Reach
Estimate how many users or accounts are affected in a given period. You can enter week, month, quarter, or year and the tool normalizes to quarter for clean ranking.
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RICE Score Calculator (Free)
This RICE score calculator helps product teams prioritize feature ideas in one view, with consistent math and practical exports for roadmap planning.
Compare one initiative or an entire backlog, normalize mixed timeframes, and share ranking decisions without extra tooling.
- Batch and single scoring with normalized reach-per-quarter ranking
- CSV import plus CSV, Markdown, and JSON exports for handoff
- Quick wins, stakeholder rationale, and confidence sensitivity checks
No login. Runs in your browser. We do not store your inputs.
Calculator mode
Normalization: week x13, month x3, quarter x1, year /4. Import and export headers: name, reach_input, reach_timeframe, reach_per_quarter, impact, confidence_percent, effort_person_months, notes, rice_score, rank.
Batch comparison table
Impact (?), confidence (?), effort (?).
| Initiative name | Reach | Reach time frame | Impact | Confidence | Effort | Notes / assumptions | RICE score | Rank | Actions |
|---|---|---|---|---|---|---|---|---|---|
Qtr: 1000 | 800 | 1 |
Quick wins view
High score and low effort initiatives.
- First initiative (800) with 1 pm effort
Research needed
Low-confidence rows that likely need discovery.
- No low-confidence rows in the ranked set.
Output panel preview (Markdown)
Loading saved data...
How it works
Use the calculator as a working prioritization workflow, not a one-time scoring exercise. The value comes from keeping assumptions visible and rerunning ranking as evidence changes, so roadmap conversations stay grounded in current information.
Step 1
Add one or more initiatives with Reach, Impact, Confidence, and Effort inputs. Reach can be weekly, monthly, quarterly, or yearly.
Step 2
The calculator normalizes every initiative to reach per quarter, computes the RICE score, and ranks rows with stable sorting.
Step 3
Review quick wins, stakeholder rationale, and confidence sensitivity, then export or share for roadmap decisions.
What RICE stands for
RICE is short for Reach, Impact, Confidence, and Effort. The framework works best when each value is estimated in a repeatable way, then discussed as assumptions rather than facts. A good score is useful only if your team can explain why each input was chosen and what evidence could change it next week.
Impact
Use the default Intercom-style scale: Massive 3, High 2, Medium 1, Low 0.5, Minimal 0.25. Tie impact to one primary metric, not multiple outcomes.
Confidence
Confidence reflects evidence strength. Start with 100%, 80%, or 50%, then use a custom percentage when your evidence sits between standard levels.
Effort
Effort is entered in person-months with minimum 0.5 and step 0.5. The formula divides by effort, so oversized estimates can quickly push initiatives down ranking.
Scoring rubrics with examples
Keep scoring pragmatic. If your team uses vague scoring language, RICE devolves into a debate about interpretation. Clear rubrics reduce that friction and make ranking changes easier to communicate in roadmap prioritization meetings.
Impact rubric
- Massive (3): likely to move a core KPI materially this cycle.
- High (2): meaningful KPI movement with moderate dependency risk.
- Medium (1): useful improvement but not a game-changing shift.
- Low (0.5): incremental enhancement with limited visible change.
- Minimal (0.25): small polish or speculative upside.
Confidence rubric
- 100%: strong quantitative support or repeated historical proof.
- 80%: good directional evidence, but still some unknowns.
- 50%: early hypothesis with limited supporting data.
If your evidence is mixed, set custom confidence and note what experiment would increase certainty for the next scoring pass.
Examples
These three prefilled scenarios are realistic product initiatives. Load one to see how the RICE scoring model behaves with different effort and confidence profiles.
Guided onboarding checklist
Reach 1200 per quarter, impact High (2), confidence 80%, effort 1.5 person-months, activation-focused assumptions.
Strong RICE candidate with solid confidence and moderate effort. Good fit for near-term roadmap prioritization.
Pricing page proof block test
Reach 350 per month (normalized to quarter), impact Medium (1), confidence 50%, effort 0.5 person-month.
Quick to run and cheap in effort, but confidence is low. Prioritize as a fast experiment, not a full commitment.
Enterprise audit log export
Reach 120 per quarter, impact Massive (3), confidence 80%, effort 4 person-months, cross-team dependencies.
Potentially high-impact initiative that ranks lower because effort is substantial. Keep as a strategic track.
Pro tips
- Anchor Reach to one source of truth (analytics dashboard, CRM report, or cohort export) before scoring.
- Keep one time frame per workshop, then normalize to quarter only for comparability and ranking.
- Use impact labels publicly and numeric values privately so stakeholders align on meaning, not decimals.
- Treat 50% confidence as a trigger for discovery tasks, not as a blocker for every experiment.
- Split initiatives with effort above 3 person-months into phased bets and score phase one first.
- Document one core assumption in Notes for every row; it makes future reprioritization explainable.
- Reorder by score only after validation errors are resolved, otherwise rank noise will mislead planning.
