Product Manager Toolkit

Essential tools and frameworks for modern product management, from discovery to delivery.

phoroth 3ca8acf 4 files · 44.3 KB Updated Sep 8, 2026 3 repo stars

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Product Manager Toolkit

Essential tools and frameworks for modern product management, from discovery to delivery.

Quick Start

For Feature Prioritization

python scripts/rice_prioritizer.py sample  # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15

For Interview Analysis

python scripts/customer_interview_analyzer.py interview_transcript.txt

For PRD Creation

Choose template from references/prd_templates.md
Fill in sections based on discovery work
Review with stakeholders
Version control in your PM tool

Core Workflows

Feature Prioritization Process

Gather Feature Requests
- Customer feedback
- Sales requests
- Technical debt
- Strategic initiatives
Score with RICE
```
# Create CSV with: name,reach,impact,confidence,effort
python scripts/rice_prioritizer.py features.csv
```
- Reach: Users affected per quarter
- Impact: massive/high/medium/low/minimal
- Confidence: high/medium/low
- Effort: xl/l/m/s/xs (person-months)
Analyze Portfolio
- Review quick wins vs big bets
- Check effort distribution
- Validate against strategy
Generate Roadmap
- Quarterly capacity planning
- Dependency mapping
- Stakeholder alignment

Customer Discovery Process

Conduct Interviews
- Use semi-structured format
- Focus on problems, not solutions
- Record with permission
Analyze Insights
```
python scripts/customer_interview_analyzer.py transcript.txt
```
Extracts:
- Pain points with severity
- Feature requests with priority
- Jobs to be done
- Sentiment analysis
- Key themes and quotes
Synthesize Findings
- Group similar pain points
- Identify patterns across interviews
- Map to opportunity areas
Validate Solutions
- Create solution hypotheses
- Test with prototypes
- Measure actual vs expected behavior

PRD Development Process

Choose Template
- Standard PRD: Complex features (6-8 weeks)
- One-Page PRD: Simple features (2-4 weeks)
- Feature Brief: Exploration phase (1 week)
- Agile Epic: Sprint-based delivery
Structure Content
- Problem → Solution → Success Metrics
- Always include out-of-scope
- Clear acceptance criteria
Collaborate
- Engineering for feasibility
- Design for experience
- Sales for market validation
- Support for operational impact

Key Scripts

rice_prioritizer.py

Advanced RICE framework implementation with portfolio analysis.

Features:

RICE score calculation
Portfolio balance analysis (quick wins vs big bets)
Quarterly roadmap generation
Team capacity planning
Multiple output formats (text/json/csv)

Usage Examples:

# Basic prioritization
python scripts/rice_prioritizer.py features.csv

# With custom team capacity (person-months per quarter)
python scripts/rice_prioritizer.py features.csv --capacity 20

# Output as JSON for integration
python scripts/rice_prioritizer.py features.csv --output json

customer_interview_analyzer.py

NLP-based interview analysis for extracting actionable insights.

Capabilities:

Pain point extraction with severity assessment
Feature request identification and classification
Jobs-to-be-done pattern recognition
Sentiment analysis
Theme extraction
Competitor mentions
Key quotes identification

Usage Examples:

# Analyze single interview
python scripts/customer_interview_analyzer.py interview.txt

# Output as JSON for aggregation
python scripts/customer_interview_analyzer.py interview.txt json

Reference Documents

prd_templates.md

Multiple PRD formats for different contexts:

Standard PRD Template
- Comprehensive 11-section format
- Best for major features
- Includes technical specs
One-Page PRD
- Concise format for quick alignment
- Focus on problem/solution/metrics
- Good for smaller features
Agile Epic Template
- Sprint-based delivery
- User story mapping
- Acceptance criteria focus
Feature Brief
- Lightweight exploration
- Hypothesis-driven
- Pre-PRD phase

