Feature Prioritization (RICE)

You are an experienced Product Manager using the RICE framework to prioritize these features: [Features to Prioritize]

For each feature, provide:

## RICE SCORING BREAKDOWN

### Feature Name
**Reach** (users/quarter):
- Estimated number of users impacted
- Justification for estimate
- Confidence level

**Impact** (scale: 0.25=minimal, 0.5=low, 1=medium, 2=high, 3=massive):
- Expected impact on key metrics
- User value delivered
- Strategic importance

**Confidence** (percentage):
- Problem validation confidence
- Solution confidence
- Execution confidence
- Overall percentage

**Effort** (person-months):
- Engineering effort
- Design effort
- QA effort
- Total estimate

**RICE Score**: (Reach × Impact × Confidence) / Effort. Enter Confidence as a decimal, such as 0.8 for 80%.

## PRIORITIZED RANKING
List all features ranked by RICE score with:
1. Feature name - Score: [X]
2. Key insights about priority
3. Dependencies or constraints
4. Recommended sequencing

## STRATEGIC RECOMMENDATIONS
- Top 3 features to build now
- Features to defer or descope
- Resource allocation suggestions
- Risk mitigation strategies

## SENSITIVITY ANALYSIS
- **Effort Variance**: What if effort estimates are ±50% off?
  - Show how rankings change with optimistic/pessimistic effort
  - Identify which items are stable vs volatile in ranking
- **Confidence Calibration**: 
  - Check whether each confidence rating matches the supporting evidence
  - Do not force a distribution; similar evidence can justify similar scores
- **Scenario analysis**: Compare these cases; call it Monte Carlo only if random sampling from stated distributions is actually performed:
  - Best case: High confidence, low effort
  - Expected case: Current estimates
  - Worst case: Low confidence, high effort
- **Dependencies Impact**: How do item dependencies affect priority?

## SCORING CONSTRAINTS
- **Impact consistency**: Use the 0.25-3 scale above for all items
- **Evidence requirement**: Explain Confidence using evidence for Reach, Impact, and Effort
- **Effort Reality Check**: Compare to historical velocity data

Provide specific numbers and clear justification for each score. Include confidence level for each assessment.

## Evidence and accuracy
- Use supplied facts and verified sources. Do not invent metrics, quotes, people, company details, commitments, or personal experience.
- Mark assumptions [ASSUMPTION], estimates [ESTIMATE: method], and unresolved questions [UNCERTAIN: reason]. Leave unavailable values unfilled rather than guessing.
- Explain confidence as high, medium, or low using the evidence available. These labels are judgments, not calibrated probabilities. Give numerical probabilities only when a stated method supports them.
- Treat preset weights, scores, timelines, and targets in this template as starting examples. Adapt them to the task and explain changes; they are not universal benchmarks or approved commitments.
- Define score scales and directions before calculating totals. Keep units, denominators, and time periods consistent. Do not average away a critical blocker.
- Use only exact supplied or verified quotes with attribution. Label requested fictional examples as illustrative. Distinguish observed behavior from inferred motives or causes.
- Use only the sections and rows the task needs. Write plainly, preserve necessary technical terms, and avoid unsupported benefits or forced specificity.
- Identify missing information needed for a decision. Recommendations remain proposals until reviewed by the responsible team.

## Evidence and accuracy
- Use supplied facts and verified sources. Do not invent metrics, quotes, people, company details, commitments, or personal experience.
- Mark assumptions [ASSUMPTION], estimates [ESTIMATE: method], and unresolved questions [UNCERTAIN: reason]. Leave unavailable values unfilled rather than guessing.
- Explain confidence as high, medium, or low using the evidence available. These labels are judgments, not calibrated probabilities. Give numerical probabilities only when a stated method supports them.
- Treat preset weights, scores, timelines, and targets in this template as starting examples. Adapt them to the task and explain changes; they are not universal benchmarks or approved commitments.
- Define score scales and directions before calculating totals. Keep units, denominators, and time periods consistent. Do not average away a critical blocker.
- Use only exact supplied or verified quotes with attribution. Label requested fictional examples as illustrative. Distinguish observed behavior from inferred motives or causes.
- Use only the sections and rows the task needs. Write plainly, preserve necessary technical terms, and avoid unsupported benefits or forced specificity.
- Identify missing information needed for a decision. Recommendations remain proposals until reviewed by the responsible team.