Product Manager Toolkit

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

Quick Start
Core Workflows
- Feature Prioritization
- Customer Discovery
- PRD Development
Tools Reference
- RICE Prioritizer
- Customer Interview Analyzer
Input/Output Examples
Integration Points
Common Pitfalls

Quick Start

For Feature Prioritization

# Create sample data file
python scripts/rice_prioritizer.py sample

# Run prioritization with team capacity
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 sections based on discovery work
Review with engineering for feasibility
Version control in project management tool

Core Workflows

Feature Prioritization Process

Gather → Score → Analyze → Plan → Validate → Execute

Step 1: Gather Feature Requests

Customer feedback (support tickets, interviews)
Sales requests (CRM pipeline blockers)
Technical debt (engineering input)
Strategic initiatives (leadership goals)

Step 2: Score with RICE

# Input: CSV with features
python scripts/rice_prioritizer.py features.csv --capacity 20

See references/frameworks.md for RICE formula and scoring guidelines.

Step 3: Analyze Portfolio

Review the tool output for:

Quick wins vs big bets distribution
Effort concentration (avoid all XL projects)
Strategic alignment gaps

Step 4: Generate Roadmap

Quarterly capacity allocation
Dependency identification
Stakeholder communication plan

Step 5: Validate Results

Before finalizing the roadmap:

Compare top priorities against strategic goals
Run sensitivity analysis (what if estimates are wrong by 2x?)
Review with key stakeholders for blind spots
Check for missing dependencies between features
Validate effort estimates with engineering

Step 6: Execute and Iterate

Share roadmap with team
Track actual vs estimated effort
Revisit priorities quarterly
Update RICE inputs based on learnings

Customer Discovery Process

Plan → Recruit → Interview → Analyze → Synthesize → Validate

Step 1: Plan Research

Define research questions
Identify target segments
Create interview script (see references/frameworks.md)

Step 2: Recruit Participants

5-8 interviews per segment
Mix of power users and churned users
Incentivize appropriately

Step 3: Conduct Interviews

Use semi-structured format
Focus on problems, not solutions
Record with permission
Take minimal notes during interview

Step 4: Analyze Insights

python scripts/customer_interview_analyzer.py transcript.txt

Extracts:

Pain points with severity
Feature requests with priority
Jobs to be done patterns
Sentiment and key themes
Notable quotes

Step 5: Synthesize Findings

Group similar pain points across interviews
Identify patterns (3+ mentions = pattern)
Map to opportunity areas using Opportunity Solution Tree
Prioritize opportunities by frequency and severity

Step 6: Validate Solutions

Before building:

Create solution hypotheses (see references/frameworks.md)
Test with low-fidelity prototypes
Measure actual behavior vs stated preference
Iterate based on feedback
Document learnings for future research

PRD Development Process

Scope → Draft → Review → Refine → Approve → Track

Step 1: Choose Template

Select from references/prd_templates.md:

Template	Use Case	Timeline
Standard PRD	Complex features, cross-team	6-8 weeks
One-Page PRD	Simple features, single team	2-4 weeks
Feature Brief	Exploration phase	1 week
Agile Epic	Sprint-based delivery	Ongoing

Step 2: Draft Content

Lead with problem statement
Define success metrics upfront
Explicitly state out-of-scope items
Include wireframes or mockups

Step 3: Review Cycle

Engineering: feasibility and effort
Design: user experience gaps
Sales: market validation
Support: operational impact

Step 4: Refine Based on Feedback

Address technical constraints
Adjust scope to fit timeline
Document trade-off decisions

Step 5: Approval and Kickoff

Stakeholder sign-off
Sprint planning integration
Communication to broader team

Step 6: Track Execution

After launch:

Compare actual metrics vs targets
Conduct user feedback sessions
Document what worked and what didn't
Update estimation accuracy data
Share learnings with team

Tools Reference

RICE Prioritizer

Advanced RICE framework implementation with portfolio analysis.

Features:

RICE score calculation with configurable weights
Portfolio balance analysis (quick wins vs big bets)
Quarterly roadmap generation based on capacity
Multiple output formats (text, JSON, CSV)

CSV Input Format:

name,reach,impact,confidence,effort,description
User Dashboard Redesign,5000,high,high,l,Complete redesign
Mobile Push Notifications,10000,massive,medium,m,Add push support
Dark Mode,8000,medium,high,s,Dark theme option

Commands:

# Create sample data
python scripts/rice_prioritizer.py sample

# Run with default capacity (10 person-months)
python scripts/rice_prioritizer.py features.csv

# Custom capacity
python scripts/rice_prioritizer.py features.csv --capacity 20

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

# CSV output for spreadsheets
python scripts/rice_prioritizer.py features.csv --output csv

Customer Interview Analyzer

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 per section
Theme and quote extraction
Competitor mention detection

Commands:

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

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

Input/Output Examples

→ See references/input-output-examples.md for details

Integration Points

Compatible tools and platforms:

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

JSON export enables integration with most tools:

# Export for Jira import
python scripts/rice_prioritizer.py features.csv --output json > priorities.json

# Export for dashboard
python scripts/customer_interview_analyzer.py interview.txt json > insights.json

Common Pitfalls to Avoid

Pitfall	Description	Prevention
Solution-First	Jumping to features before understanding problems	Start every PRD with problem statement
Analysis Paralysis	Over-researching without shipping	Set time-boxes for research phases
Feature Factory	Shipping features without measuring impact	Define success metrics before building
Ignoring Tech Debt	Not allocating time for platform health	Reserve 20% capacity for maintenance
Stakeholder Surprise	Not communicating early and often	Weekly async updates, monthly demos
Metric Theater	Optimizing vanity metrics over real value	Tie metrics to user value delivered

Best Practices

Writing Great PRDs:

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

Effective Prioritization:

Mix quick wins with strategic bets
Consider opportunity cost of delays
Account for dependencies between features
Buffer 20% for unexpected work
Revisit priorities quarterly
Communicate decisions with context

Customer Discovery:

Ask "why" five times to find root cause
Focus on past behavior, not future intentions
Avoid leading questions ("Wouldn't you love...")
Interview in the user's natural environment
Watch for emotional reactions (pain = opportunity)
Validate qualitative with quantitative data

Quick Reference

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

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

# Generate sample data
python scripts/rice_prioritizer.py sample

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

Reference Documents

references/prd_templates.md - PRD templates for different contexts
references/frameworks.md - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)