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Featured Prompt

Feature Prioritization (RICE)

Prioritize your feature backlog using the RICE scoring framework.

Analytics & Metrics Universal Intermediate
2
0
#prioritization #RICE #roadmap

The Prompt

Act as a Product Manager experienced in prioritization frameworks. Help me prioritize my feature backlog using the RICE framework (Reach, Impact, Confidence, Effort). **Product Context:** - Product: [Name] - Current user base: [Number] - Time period for planning: [Quarter/Half] **Features to Evaluate:** 1. [Feature 1 - brief description] 2. [Feature 2 - brief description] 3. [Feature 3 - brief description] 4. [Feature 4 - brief description] 5. [Feature 5 - brief description] **Available Data:** - [Any relevant metrics or user research] For each feature, please provide: 1. **RICE Score Breakdown:** - **Reach**: How many users will this impact per quarter? (number) - **Impact**: What is the impact per user? (0.25/0.5/1/2/3 scale) - **Confidence**: How confident are we? (100%/80%/50%) - **Effort**: Person-months required (number) - **Final Score**: (R × I × C) / E 2. **Scoring Rationale:** - Why this reach estimate? - What's the expected impact? - What affects confidence? 3. **Final Prioritized List:** - Ranked by RICE score - Recommendations for next quarter 4. **Sensitivity Analysis:** - Which scores are most uncertain? - How would different assumptions change ranking? Also suggest: - Quick wins (high score, low effort) - Strategic bets (high impact, lower confidence) - Features to deprioritize or kill

Example Output

RICE Prioritization Results

Feature Reach Impact Confidence Effort Score
Feature A 10,000 2 80% 2 8,000
Feature B 5,000 3 50% 1 7,500
Feature C 20,000 1 80% 4 4,000

Recommendations

  1. Build Feature A first - Highest score with good confidence
  2. Consider Feature B - High impact but validate assumptions first...

Tips for Best Results

  • Use consistent estimation methods
  • Include both quantitative and qualitative data
  • Review and adjust scores with the team

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