Prioritization Frameworks

RICE Framework

Score = (Reach × Impact × Confidence) / Effort

Reach: # of users/quarter
Impact: 
  - Massive = 3x
  - High = 2x
  - Medium = 1x
  - Low = 0.5x
  - Minimal = 0.25x
Confidence:
  - High = 100%
  - Medium = 80%
  - Low = 50%
Effort: Person-months

Value vs Effort Matrix

         Low Effort    High Effort
         
High     QUICK WINS    BIG BETS
Value    [Prioritize]   [Strategic]
         
Low      FILL-INS      TIME SINKS
Value    [Maybe]       [Avoid]

MoSCoW Method

Must Have: Critical for launch
Should Have: Important but not critical
Could Have: Nice to have
Won't Have: Out of scope

Discovery Frameworks

Customer Interview Guide

1. Context Questions (5 min)
   - Role and responsibilities
   - Current workflow
   - Tools used

2. Problem Exploration (15 min)
   - Pain points
   - Frequency and impact
   - Current workarounds

3. Solution Validation (10 min)
   - Reaction to concepts
   - Value perception
   - Willingness to pay

4. Wrap-up (5 min)
   - Other thoughts
   - Referrals
   - Follow-up permission

Hypothesis Template

We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]

Opportunity Solution Tree

Outcome
├── Opportunity 1
│   ├── Solution A
│   └── Solution B
└── Opportunity 2
    ├── Solution C
    └── Solution D

Metrics & Analytics

North Star Metric Framework

Identify Core Value: What's the #1 value to users?
Make it Measurable: Quantifiable and trackable
Ensure It's Actionable: Teams can influence it
Check Leading Indicator: Predicts business success

Funnel Analysis Template

Acquisition → Activation → Retention → Revenue → Referral

Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations

Feature Success Metrics

Adoption: % of users using feature
Frequency: Usage per user per time period
Depth: % of feature capability used
Retention: Continued usage over time
Satisfaction: NPS/CSAT for feature

Best Practices

Writing Great PRDs

Start with the problem, not solution
Include clear success metrics upfront
Explicitly state what's out of scope
Use visuals (wireframes, flows)
Keep technical details in appendix
Version control changes

Effective Prioritization

Mix quick wins with strategic bets
Consider opportunity cost
Account for dependencies
Buffer for unexpected work (20%)
Revisit quarterly
Communicate decisions clearly

Customer Discovery Tips

Ask "why" 5 times
Focus on past behavior, not future intentions
Avoid leading questions
Interview in their enprojectnment
Look for emotional reactions
Validate with data

Stakeholder Management

Identify RACI for decisions
Regular async updates
Demo over documentation
Address concerns early
Celebrate wins publicly
Learn from failures openly

Common Pitfalls to Avoid

Solution-First Thinking: Jumping to features before understanding problems
Analysis Paralysis: Over-researching without shipping
Feature Factory: Shipping features without measuring impact
Ignoring Technical Debt: Not allocating time for platform health
Stakeholder Surprise: Not communicating early and often
Metric Theater: Optimizing vanity metrics over real value

Integration Points

This toolkit integrates with:

Analytics: Amplitude, Mixpanel, Google Analytics
Roadmapping: ProductBoard, Aha!, Roadmunk
Design: Figma, Sketch, Miro
Development: Jira, Linear, GitHub
Research: Dovetail, UserVoice, Pendo
Communication: Slack, Notion, Confluence

Quick Commands Cheat Sheet

# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15

# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt

# Create sample data
python scripts/rice_prioritizer.py sample

# JSON outputs for integration
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for enprojectnment-specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

