 per month.
2. Impact: What's the Benefit?
Impact quantifies how much each person will benefit from this initiative. This is naturally more subjective than reach, but you can ground your estimates in data.
Will it solve a major pain point? (High impact: 7-10)
Does it create a minor improvement? (Medium impact: 4-6)
Is it a nice-to-have enhancement? (Low impact: 1-3)
Product teams often tie impact to specific goals like conversion rate improvements, user retention increases, or support ticket reductions.
If your new onboarding flow historically increases conversion by 25%, that's high impact.
3. Confidence: How Sure Are You?
Confidence is your reality check. It prevents overconfident estimates from skewing your priorities and ensures you account for uncertainty.
Use this confidence scale:
High confidence (8-10): Strong data, customer research, or proven assumptions
Medium confidence (5-7): Some data with reasonable assumptions
Low confidence (1-4): Limited data or pure speculation
If you are building based on customer interviews with 50 users, you might have 8/10 confidence. If it's based on a hunch from one executive, perhaps 3/10 confidence is more appropriate.
4. Effort: Resource Investment
Effort represents the total work required from all team members, typically measured in person-months. One person-month equals one team member working full-time for one month.
Effort estimation tips:
Include design, development, testing, and deployment time
Account for complexity and technical debt
Consider dependencies on other teams
Factor in documentation and training needs
A simple UI update might require 0.5 person-months (rate as 1), while rebuilding your payment system could take 12 person-months (rate as 10).
Why Product Managers Need RICE for Prioritization
Product managers face an endless stream of feature requests, stakeholder demands, and promising ideas. Without a structured prioritization framework, decision-making becomes chaotic and politically charged.
The Problems RICE Solves
1. Removes personal bias:
Everyone has opinions about what to build next. The loudest voice often wins, even when their idea isn't the most valuable. RICE replaces subjective arguments with quantifiable metrics that anyone can evaluate.
2. Enables data-driven decisions:
Instead of saying "I think we should build feature X," you can say "Feature X scores 425 on RICE while Feature Y scores 180." This shifts conversations from opinions to evidence.
3. Improves stakeholder communication:
When executives or sales teams push for their pet projects, you can show them exactly why other initiatives rank higher. The transparent formula makes your reasoning clear and defensible.
4. Balances quick wins with long-term bets:
RICE naturally surfaces opportunities where modest effort yields significant impact. It also helps you identify when a high-effort project is genuinely worth the investment because its reach and impact justify the cost.
When to Use RICE Scoring
You will find this framework most valuable when:
Comparing diverse feature types that seem impossible to rank against each other
Managing a large backlog with dozens of competing priorities
Needing to explain your prioritization logic to non-product stakeholders
Building roadmaps for the next quarter or planning cycle
Evaluating both new features and improvements to existing functionality
RICE Calculator Example in Action
Let's see how this works with a realistic product management scenario. Imagine you're prioritizing three features for your project management software:
Feature A: Team Dashboard
Reach: 8 (80% of teams will use it monthly)
Impact: 7 (significantly improves visibility)
Confidence: 8 (validated through user research)
Effort: 4 (requires frontend and backend work)
RICE Score: (8 × 7 × 8) / 4 = 112
Feature B: Export to CSV
Reach: 4 (40% of users requested it)
Impact: 5 (solves a moderate pain point)
Confidence: 9 (clear user feedback)
Effort: 2 (straightforward implementation)
RICE Score: (4 × 5 × 9) / 2 = 90
Feature C: Advanced Filtering
Reach: 9 (90% of users would benefit)
Impact: 8 (dramatically improves workflow)
Confidence: 5 (based on assumptions)
Effort: 7 (complex technical requirements)
RICE Score: (9 × 8 × 5) / 7 = 51.4
Best Practices for RICE Scoring
Follow these guidelines to get the most value from your RICE prioritization:
1. Score multiple features simultaneously:
RICE works best when comparing relative priorities. Score at least 5-10 initiatives together to see meaningful patterns emerge.
2. Involve your team in estimation:
Don't calculate scores in isolation. Bring together product, engineering, and design to get more accurate effort estimates and diverse perspectives on impact.
3. Update scores as you learn:
Your confidence and effort estimates will improve as you gather more data. Revisit your scores quarterly or when significant new information emerges.
4. Don't overthink the numbers:
You're looking for directional accuracy, not mathematical precision. If Feature A scores 450 and Feature B scores 120, the exact numbers matter less than the clear difference in priority.
5. Combine with other frameworks:
RICE excels at comparing disparate features, but you might use it alongside OKRs for strategic alignment or user story mapping for release planning.
Frequently Asked Questions
How to calculate RICE score?
Multiply Reach, Impact, and Confidence, then divide by Effort: (Reach × Impact × Confidence) / Effort. For example, if a feature reaches 1,000 users with 7 impact, 8 confidence, and 4 effort, the score is (1,000 × 7 × 8) / 4 = 14,000.
What is a good RICE score?
There's no universal "good" score, RICE is comparative, not absolute. A score of 200 might be excellent if your other features score 50-100, but mediocre compared to features scoring 400+. Focus on relative rankings within your specific backlog.
How does RICE scoring work?
RICE scoring works by quantifying four factors: Reach (audience size), Impact (benefit magnitude), Confidence (certainty level), and Effort (resource cost). The formula balances value delivered against resources required, giving you objective scores to compare initiatives and make data-driven prioritization decisions.
What is the formula for RICE?
The RICE formula is: RICE Score = (Reach × Impact × Confidence) / Effort. The numerator (Reach × Impact × Confidence) represents total potential value, while the denominator (Effort) represents cost—measuring value per unit of investment.
When should I recalculate RICE scores?
Recalculate quarterly or whenever significant new information emerges. Your confidence might increase after user research, or effort estimates might change after technical discovery. Regular updates keep your roadmap aligned with current reality and prevent outdated priorities.