- When two rows are close, use confidence and dependency risk as tie-breakers in roadmap discussion.
- Export Markdown after each session to create an audit trail of why backlog order changed.
- Rerun the sensitivity check before leadership reviews to spot fragile priorities early.
Common mistakes
Symptom: Scores look inflated across every initiative.
Cause: Impact is set to Massive by default without a shared rubric.
Fix: Define impact anchors before scoring and challenge every Massive score with concrete metric evidence.
Symptom: A weekly initiative outranks long-term bets unexpectedly.
Cause: Reach timeframe was mixed but normalization was ignored in discussion.
Fix: Review normalized reach per quarter in the tooltip and align on quarter-based comparisons.
Symptom: Top-ranked rows change every meeting with no clear reason.
Cause: Inputs are edited without updating assumptions in notes.
Fix: Require one note update whenever confidence, reach, or effort changes.
Symptom: Import CSV fails even though values look correct.
Cause: Headers or order differ from the required template.
Fix: Use the downloadable sample CSV and preserve the exact header names and order.
Symptom: Initiatives with low confidence still dominate ranking.
Cause: Confidence was set to 100% despite limited evidence.
Fix: Use 50% or custom low confidence until quantitative proof exists.
Symptom: Effort inputs are rejected with validation errors.
Cause: Effort values are below 0.5 or not in 0.5 increments.
Fix: Use person-month estimates with minimum 0.5 and step size 0.5.
Symptom: Stakeholders reject the ranked table as too technical.
Cause: Raw math is shared without practical rationale and assumptions.
Fix: Switch to Stakeholder View and present top-five rationale with notes.
Symptom: Priorities collapse under uncertainty checks.
Cause: Backlog relies on fragile confidence assumptions.
Fix: Run the confidence -20% sensitivity mode and promote initiatives that remain stable.
FAQ
Is this free?
Yes. The RICE score calculator is fully free, requires no login, and supports unlimited scoring sessions. You can compare a full backlog in batch mode, run one-off checks in single mode, and export results to CSV, Markdown, or JSON without any paywall steps.
Do you store my data?
No server storage is used for your initiative inputs. Data stays in your browser, with optional local autosave so you can resume work later. You can remove everything at any time with Clear data. CraftUp does not persist your initiative names, notes, or scores on backend systems.
How is this different from using ChatGPT directly?
A chat tool can brainstorm, but it does not enforce consistent RICE structure by default. This calculator standardizes inputs, normalizes reach per quarter, validates effort steps, ranks initiatives, and gives export workflows. That consistency is what makes recurring roadmap prioritization credible across cycles.
Can I use this for work or client projects?
Yes. The output format is built for practical product and growth planning, including stakeholder review decks and backlog triage docs. Teams commonly export Markdown into planning notes and share compressed URLs internally. Just review notes before sharing externally if they contain sensitive assumptions.
What confidence values should I use in RICE prioritization?
Start with the default 100%, 80%, and 50% bands to keep scoring calibrated across teams. Use 100% only for evidence-backed initiatives, 80% when you have good directional support, and 50% when assumptions are still weak. You can also enter a custom percentage for edge cases.
Why do you normalize reach to quarter?
Teams often mix weekly, monthly, and quarterly reach estimates. Without normalization, ranking becomes misleading because time windows differ. The calculator converts all entries to reach per quarter using explicit factors, so initiatives can be compared on one baseline while preserving original input values.
How should I estimate effort in person-months?
Use implementation effort for the scoped initiative, not broad program effort. Include engineering, design, and QA where relevant, then round to 0.5 increments to keep estimates practical. If effort is uncertain, run a lower-confidence score first and refine after technical discovery.
Can I share a scoring session with my team?
Yes. Share URL compresses your batch table and notes client-side and recreates the session in a fresh browser. This makes async reviews straightforward because everyone sees the same rows and assumptions. If the URL becomes long, trim notes before sharing outside your internal tools.
What does the sensitivity check do?
Sensitivity mode applies a relative confidence drop of 20% to each row and compares the top-five ranking against the baseline. It highlights priorities that are fragile when evidence weakens. Use it before roadmap commitments to avoid overcommitting to initiatives with unstable confidence assumptions.
How often should we rerun this RICE scoring model?
A weekly or biweekly cadence is practical for most teams. Re-score when reach forecasts change, confidence improves from new research, or effort estimates shift after technical grooming. Frequent lightweight reruns keep product backlog prioritization aligned with current evidence instead of outdated assumptions.
Learn more with CraftUp
Keep your prioritization decisions execution-ready
Use CraftUp lessons and workflows to turn ranked initiatives into shipped outcomes.
Freshness
Last updated: 2026-03-03
- Launched advanced batch and single RICE workflows with normalized reach-per-quarter ranking.
- Added CSV import/export, Markdown and JSON exports, and lz-string share links for session handoff.
- Added quick wins, stakeholder rationale, and confidence -20% sensitivity checks for decision robustness.