- Created skills/ directory - Moved 272 skills to skills/ subfolder - Kept agents/ at root level - Kept installation scripts and docs at root level Repository structure: - skills/ - All 272 skills from skills.sh - agents/ - Agent definitions - *.sh, *.ps1 - Installation scripts - README.md, etc. - Documentation Co-Authored-By: Claude <noreply@anthropic.com>
352 lines
8.7 KiB
Markdown
352 lines
8.7 KiB
Markdown
---
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name: product-manager-toolkit
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description: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.
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---
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# Product Manager Toolkit
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Essential tools and frameworks for modern product management, from discovery to delivery.
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## Quick Start
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### For Feature Prioritization
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```bash
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python scripts/rice_prioritizer.py sample # Create sample CSV
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python scripts/rice_prioritizer.py sample_features.csv --capacity 15
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```
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### For Interview Analysis
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```bash
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python scripts/customer_interview_analyzer.py interview_transcript.txt
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```
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### For PRD Creation
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1. Choose template from `references/prd_templates.md`
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2. Fill in sections based on discovery work
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3. Review with stakeholders
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4. Version control in your PM tool
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## Core Workflows
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### Feature Prioritization Process
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1. **Gather Feature Requests**
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- Customer feedback
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- Sales requests
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- Technical debt
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- Strategic initiatives
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2. **Score with RICE**
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```bash
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# Create CSV with: name,reach,impact,confidence,effort
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python scripts/rice_prioritizer.py features.csv
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```
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- **Reach**: Users affected per quarter
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- **Impact**: massive/high/medium/low/minimal
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- **Confidence**: high/medium/low
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- **Effort**: xl/l/m/s/xs (person-months)
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3. **Analyze Portfolio**
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- Review quick wins vs big bets
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- Check effort distribution
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- Validate against strategy
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4. **Generate Roadmap**
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- Quarterly capacity planning
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- Dependency mapping
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- Stakeholder alignment
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### Customer Discovery Process
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1. **Conduct Interviews**
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- Use semi-structured format
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- Focus on problems, not solutions
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- Record with permission
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2. **Analyze Insights**
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```bash
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python scripts/customer_interview_analyzer.py transcript.txt
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```
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Extracts:
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- Pain points with severity
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- Feature requests with priority
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- Jobs to be done
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- Sentiment analysis
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- Key themes and quotes
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3. **Synthesize Findings**
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- Group similar pain points
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- Identify patterns across interviews
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- Map to opportunity areas
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4. **Validate Solutions**
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- Create solution hypotheses
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- Test with prototypes
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- Measure actual vs expected behavior
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### PRD Development Process
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1. **Choose Template**
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- **Standard PRD**: Complex features (6-8 weeks)
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- **One-Page PRD**: Simple features (2-4 weeks)
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- **Feature Brief**: Exploration phase (1 week)
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- **Agile Epic**: Sprint-based delivery
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2. **Structure Content**
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- Problem → Solution → Success Metrics
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- Always include out-of-scope
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- Clear acceptance criteria
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3. **Collaborate**
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- Engineering for feasibility
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- Design for experience
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- Sales for market validation
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- Support for operational impact
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## Key Scripts
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### rice_prioritizer.py
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Advanced RICE framework implementation with portfolio analysis.
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**Features**:
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- RICE score calculation
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- Portfolio balance analysis (quick wins vs big bets)
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- Quarterly roadmap generation
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- Team capacity planning
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- Multiple output formats (text/json/csv)
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**Usage Examples**:
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```bash
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# Basic prioritization
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python scripts/rice_prioritizer.py features.csv
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# With custom team capacity (person-months per quarter)
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python scripts/rice_prioritizer.py features.csv --capacity 20
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# Output as JSON for integration
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python scripts/rice_prioritizer.py features.csv --output json
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```
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### customer_interview_analyzer.py
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NLP-based interview analysis for extracting actionable insights.
