product-manager-toolkit

Product Manager Toolkit

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

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Table of Contents

• [Quick Start](#quick-start)
• [Core Workflows](#core-workflows)
• [Feature Prioritization](#feature-prioritization-process)
• [Customer Discovery](#customer-discovery-process)
• [PRD Development](#prd-development-process)
• [Tools Reference](#tools-reference)
• [RICE Prioritizer](#rice-prioritizer)
• [Customer Interview Analyzer](#customer-interview-analyzer)
• [Input/Output Examples](#inputoutput-examples)
• [Integration Points](#integration-points)
• [Common Pitfalls](#common-pitfalls-to-avoid)

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Clarify First

Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• [ ] Which deliverable — RICE prioritization, interview synthesis, PRD, or positioning statement (sets which workflow, template, and inputs apply)
• [ ] The core problem and who has it — one sentence in the user's words (drives the PRD problem statement and JTBD)
• [ ] Success metric — the measurable outcome that defines "it worked" (drives PRD success metrics and RICE impact)
• [ ] Scope boundary — what is explicitly out (drives RICE effort estimates and PRD out-of-scope)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

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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Positioning Statement Framework

Create a Geoffrey Moore-style positioning statement to clarify product differentiation and value. Use this before writing PRDs, go-to-market plans, or pitch decks.

Core Positioning Template

For [target user/persona]
who [underserved need or painful moment],
[product name] is a [product category]
that [primary outcome delivered].
Unlike [main alternative: competitor, workaround, or status quo],
[product name] [unique differentiation in outcome terms].

One-Sentence Value Proposition

Write a single sentence a PM can reuse in docs and slides.

Differentiation Proof Points

List 3 concrete proof points that support the "unlike" claim. Focus on outcomes and evidence, not adjectives.

Writing Rules

• Use persona-first language.
• Focus on outcomes, not feature lists.
• Keep wording specific and testable.
• "Unlike X" should name the real alternative, including status quo.
• Strong differentiation is about outcomes and evidence, not adjectives.

Optional Variants

• Executive variant: Shorter strategic wording for board decks.
• Customer-facing variant: Clear plain-language wording for marketing.

Next Steps

1. Generate 3 alternate positioning directions (Recommended)
2. Create a competitor comparison message matrix
3. Convert into homepage headline + subheadline options

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Recommendation Canvas

Evaluate product opportunities holistically using a structured canvas that connects problem framing to solution evidence. Useful for investment decisions, portfolio reviews, and stakeholder alignment.

Canvas Sections

## Product Name
[Name of the product or service]

## Business Outcome
[Direction] [Metric] [Outcome] [Context] [Acceptance criteria]

## Product Outcome
[Direction] [Metric] [Outcome] [Context] [Acceptance criteria]

## Problem Statement Narrative
[2-3 sentences telling the persona's story from their point-of-view]

## Solution Hypothesis
If we [action/solution] for [target persona],
then we will [desirable outcome].

### Tiny Acts of Discovery
- [Small experiment focused on viability]
- [Small experiment focused on customer value]

### Proof-of-Life
Within [timeframe], we observe:
- [Quantitative measurable outcome]
- [Qualitative measurable outcome]

## Positioning Statement
For [target persona] that need [underserved need],
[product] is a [category] that [benefit].
Unlike [competitor], [product] provides [differentiation].

## Assumptions & Unknowns
- [Assumption 1]
- [Assumption 2]

## Issues/Risks (PESTEL lens)
- Political: [Risk]
- Economic: [Risk]
- Social: [Risk]
- Technological: [Risk]
- Environmental: [Risk]
- Legal: [Risk]

## Value Justification
[Yes/Yes with caveats/No with alternatives/No]
Justification: [Why this is or isn't valuable]

## Success Metrics
1. [SMART metric 1]
2. [SMART metric 2]
3. [SMART metric 3]

## What's Next
1. [Next step with owner]
2. [Next step with owner]

When to Use

• Evaluating whether to invest in a new product or feature.
• Preparing for portfolio review or investment committee.
• Aligning stakeholders on go/no-go decisions.

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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

---

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 |