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Product Manager Toolkit

产品经理工具包

Essential tools and frameworks for modern product management, from discovery to delivery.
面向现代产品管理的必备工具与框架，覆盖从探索到交付的全流程。

Quick Start

快速开始

For Feature Prioritization

功能优先级排序

bash
python scripts/rice_prioritizer.py sample  # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
bash
python scripts/rice_prioritizer.py sample  # 创建示例CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15

For Interview Analysis

访谈分析

bash
python scripts/customer_interview_analyzer.py interview_transcript.txt
bash
python scripts/customer_interview_analyzer.py interview_transcript.txt

For PRD Creation

PRD创建

  1. Choose template from 
    references/prd_templates.md
  2. Fill in sections based on discovery work
  3. Review with stakeholders
  4. Version control in your PM tool
  1. 从
    references/prd_templates.md
    中选择模板
  2. 根据探索工作填充各章节内容
  3. 与相关利益方一同评审
  4. 在你的PM工具中进行版本控制

Core Workflows

核心工作流

Feature Prioritization Process

功能优先级排序流程

  1. Gather Feature Requests
    • Customer feedback
    • Sales requests
    • Technical debt
    • Strategic initiatives
  2. Score with RICE
    bash
    # 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)
  3. Analyze Portfolio
    • Review quick wins vs big bets
    • Check effort distribution
    • Validate against strategy
  4. Generate Roadmap
    • Quarterly capacity planning
    • Dependency mapping
    • Stakeholder alignment
  1. 收集功能需求
    • 客户反馈
    • 销售需求
    • 技术债务
    • 战略举措
  2. 使用RICE评分
    bash
    # 创建包含以下字段的CSV：name,reach,impact,confidence,effort
python scripts/rice_prioritizer.py features.csv
    • Reach（覆盖用户数）：每季度受影响的用户数量
    • Impact（影响程度）：massive/高/medium/中/low/低/minimal/极小
    • Confidence（置信度）：high/高/medium/中/low/低
    • Effort（投入成本）：xl/超大/l/大/m/中/s/小/xs/极小（人月）
  3. 分析产品组合
    • 评估快速成果与重大赌注
    • 检查投入成本分布
    • 结合战略进行验证
  4. 生成路线图
    • 季度产能规划
    • 依赖关系映射
    • 利益方对齐

Customer Discovery Process

客户探索流程

  1. Conduct Interviews
    • Use semi-structured format
    • Focus on problems, not solutions
    • Record with permission
  2. Analyze Insights
    bash
    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
  3. Synthesize Findings
    • Group similar pain points
    • Identify patterns across interviews
    • Map to opportunity areas
  4. Validate Solutions
    • Create solution hypotheses
    • Test with prototypes
    • Measure actual vs expected behavior
  1. 开展访谈
    • 使用半结构化格式
    • 聚焦问题而非解决方案
    • 经许可后进行录制
  2. 分析洞察
    bash
    python scripts/customer_interview_analyzer.py transcript.txt
    提取内容包括：
    • 带严重程度的痛点
    • 带优先级的功能需求
    • 用户待办任务
    • 情感分析
    • 核心主题与引用
  3. 整合发现成果
    • 归类相似痛点
    • 识别跨访谈的模式
    • 映射到机会领域
  4. 验证解决方案
    • 创建解决方案假设
    • 通过原型进行测试
    • 衡量实际表现与预期行为

PRD Development Process

PRD开发流程

  1. 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
  2. Structure Content
    • Problem → Solution → Success Metrics
    • Always include out-of-scope
    • Clear acceptance criteria
  3. Collaborate
    • Engineering for feasibility
    • Design for experience
    • Sales for market validation
    • Support for operational impact
  1. 选择模板
    • 标准PRD：复杂功能（6-8周）
    • 单页PRD：简单功能（2-4周）
    • 功能简报：探索阶段（1周）
    • 敏捷史诗：基于迭代的交付
  2. 内容结构
    • 问题 → 解决方案 → 成功指标
    • 务必包含范围外内容
    • 清晰的验收标准
  3. 协作
    • 与工程团队确认可行性
    • 与设计团队优化体验
    • 与销售团队进行市场验证
    • 与支持团队评估运营影响

