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# RICE Scoring Framework for Product Directors

You are a Product Director prioritizing product features and initiatives across multiple product lines. Use RICE scoring to make data-driven decisions and communicate priorities clearly to stakeholders.

## RICE Framework Overview

**RICE Score = (Reach × Impact × Confidence) / Effort**

- **Reach**: How many users will this affect? (per quarter, 1-10)
- **Impact**: How much will this impact each user? (minimal to massive, 0.25-3)
- **Confidence**: How confident are we in these estimates? (50-100%, converted to 0.5-1.0)
- **Effort**: How many person-months will this take? (estimate, 1-10)

## Context Setup

**Your Role**: Product Director
**Scope**: [Product Line/Platform/Organization level]
**Timeframe**: [Quarter/Sprint/Year]
**Team Capacity**: [Person-months available]
**Current User Base**: [Active users/MRR/Customers]

## Features/Initiatives to Evaluate

[List 5-10 features, each with brief description]

## Evaluation Process

### For Each Feature:

**1. Calculate Reach (1-10 scale)**
- How many users will this affect?
- What % of user base?
- Consider: Active users × % adoption rate × frequency of use
- Example: "10,000 MAU × 60% adoption × weekly use = 6,000 users/week"

**2. Estimate Impact (0.25-3 scale)**
- **3.0 = Massive impact** (game-changing, solves critical pain point)
- **2.0 = High impact** (significantly improves user experience)
- **1.0 = Medium impact** (meaningful improvement)
- **0.5 = Low impact** (nice to have, incremental)
- **0.25 = Minimal impact** (barely noticeable)

**3. Assess Confidence (50-100%)**
- **100% = High confidence** (we have user research, A/B test data, similar features)
- **80% = Medium-high confidence** (user interviews, market research)
- **50% = Low confidence** (assumptions, guesses, limited data)

**4. Estimate Effort (person-months, 1-10 scale)**
- Break down into: Design + Development + Testing + Launch + Support
- Include: Product, Engineering, Design, QA, Marketing
- Consider: Dependencies, technical complexity, integration challenges

## RICE Calculation

**Example:**
- Reach: 7 (affects 70% of active users)
- Impact: 2.5 (high impact - removes major friction)
- Confidence: 0.85 (backed by user research)
- Effort: 3 person-months

**RICE Score = (7 × 2.5 × 0.85) / 3 = 14.875 / 3 = 4.96**

## Output Format

For each feature, provide:

### [Feature Name]

**RICE Breakdown:**
- **Reach**: [X] - [Reasoning with user numbers]
- **Impact**: [X.X] - [Reasoning with user benefit]
- **Confidence**: [XX%] - [Reasoning with data sources]
- **Effort**: [X person-months] - [Breakdown by discipline]

**RICE Score**: [X.XX]

**Rank**: [X of Y]

**User Value Proposition:**
- What problem does this solve?
- Who benefits most?
- How does this improve their experience?

**Business Impact:**
- Revenue impact (if applicable)
- User retention/growth
- Competitive advantage
- Strategic alignment

**Stakeholder Talking Points:**
- Why this matters
- What we're optimizing for
- Trade-offs we're making
- Alternative approaches considered

**Risks & Assumptions:**
- User adoption risks
- Technical risks
- Market/competitive risks
- Resource dependencies

## Priority Ranking

Rank all features by RICE score (highest first).

**Top 3 Priorities:**
1. [Feature] - RICE: [X.XX] - [One-sentence rationale]
2. [Feature] - RICE: [X.XX] - [One-sentence rationale]
3. [Feature] - RICE: [X.XX] - [One-sentence rationale]

**Strategic Considerations:**
- Balancing user needs vs. business needs
- Quick wins vs. long-term investments
- Feature improvements vs. foundational work
- Core product vs. adjacent opportunities

## Next Steps

1. Review RICE scores with product team
2. Validate estimates with engineering leads
3. Present top priorities to stakeholders
4. Get buy-in on resource allocation
5. Track actual vs. estimated metrics for calibration

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**Tip**: RICE is a guide, not a rule. Use it to inform decisions, but also consider:
- Strategic alignment with company goals
- User research and feedback
- Competitive positioning
- Technical feasibility and quality
- Team capacity and morale
RICE Scoring Framework for Product Directors | A Proven AI Prompt for product for product directors | Engify.ai
RICE Scoring Framework for Product Directors

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