Prioritize with math, not opinions. RICE scoring forces explicit tradeoffs. The enabler/blocker lens from Linear ensures you're not just building fun things while adoption barriers remain.
RICE Scoring
Score every candidate feature on four dimensions:
- Reach: How many users/accounts will this affect in a set time period? Use real numbers from analytics, not gut feel. "500 users/quarter" not "a lot."
- Impact: How much will this move the target metric per user? Score 0.25 (minimal), 0.5 (low), 1 (medium), 2 (high), 3 (massive). Be honest — most features are a 1.
- Confidence: How sure are you about Reach and Impact? 100% = hard data. 80% = strong evidence. 50% = gut feel. NEVER score 100% without quantitative data.
- Effort: Person-weeks of work. Include design, engineering, QA, and any cross-team coordination. Round up.
RICE = (Reach x Impact x Confidence) / Effort
Example: SSO — Reach: 500 users/qtr, Impact: 2 (high — unlocks enterprise deals), Confidence: 80%, Effort: 4 person-weeks. RICE = (500 x 2 x 0.8) / 4 = 200. Tag: Blocker.
Rank by score. The math won't be perfect, but it forces you to justify each dimension.
Enablers vs Blockers (Linear)
After RICE scoring, classify each feature:
- Blocker: Removes a barrier to adoption or retention. Users are churning, stuck, or can't even start because this is missing. Examples: missing SSO for enterprise deals, broken mobile experience, no data export.
- Enabler: Delights existing users or deepens engagement. Users are already successful but this makes them more so. Examples: keyboard shortcuts, advanced filters, integrations.
Rule: Prioritize blockers over enablers when growing. Removing friction > adding delight when you're trying to grow. Flip this when retention is strong but engagement is flat.
Running a Prioritization Session
- List all candidates with a one-sentence description
- Score each on R, I, C, E independently — don't anchor on each other
- Calculate RICE scores and rank
- Tag each as Blocker or Enabler
- Check: are any Blockers ranked below Enablers? Justify or re-rank.
- Top 3-5 items = your next cycle
Guidelines
- ALWAYS show the math. A prioritization without visible scores is just an opinion list.
- NEVER let Confidence = 100% without hard data (analytics, A/B test results, or customer commit).
- ALWAYS separate enablers from blockers before finalizing the rank.
- NEVER prioritize more than one cycle at a time. The world changes. Re-score next cycle.
- CRITICAL: If two items are within 20% RICE score of each other, they're effectively tied. Use the blocker/enabler lens to break ties, or pick the one with higher Confidence.
Built on Intercom's RICE framework and the Linear Method. Skills from productskills.
1---2name: feature-prioritization3description: Prioritize features and backlog items using RICE scoring and Linear's enablers vs blockers lens. Use when asked to rank features, prioritize a backlog, decide what to build next, or evaluate feature requests against each other.4---56Prioritize with math, not opinions. RICE scoring forces explicit tradeoffs. The enabler/blocker lens from Linear ensures you're not just building fun things while adoption barriers remain.78## RICE Scoring910Score every candidate feature on four dimensions:1112- **Reach:** How many users/accounts will this affect in a set time period? Use real numbers from analytics, not gut feel. "500 users/quarter" not "a lot."13- **Impact:** How much will this move the target metric per user? Score 0.25 (minimal), 0.5 (low), 1 (medium), 2 (high), 3 (massive). Be honest — most features are a 1.14- **Confidence:** How sure are you about Reach and Impact? 100% = hard data. 80% = strong evidence. 50% = gut feel. NEVER score 100% without quantitative data.15- **Effort:** Person-weeks of work. Include design, engineering, QA, and any cross-team coordination. Round up.1617**RICE = (Reach x Impact x Confidence) / Effort**1819Example: SSO — Reach: 500 users/qtr, Impact: 2 (high — unlocks enterprise deals), Confidence: 80%, Effort: 4 person-weeks. RICE = (500 x 2 x 0.8) / 4 = **200**. Tag: Blocker.2021Rank by score. The math won't be perfect, but it forces you to justify each dimension.2223## Enablers vs Blockers (Linear)2425After RICE scoring, classify each feature:2627- **Blocker:** Removes a barrier to adoption or retention. Users are churning, stuck, or can't even start because this is missing. Examples: missing SSO for enterprise deals, broken mobile experience, no data export.28- **Enabler:** Delights existing users or deepens engagement. Users are already successful but this makes them more so. Examples: keyboard shortcuts, advanced filters, integrations.2930**Rule: Prioritize blockers over enablers when growing.** Removing friction > adding delight when you're trying to grow. Flip this when retention is strong but engagement is flat.3132## Running a Prioritization Session33341. List all candidates with a one-sentence description352. Score each on R, I, C, E independently — don't anchor on each other363. Calculate RICE scores and rank374. Tag each as Blocker or Enabler385. Check: are any Blockers ranked below Enablers? Justify or re-rank.396. Top 3-5 items = your next cycle4041## Guidelines4243- ALWAYS show the math. A prioritization without visible scores is just an opinion list.44- NEVER let Confidence = 100% without hard data (analytics, A/B test results, or customer commit).45- ALWAYS separate enablers from blockers before finalizing the rank.46- NEVER prioritize more than one cycle at a time. The world changes. Re-score next cycle.47- CRITICAL: If two items are within 20% RICE score of each other, they're effectively tied. Use the blocker/enabler lens to break ties, or pick the one with higher Confidence.4849---5051*Built on Intercom's RICE framework and the Linear Method. Skills from [productskills](https://github.com/assimovt/productskills).*
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