Prioritization matrix

Prioritization Matrix Skill

Score, rank, and prioritize a set of features, initiatives, or ideas using structured scoring frameworks.

When to Use

• User has a list of features and needs to decide what to build first
• User needs to justify prioritization to stakeholders
• User says /prioritization-matrix followed by a list of items
• Any time competing initiatives need to be ranked

Supported Frameworks

RICE (Reach, Impact, Confidence, Effort)

Best for: Growth-focused teams with measurable reach data.

Factor	How to Score
Reach	# of users/customers affected per quarter
Impact	0.25 (minimal) / 0.5 (low) / 1 (medium) / 2 (high) / 3 (massive)
Confidence	100% (high) / 80% (medium) / 50% (low)
Effort	Person-months of work

Score = (Reach x Impact x Confidence) / Effort

ICE (Impact, Confidence, Ease)

Best for: Fast estimation when detailed reach data isn't available.

Factor	How to Score (1-10)
Impact	How much will this move the needle?
Confidence	How sure are we about impact and effort?
Ease	How easy is this to implement? (10 = trivial)

Score = Impact x Confidence x Ease

Weighted Scoring

Best for: Custom criteria that matter to your team.

Define 4-6 criteria with weights (must sum to 100%):

Criteria	Weight	Description
Strategic alignment	25%	How well does this support company goals?
User impact	25%	How much does this improve user experience?
Revenue potential	20%	Direct or indirect revenue impact
Technical feasibility	15%	How complex is implementation?
Time sensitivity	15%	Is there a window of opportunity?

Score each item 1-5 on each criterion. Weighted score = sum of (score x weight).

Value vs. Effort (2x2)

Best for: Quick visual communication to stakeholders.

Plot items on a 2x2 matrix:

• Quick Wins (High value, Low effort) → Do first
• Big Bets (High value, High effort) → Plan carefully
• Fill-ins (Low value, Low effort) → Do if capacity allows
• Money Pits (Low value, High effort) → Deprioritize

Workflow

Step 1: Clarify

• What are we prioritizing? (features, bugs, initiatives, experiments)
• What timeframe? (this sprint, this quarter, this year)
• What constraints? (team size, dependencies, deadlines)
• What's the primary goal? (growth, retention, revenue, quality)

Step 2: Choose Framework

Based on the context, recommend the most appropriate framework. If the user doesn't specify, default to RICE for product features and Weighted Scoring for strategic initiatives.

Step 3: Score

For each item:

• Score on each dimension with reasoning (not just numbers)
• Flag assumptions and confidence level
• Note dependencies between items

Step 4: Rank & Recommend

• Sort by composite score
• Group into tiers: Must Do / Should Do / Could Do / Won't Do
• Highlight any items where the score conflicts with your intuition (and explain why)

Step 5: Communicate

Generate a stakeholder-ready summary:

• Top 3 priorities with one-sentence rationale each
• What we're NOT doing and why
• Key assumptions that could change the ranking

Output Format

Generate a clean markdown table with scores, plus a summary paragraph. Include the rationale for the top and bottom items. Flag any close calls where small changes in assumptions would flip the ranking.

AI/ML-Specific Considerations

When prioritizing AI features, also consider:

• Model readiness: Is the underlying model capable enough?
• Eval coverage: Do we have evals to measure success?
• Safety review: Does this need safety/red-team review?
• Data requirements: Do we have the training/eval data?
• Cost per query: What's the inference cost impact?