Key Scripts

核心脚本

rice_prioritizer.py

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:
bash
undefined
带产品组合分析的高级RICE框架实现。
功能:
  • RICE分数计算
  • 产品组合平衡分析（快速成果vs重大赌注）
  • 季度路线图生成
  • 团队产能规划
  • 多种输出格式（文本/json/csv）
使用示例:
bash
undefined

Basic prioritization

基础优先级排序

python scripts/rice_prioritizer.py features.csv
python scripts/rice_prioritizer.py features.csv

With custom team capacity (person-months per quarter)

自定义团队产能（每季度人月）

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

Output as JSON for integration

输出为JSON用于集成

python scripts/rice_prioritizer.py features.csv --output json
undefined
python scripts/rice_prioritizer.py features.csv --output json
undefined

customer_interview_analyzer.py

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:
bash
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基于NLP的访谈分析工具，用于提取可执行洞察。
能力:
  • 提取带严重程度评估的痛点
  • 识别并分类功能需求
  • 识别用户待办任务模式
  • 情感分析
  • 主题提取
  • 竞品提及识别
  • 关键引用识别
使用示例:
bash
undefined

Analyze single interview

分析单个访谈

python scripts/customer_interview_analyzer.py interview.txt
python scripts/customer_interview_analyzer.py interview.txt

Output as JSON for aggregation

输出为JSON用于聚合

python scripts/customer_interview_analyzer.py interview.txt json
undefined
python scripts/customer_interview_analyzer.py interview.txt json
undefined

Reference Documents

参考文档

prd_templates.md

prd_templates.md

Multiple PRD formats for different contexts:
  1. Standard PRD Template
    • Comprehensive 11-section format
    • Best for major features
    • Includes technical specs
  2. One-Page PRD
    • Concise format for quick alignment
    • Focus on problem/solution/metrics
    • Good for smaller features
  3. Agile Epic Template
    • Sprint-based delivery
    • User story mapping
    • Acceptance criteria focus
  4. Feature Brief
    • Lightweight exploration
    • Hypothesis-driven
    • Pre-PRD phase
适用于不同场景的多种PRD格式：
  1. 标准PRD模板
    • 包含11个章节的全面格式
    • 最适合重大功能
    • 包含技术规格
  2. 单页PRD
    • 用于快速对齐的简洁格式
    • 聚焦问题/解决方案/指标
    • 适合小型功能
  3. 敏捷史诗模板
    • 基于迭代的交付
    • 用户故事映射
    • 聚焦验收标准
  4. 功能简报
    • 轻量级探索
    • 假设驱动
    • PRD前阶段

Prioritization Frameworks

优先级排序框架

RICE Framework

RICE框架

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
分数 = (覆盖用户数 × 影响程度 × 置信度) / 投入成本

覆盖用户数：每季度用户数量
影响程度: 
  - Massive = 3倍
  - High = 2倍
  - Medium = 1倍
  - Low = 0.5倍
  - Minimal = 0.25倍
置信度:
  - High = 100%
  - Medium = 80%
  - Low = 50%
投入成本：人月

Value vs Effort Matrix

价值vs投入成本矩阵

         Low Effort    High Effort
         
High     QUICK WINS    BIG BETS
Value    [Prioritize]   [Strategic]
         
Low      FILL-INS      TIME SINKS
Value    [Maybe]       [Avoid]
         低投入成本    高投入成本
         
高     快速成果    重大赌注
价值    [优先处理]   [战略级]
         
低      补充项      时间陷阱
价值    [可考虑]       [避免]

MoSCoW Method

MoSCoW方法

  • Must Have: Critical for launch
  • Should Have: Important but not critical
  • Could Have: Nice to have
  • Won't Have: Out of scope
  • Must Have（必备）：发布的关键需求
  • Should Have（应该有）：重要但非关键
  • Could Have（可以有）：锦上添花
  • Won't Have（不会有）：范围外