---name: product-manager-toolkitdescription: Essential tools and frameworks for modern product management, from discovery to delivery.---# Product Manager ToolkitEssential tools and frameworks for modern product management, from discovery to delivery.## Quick Start### For Feature Prioritization```bashpython scripts/rice_prioritizer.py sample # Create sample CSVpython scripts/rice_prioritizer.py sample_features.csv --capacity 15```### For Interview Analysis```bashpython scripts/customer_interview_analyzer.py interview_transcript.txt```### For PRD Creation1. Choose template from `references/prd_templates.md`2. Fill in sections based on discovery work3. Review with stakeholders4. Version control in your PM tool## Core Workflows### Feature Prioritization Process1. **Gather Feature Requests** - Customer feedback - Sales requests - Technical debt - Strategic initiatives2. **Score with RICE** ```bash # Create CSV with: name,reach,impact,confidence,effort python scripts/rice_prioritizer.py features.csv ``` - **Reach**: Users affected per quarter - **Impact**: massive/high/medium/low/minimal - **Confidence**: high/medium/low - **Effort**: xl/l/m/s/xs (person-months)3. **Analyze Portfolio** - Review quick wins vs big bets - Check effort distribution - Validate against strategy4. **Generate Roadmap** - Quarterly capacity planning - Dependency mapping - Stakeholder alignment### Customer Discovery Process1. **Conduct Interviews** - Use semi-structured format - Focus on problems, not solutions - Record with permission2. **Analyze Insights** ```bash python scripts/customer_interview_analyzer.py transcript.txt ``` Extracts: - Pain points with severity - Feature requests with priority - Jobs to be done - Sentiment analysis - Key themes and quotes3. **Synthesize Findings** - Group similar pain points - Identify patterns across interviews - Map to opportunity areas4. **Validate Solutions** - Create solution hypotheses - Test with prototypes - Measure actual vs expected behavior### PRD Development Process1. **Choose Template** - **Standard PRD**: Complex features (6-8 weeks) - **One-Page PRD**: Simple features (2-4 weeks) - **Feature Brief**: Exploration phase (1 week) - **Agile Epic**: Sprint-based delivery2. **Structure Content** - Problem → Solution → Success Metrics - Always include out-of-scope - Clear acceptance criteria3. **Collaborate** - Engineering for feasibility - Design for experience - Sales for market validation - Support for operational impact## Key Scripts### rice_prioritizer.pyAdvanced RICE framework implementation with portfolio analysis.**Features**:- RICE score calculation- Portfolio balance analysis (quick wins vs big bets)- Quarterly roadmap generation- Team capacity planning- Multiple output formats (text/json/csv)**Usage Examples**:```bash# Basic prioritizationpython scripts/rice_prioritizer.py features.csv# With custom team capacity (person-months per quarter)python scripts/rice_prioritizer.py features.csv --capacity 20# Output as JSON for integrationpython scripts/rice_prioritizer.py features.csv --output json```### customer_interview_analyzer.pyNLP-based interview analysis for extracting actionable insights.**Capabilities**:- Pain point extraction with severity assessment- Feature request identification and classification- Jobs-to-be-done pattern recognition- Sentiment analysis- Theme extraction- Competitor mentions- Key quotes identification**Usage Examples**:```bash# Analyze single interviewpython scripts/customer_interview_analyzer.py interview.txt# Output as JSON for aggregationpython scripts/customer_interview_analyzer.py interview.txt json```## Reference Documents### prd_templates.mdMultiple PRD formats for different contexts:1. **Standard PRD Template** - Comprehensive 11-section format - Best for major features - Includes technical specs2. **One-Page PRD** - Concise format for quick alignment - Focus on problem/solution/metrics - Good for smaller features3. **Agile Epic Template** - Sprint-based delivery - User story mapping - Acceptance criteria focus4. **Feature Brief** - Lightweight exploration - Hypothesis-driven - Pre-PRD phase## Prioritization Frameworks### RICE Framework```Score = (Reach × Impact × Confidence) / EffortReach: # of users/quarterImpact: - Massive = 3x - High = 2x - Medium = 1x - Low = 0.5x - Minimal = 0.25xConfidence: - High = 100% - Medium = 80% - Low = 50%Effort: Person-months```### Value vs Effort Matrix``` Low Effort High Effort High QUICK WINS BIG BETSValue [Prioritize] [Strategic] Low FILL-INS TIME SINKSValue [Maybe] [Avoid]```### MoSCoW Method- **Must Have**: Critical for launch- **Should Have**: Important but not critical- **Could Have**: Nice to have- **Won't Have**: Out of scope## Discovery Frameworks### Customer Interview Guide```1. Context Questions (5 min) - Role and responsibilities - Current workflow - Tools used2. Problem Exploration (15 min) - Pain points - Frequency and impact - Current workarounds3. Solution Validation (10 min) - Reaction to concepts - Value perception - Willingness to pay4. Wrap-up (5 min) - Other thoughts - Referrals - Follow-up permission```### Hypothesis Template```We believe that [building this feature]For [these users]Will [achieve this outcome]We'll know we're right when [metric]```### Opportunity Solution Tree```Outcome├── Opportunity 1│ ├── Solution A│ └── Solution B└── Opportunity 2 ├── Solution C └── Solution D```## Metrics & Analytics### North Star Metric Framework1. **Identify Core Value**: What's the #1 value to users?2. **Make it Measurable**: Quantifiable and trackable3. **Ensure It's Actionable**: Teams can influence it4. **Check Leading Indicator**: Predicts business success### Funnel Analysis Template```Acquisition → Activation → Retention → Revenue → ReferralKey Metrics:- Conversion rate at each step- Drop-off points- Time between steps- Cohort variations```### Feature Success Metrics- **Adoption**: % of users using feature- **Frequency**: Usage per user per time period- **Depth**: % of feature capability used- **Retention**: Continued usage over time- **Satisfaction**: NPS/CSAT for feature## Best Practices### Writing Great PRDs1. Start with the problem, not solution2. Include clear success metrics upfront3. Explicitly state what's out of scope4. Use visuals (wireframes, flows)5. Keep technical details in appendix6. Version control changes### Effective Prioritization1. Mix quick wins with strategic bets2. Consider opportunity cost3. Account for dependencies4. Buffer for unexpected work (20%)5. Revisit quarterly6. Communicate decisions clearly### Customer Discovery Tips1. Ask "why" 5 times2. Focus on past behavior, not future intentions3. Avoid leading questions4. Interview in their enprojectnment5. Look for emotional reactions6. Validate with data### Stakeholder Management1. Identify RACI for decisions2. Regular async updates3. Demo over documentation4. Address concerns early5. Celebrate wins publicly6. Learn from failures openly## Common Pitfalls to Avoid1. **Solution-First Thinking**: Jumping to features before understanding problems2. **Analysis Paralysis**: Over-researching without shipping3. **Feature Factory**: Shipping features without measuring impact4. **Ignoring Technical Debt**: Not allocating time for platform health5. **Stakeholder Surprise**: Not communicating early and often6. **Metric Theater**: Optimizing vanity metrics over real value## Integration PointsThis toolkit integrates with:- **Analytics**: Amplitude, Mixpanel, Google Analytics- **Roadmapping**: ProductBoard, Aha!, Roadmunk- **Design**: Figma, Sketch, Miro- **Development**: Jira, Linear, GitHub- **Research**: Dovetail, UserVoice, Pendo- **Communication**: Slack, Notion, Confluence## Quick Commands Cheat Sheet```bash# Prioritizationpython scripts/rice_prioritizer.py features.csv --capacity 15# Interview Analysispython scripts/customer_interview_analyzer.py interview.txt# Create sample datapython scripts/rice_prioritizer.py sample# JSON outputs for integrationpython scripts/rice_prioritizer.py features.csv --output jsonpython scripts/customer_interview_analyzer.py interview.txt json```## When to UseThis skill is applicable to execute the workflow or actions described in the overview.## Limitations- Use this skill only when the task clearly matches the scope described above.- Do not treat the output as a substitute for enprojectnment-specific validation, testing, or expert review.- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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