product-manager-toolkit（产品经理工具包）

Product Manager Toolkit

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

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

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

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:

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

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

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.

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

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)

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

Integration Points

Compatible tools and platforms:

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

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.)

Tool Reference

rice_prioritizer.py

RICE framework implementation with portfolio analysis and quarterly roadmap generation.

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.

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

Troubleshooting

Success Criteria

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)

Integration Points