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**Capabilities**:
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- Pain point extraction with severity assessment
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- Feature request identification and classification
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- Jobs-to-be-done pattern recognition
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- Sentiment analysis
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- Theme extraction
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- Competitor mentions
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- Key quotes identification
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**Usage Examples**:
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```bash
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# Analyze single interview
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python scripts/customer_interview_analyzer.py interview.txt
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# Output as JSON for aggregation
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python scripts/customer_interview_analyzer.py interview.txt json
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```
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## Reference Documents
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### prd_templates.md
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Multiple PRD formats for different contexts:
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1. **Standard PRD Template**
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- Comprehensive 11-section format
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- Best for major features
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- Includes technical specs
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2. **One-Page PRD**
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- Concise format for quick alignment
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- Focus on problem/solution/metrics
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- Good for smaller features
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3. **Agile Epic Template**
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- Sprint-based delivery
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- User story mapping
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- Acceptance criteria focus
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4. **Feature Brief**
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- Lightweight exploration
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- Hypothesis-driven
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- Pre-PRD phase
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## Prioritization Frameworks
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### RICE Framework
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```
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Score = (Reach × Impact × Confidence) / Effort
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Reach: # of users/quarter
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Impact:
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- Massive = 3x
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- High = 2x
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- Medium = 1x
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- Low = 0.5x
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- Minimal = 0.25x
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Confidence:
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- High = 100%
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- Medium = 80%
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- Low = 50%
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Effort: Person-months
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```
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### Value vs Effort Matrix
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```
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Low Effort High Effort
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High QUICK WINS BIG BETS
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Value [Prioritize] [Strategic]
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Low FILL-INS TIME SINKS
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Value [Maybe] [Avoid]
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```
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### MoSCoW Method
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- **Must Have**: Critical for launch
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- **Should Have**: Important but not critical
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- **Could Have**: Nice to have
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- **Won't Have**: Out of scope
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## Discovery Frameworks
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### Customer Interview Guide
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```
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1. Context Questions (5 min)
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- Role and responsibilities
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- Current workflow
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- Tools used
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2. Problem Exploration (15 min)
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- Pain points
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- Frequency and impact
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- Current workarounds
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3. Solution Validation (10 min)
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- Reaction to concepts
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- Value perception
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- Willingness to pay
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4. Wrap-up (5 min)
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- Other thoughts
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- Referrals
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- Follow-up permission
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```
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### Hypothesis Template
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```
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We believe that [building this feature]
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For [these users]
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Will [achieve this outcome]
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We'll know we're right when [metric]
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```
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### Opportunity Solution Tree
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```
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Outcome
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├── Opportunity 1
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│ ├── Solution A
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│ └── Solution B
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└── Opportunity 2
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├── Solution C
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└── Solution D
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```
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## Metrics & Analytics
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### North Star Metric Framework
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1. **Identify Core Value**: What's the #1 value to users?
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2. **Make it Measurable**: Quantifiable and trackable
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3. **Ensure It's Actionable**: Teams can influence it
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4. **Check Leading Indicator**: Predicts business success
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### Funnel Analysis Template
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```
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Acquisition → Activation → Retention → Revenue → Referral
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Key Metrics:
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- Conversion rate at each step
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- Drop-off points
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- Time between steps
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- Cohort variations
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```
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### Feature Success Metrics
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- **Adoption**: % of users using feature
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- **Frequency**: Usage per user per time period
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- **Depth**: % of feature capability used
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- **Retention**: Continued usage over time
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- **Satisfaction**: NPS/CSAT for feature
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## Best Practices
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### Writing Great PRDs
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1. Start with the problem, not solution
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2. Include clear success metrics upfront
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3. Explicitly state what's out of scope
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4. Use visuals (wireframes, flows)
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5. Keep technical details in appendix
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6. Version control changes
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### Effective Prioritization
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1. Mix quick wins with strategic bets
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2. Consider opportunity cost
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3. Account for dependencies
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4. Buffer for unexpected work (20%)
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5. Revisit quarterly
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6. Communicate decisions clearly
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### Customer Discovery Tips
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1. Ask "why" 5 times
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2. Focus on past behavior, not future intentions
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3. Avoid leading questions
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4. Interview in their environment
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5. Look for emotional reactions
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6. Validate with data
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### Stakeholder Management
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1. Identify RACI for decisions
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2. Regular async updates
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3. Demo over documentation
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4. Address concerns early
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5. Celebrate wins publicly
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6. Learn from failures openly
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## Common Pitfalls to Avoid
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1. **Solution-First Thinking**: Jumping to features before understanding problems
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2. **Analysis Paralysis**: Over-researching without shipping
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3. **Feature Factory**: Shipping features without measuring impact
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4. **Ignoring Technical Debt**: Not allocating time for platform health
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5. **Stakeholder Surprise**: Not communicating early and often
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6. **Metric Theater**: Optimizing vanity metrics over real value
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## Integration Points
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This toolkit integrates with:
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- **Analytics**: Amplitude, Mixpanel, Google Analytics
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- **Roadmapping**: ProductBoard, Aha!, Roadmunk
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- **Design**: Figma, Sketch, Miro
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- **Development**: Jira, Linear, GitHub
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- **Research**: Dovetail, UserVoice, Pendo
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- **Communication**: Slack, Notion, Confluence
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## Quick Commands Cheat Sheet
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```bash
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# Prioritization
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python scripts/rice_prioritizer.py features.csv --capacity 15
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# Interview Analysis
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python scripts/customer_interview_analyzer.py interview.txt
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# Create sample data
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python scripts/rice_prioritizer.py sample
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# JSON outputs for integration
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python scripts/rice_prioritizer.py features.csv --output json
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python scripts/customer_interview_analyzer.py interview.txt json
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```
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