Product Manager Toolkit

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

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Table of Contents

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

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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

1. Choose template from references/prd_templates.md
2. Fill sections based on discovery work
3. Review with engineering for feasibility
4. Version control in project management tool

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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

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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

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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

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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

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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

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Input/Output Examples

RICE Prioritizer Example

Input (features.csv):

name,reach,impact,confidence,effort
Onboarding Flow,20000,massive,high,s
Search Improvements,15000,high,high,m
Social Login,12000,high,medium,m
Push Notifications,10000,massive,medium,m
Dark Mode,8000,medium,high,s

Command:

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

Output:

============================================================
RICE PRIORITIZATION RESULTS
============================================================

📊 TOP PRIORITIZED FEATURES

1. Onboarding Flow
   RICE Score: 16000.0
   Reach: 20000 | Impact: massive | Confidence: high | Effort: s

2. Search Improvements
   RICE Score: 4800.0
   Reach: 15000 | Impact: high | Confidence: high | Effort: m

3. Social Login
   RICE Score: 3072.0
   Reach: 12000 | Impact: high | Confidence: medium | Effort: m

4. Push Notifications
   RICE Score: 3840.0
   Reach: 10000 | Impact: massive | Confidence: medium | Effort: m

5. Dark Mode
   RICE Score: 2133.33
   Reach: 8000 | Impact: medium | Confidence: high | Effort: s

📈 PORTFOLIO ANALYSIS

Total Features: 5
Total Effort: 19 person-months
Total Reach: 65,000 users
Average RICE Score: 5969.07

🎯 Quick Wins: 2 features
   • Onboarding Flow (RICE: 16000.0)
   • Dark Mode (RICE: 2133.33)

🚀 Big Bets: 0 features

📅 SUGGESTED ROADMAP

Q1 - Capacity: 11/15 person-months
   • Onboarding Flow (RICE: 16000.0)
   • Search Improvements (RICE: 4800.0)
   • Dark Mode (RICE: 2133.33)

Q2 - Capacity: 10/15 person-months
   • Push Notifications (RICE: 3840.0)
   • Social Login (RICE: 3072.0)

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Customer Interview Analyzer Example

Input (interview.txt):

Customer: Jane, Enterprise PM at TechCorp
Date: 2024-01-15

Interviewer: What's the hardest part of your current workflow?

Jane: The biggest frustration is the lack of real-time collaboration.
When I'm working on a PRD, I have to constantly ping my team on Slack
to get updates. It's really frustrating to wait for responses,
especially when we're on a tight deadline.

I've tried using Google Docs for collaboration, but it doesn't
integrate with our roadmap tools. I'd pay extra for something that
just worked seamlessly.

Interviewer: How often does this happen?

Jane: Literally every day. I probably waste 30 minutes just on
back-and-forth messages. It's my biggest pain point right now.

Command:

python scripts/customer_interview_analyzer.py interview.txt

Output:

============================================================
CUSTOMER INTERVIEW ANALYSIS
============================================================

📋 INTERVIEW METADATA
Segments found: 1
Lines analyzed: 15

😟 PAIN POINTS (3 found)

1. [HIGH] Lack of real-time collaboration
   "I have to constantly ping my team on Slack to get updates"

2. [MEDIUM] Tool integration gaps
   "Google Docs...doesn't integrate with our roadmap tools"

3. [HIGH] Time wasted on communication
   "waste 30 minutes just on back-and-forth messages"

💡 FEATURE REQUESTS (2 found)

1. Real-time collaboration - Priority: High
2. Seamless tool integration - Priority: Medium

🎯 JOBS TO BE DONE

When working on PRDs with tight deadlines
I want real-time visibility into team updates
So I can avoid wasted time on status checks

📊 SENTIMENT ANALYSIS

Overall: Negative (pain-focused interview)
Key emotions: Frustration, Time pressure

💬 KEY QUOTES

• "It's really frustrating to wait for responses"
• "I'd pay extra for something that just worked seamlessly"
• "It's my biggest pain point right now"

🏷️ THEMES

- Collaboration friction
- Tool fragmentation
- Time efficiency

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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

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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

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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

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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

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Reference Documents

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

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Tool Reference

rice_prioritizer.py

RICE framework implementation with portfolio analysis and quarterly roadmap generation.

