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 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