RICE Scoring
A quantitative feature prioritization framework that scores each initiative by Reach, Impact, Confidence, and Effort — producing a single number to rank your roadmap.
What is RICE Scoring?
RICE scoring is a prioritization framework that helps product managers rank features and initiatives using four factors:
| Factor | Definition | Unit |
|---|---|---|
| Reach | How many users are affected per quarter? | Number of users |
| Impact | How much does it move the needle per user? | 0.25 / 0.5 / 1 / 2 / 3 |
| Confidence | How certain are you in your estimates? | % (50 / 80 / 100) |
| Effort | Total person-months to build | Person-months |
The formula
**RICE Score = (Reach × Impact × Confidence%) ÷ Effort**
A higher score means higher priority.
Worked example
| Feature | Reach | Impact | Confidence | Effort | RICE Score |
|---|---|---|---|---|---|
| Bulk CSV export | 800 | 1 | 80% | 0.5 | 1,280 |
| SSO / SAML login | 200 | 3 | 80% | 2 | 240 |
| Slack notifications | 1,200 | 0.5 | 100% | 0.5 | 1,200 |
| AI summary widget | 400 | 2 | 50% | 3 | 133 |
Ranked order: CSV export → Slack notifications → SSO → AI widget.
Impact scale
| Score | Description |
|---|---|
| 3 | Massive impact — fundamentally changes user behaviour |
| 2 | High impact — significant improvement to core workflow |
| 1 | Medium impact — noticeable improvement |
| 0.5 | Low impact — minor convenience |
| 0.25 | Minimal impact — edge case |
When to use RICE
Use RICE when:
- You have a backlog of 10+ items competing for the same sprint capacity
- You need to defend prioritization decisions to stakeholders
- You want to depersonalize debates ("the data says X, not my opinion")
Don't use RICE for:
- < 5 items where tradeoffs are obvious
- Pure compliance or regulatory work (must-do regardless of score)
- Very early-stage products where all Reach and Impact estimates are noise
Common mistakes
- Using 100% confidence for everything. Low confidence should reduce the score. If you're not sure the impact is real, score it at 50%.
- PM estimates Effort. Engineering estimates Effort. PMs estimate Reach, Impact, and Confidence. Mixing this creates biased scores.
- Adjusting scores after calculating. If you adjust scores to match a predetermined answer, you've built a rationalization tool, not a prioritization tool.
Free templates for RICE
Frequently asked questions
What's the difference between RICE and ICE scoring?
ICE (Impact × Confidence × Ease) skips the Reach factor, treating all features as if they affect the same user base. RICE adds Reach explicitly, making it better when features have different audience sizes. For growth experiments targeting all users equally, ICE is simpler and equivalent.
Should I use the same time horizon for all Reach estimates?
Yes — always estimate Reach over the same period (typically one quarter). Mixing time horizons makes scores incomparable.
What RICE score should trigger shipping a feature?
There's no universal threshold — set one for your team at the start of the quarter. Items above the threshold are in scope; items below go to the backlog. A threshold of 200 is common for B2B SaaS teams with 2–3 person-months of capacity per sprint.
How often should RICE scores be recalculated?
Recalculate at the start of each planning cycle (quarterly or per sprint). Scores decay as user behaviour changes and as confidence in estimates improves or decays.
Apply RICE Scoring to your real product data
PMRead ingests customer feedback, interviews, and Slack threads — and generates PRDs grounded in real evidence.
Related terms
North Star Metric
A single metric that best captures the core value your product delivers to customers — and that the whole company optimises toward.
MoSCoW Method
A prioritization technique that classifies requirements into four categories — Must Have, Should Have, Could Have, and Won't Have — to scope a release against a fixed deadline.