Flag	Type	Default	Description
input	positional	(optional)	CSV file with features or "sample" to create sample
--capacity	int	10	Team capacity per quarter in person-months
--output	choice	text	Output format: text, json, csv

CSV columns: name, reach, impact, confidence, effort, description

Impact values: massive, high, medium, low, minimal Confidence values: high (100%), medium (80%), low (50%) Effort values: xl (13mo), l (8mo), m (5mo), s (3mo), xs (1mo)

python scripts/rice_prioritizer.py sample                          # Create sample CSV
python scripts/rice_prioritizer.py features.csv                    # Default capacity (10)
python scripts/rice_prioritizer.py features.csv --capacity 20      # Custom capacity
python scripts/rice_prioritizer.py features.csv --output json      # JSON for integration
python scripts/rice_prioritizer.py features.csv --output csv       # CSV for spreadsheets

customer_interview_analyzer.py

Keyword-based interview transcript analysis for extracting actionable insights.

Argument	Type	Default	Description
interview_file	positional	(required)	Path to interview transcript text file
json	positional	(optional)	Add "json" as second arg for JSON output

Extraction capabilities: pain points (with severity), feature requests (with type and priority), jobs-to-be-done patterns, sentiment analysis, key themes, notable quotes, metrics mentioned, competitor mentions.

python scripts/customer_interview_analyzer.py interview.txt        # Human-readable
python scripts/customer_interview_analyzer.py interview.txt json   # JSON output

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Troubleshooting

Problem	Cause	Solution
RICE scores cluster together	Impact/confidence not differentiated enough	Calibrate scoring rubric with team; use specific examples for each level
Roadmap overcommits capacity	Effort estimates too optimistic	Add 20% buffer; validate estimates with engineering before finalizing
Interview analysis misses key insights	Transcript is too short or uses unexpected phrasing	Supplement with manual review; ensure transcripts capture full context
Stakeholders disagree with priorities	Different value perceptions	Share raw RICE inputs transparently; allow stakeholders to adjust weights
Quick wins dominate roadmap	Bias toward low-effort items	Reserve 30-40% of capacity for strategic big bets
PRD scope creeps after approval	Insufficient out-of-scope definition	Explicitly list excluded items; require change request for additions
Feature factory behavior	Shipping without measuring impact	Define success metrics in PRD before development starts

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Success Criteria

Criterion	Target	How to Measure
Prioritization velocity	<2 hours from data to ranked backlog	Time from CSV input to roadmap output
Interview analysis coverage	>80% of pain points captured	Compare tool output to manual expert review
Estimation accuracy	Actual effort within 1.5x of RICE estimate	Track actual vs estimated effort post-delivery
Roadmap confidence	>70% of Q1 roadmap items shipped in quarter	Shipped items / Planned items
Discovery cadence	5-8 interviews per segment per quarter	Count completed interviews
PRD quality	0 scope change requests after approval	Track change requests per PRD
Feature impact rate	>60% of shipped features hit success metrics	Post-launch metric comparison

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Scope & Limitations

In scope:

• RICE prioritization with portfolio analysis
• Quarterly roadmap generation with capacity planning
• Customer interview transcript analysis
• Pain point, feature request, and JTBD extraction
• Sentiment analysis using keyword heuristics
• PRD development process and templates
• CSV/JSON import and export

Out of scope:

• Real-time analytics integration (use Amplitude/Mixpanel APIs)
• NLP model-based analysis (tool uses keyword heuristics, not ML)
• Multi-language transcript analysis (English only)
• Visual wireframe or prototype generation
• Competitive intelligence gathering (see business-growth skills)
• Revenue impact modeling (see finance skills)

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Integration Points

Tool / Platform	Integration Method	Use Case
Jira / Linear	--output json from rice_prioritizer	Import prioritized features as tickets
Google Sheets	--output csv from rice_prioritizer	Share roadmap with stakeholders
Dovetail / Notion	JSON output from interview analyzer	Aggregate interview insights in research repo
agile-product-owner	RICE priorities feed sprint backlog	Connect strategy to execution
product-strategist	OKR cascade informs RICE reach/impact	Align features with strategic objectives
Slack / Email	Human-readable output from both tools	Async stakeholder communication