ICE Scoring
A lightweight prioritization framework that scores initiatives by Impact, Confidence, and Ease — producing a simple rank-order without requiring per-feature reach estimates.
What is ICE Scoring?
ICE scoring was popularised by Sean Ellis (who also created the 40% NPS PMF benchmark) as a fast prioritisation tool for growth experiments. It scores each initiative on three dimensions:
| Factor | Question | Scale |
|---|---|---|
| Impact | If this works, how big is the effect? | 1–10 |
| Confidence | How sure are we it will work? | 1–10 |
| Ease | How easy is it to implement? | 1–10 |
**ICE Score = Impact × Confidence × Ease**
ICE vs. RICE
| Dimension | ICE | RICE |
|---|---|---|
| Reach | Not included | Included |
| Speed | Faster — no Reach estimate needed | Slower |
| Best for | Growth experiments, equal-reach features | Backlog with variable audience sizes |
| Risk | Treats all features as same audience | More accurate but more effort |
When to use ICE
- Growth experiments where all features target the full user base
- Quick stack-ranking when you need a decision in < 30 minutes
- Early-stage products where Reach estimates are unreliable
- Comparing experiments within a single funnel stage
ICE pitfall
Because Ease is in the formula, ICE systematically favours quick wins over high-impact hard things. Balance this by also reviewing top ICE items against strategic importance.
Free templates for ICE
Frequently asked questions
Should Ease be higher = easier or higher = harder?
Higher = easier in the standard ICE formula. A score of 9 means it's very easy to implement. Some teams invert this to 'Effort' (higher = more effort) and divide instead of multiply — but this changes the formula direction. Stick to the original: higher Ease = simpler implementation = higher score.
How is ICE different from just gut instinct?
ICE makes the assumptions explicit and forces you to separate the three dimensions. It also creates a shared decision record — 'we scored this 7×3×8 = 168 and ranked it #3' — which is more defensible than 'it felt right'. The value is in the conversation the scoring triggers, not the precision of the number.
Apply ICE Scoring to your real product data
PMRead ingests customer feedback, interviews, and Slack threads — and generates PRDs grounded in real evidence.
Related terms
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.
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.