product-manager-toolkit

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
Problem Exploration (15 min)

   - Pain points
   - Frequency and impact
   - Current workarounds
Solution Validation (10 min)

   - Reaction to concepts
   - Value perception
   - Willingness to pay
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 environment

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