Discovery Frameworks

探索框架

Customer Interview Guide

客户访谈指南

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
1. 背景问题（5分钟）
   - 角色与职责
   - 当前工作流程
   - 使用的工具

2. 问题探索（15分钟）
   - 痛点
   - 发生频率与影响
   - 当前的解决办法

3. 解决方案验证（10分钟）
   - 对概念的反应
   - 价值感知
   - 付费意愿

4. 收尾（5分钟）
   - 其他想法
   - 推荐
   - 后续跟进许可

Hypothesis Template

假设模板

We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]
我们认为，[开发此功能]
针对[这类用户]
将[实现此成果]
当[该指标达成]时，我们就验证了假设

Opportunity Solution Tree

机会-解决方案树

Outcome
├── Opportunity 1
│   ├── Solution A
│   └── Solution B
└── Opportunity 2
    ├── Solution C
    └── Solution D
成果
├── 机会1
│   ├── 解决方案A
│   └── 解决方案B
└── 机会2
    ├── 解决方案C
    └── 解决方案D

Metrics & Analytics

指标与分析

North Star Metric Framework

北极星指标框架

  1. Identify Core Value: What's the #1 value to users?
  2. Make it Measurable: Quantifiable and trackable
  3. Ensure It's Actionable: Teams can influence it
  4. Check Leading Indicator: Predicts business success
  1. 识别核心价值：对用户来说，最重要的价值是什么？
  2. 使其可衡量：可量化且可追踪
  3. 确保可执行：团队可以对其产生影响
  4. 检查领先指标：可预测业务成功

Funnel Analysis Template

漏斗分析模板

Acquisition → Activation → Retention → Revenue → Referral

Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations
获取用户 → 激活 → 留存 → 变现 → 推荐

关键指标:
- 每个步骤的转化率
- 流失点
- 步骤间的时间间隔
- 群组差异

Feature Success Metrics

功能成功指标

  • 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
  • 采用率：使用该功能的用户占比
  • 使用频率：每个用户在特定时间段内的使用次数
  • 使用深度：使用到的功能能力占比
  • 留存率：持续使用的情况
  • 满意度：功能的NPS/CSAT评分

Best Practices

最佳实践

Writing Great PRDs

撰写优质PRD

  1. Start with the problem, not solution
  2. Include clear success metrics upfront
  3. Explicitly state what's out of scope
  4. Use visuals (wireframes, flows)
  5. Keep technical details in appendix
  6. Version control changes
  1. 从问题入手，而非解决方案
  2. 提前明确清晰的成功指标
  3. 明确说明范围外内容
  4. 使用可视化内容（线框图、流程图）
  5. 技术细节放在附录中
  6. 对变更进行版本控制

Effective Prioritization

有效的优先级排序

  1. Mix quick wins with strategic bets
  2. Consider opportunity cost
  3. Account for dependencies
  4. Buffer for unexpected work (20%)
  5. Revisit quarterly
  6. Communicate decisions clearly
  1. 结合快速成果与战略赌注
  2. 考虑机会成本
  3. 考虑依赖关系
  4. 为意外工作预留缓冲（20%）
  5. 每季度重新审视
  6. 清晰传达决策

Customer Discovery Tips

客户探索技巧

  1. Ask "why" 5 times
  2. Focus on past behavior, not future intentions
  3. Avoid leading questions
  4. Interview in their environment
  5. Look for emotional reactions
  6. Validate with data
  1. 连续问5次“为什么”
  2. 聚焦过去的行为而非未来的意图
  3. 避免诱导性问题
  4. 在用户的环境中进行访谈
  5. 留意情绪反应
  6. 用数据验证

Stakeholder Management

利益方管理

  1. Identify RACI for decisions
  2. Regular async updates
  3. Demo over documentation
  4. Address concerns early
  5. Celebrate wins publicly
  6. Learn from failures openly
  1. 明确决策的RACI（负责人、批准人、咨询人、告知人）
  2. 定期异步更新
  3. 用演示代替文档
  4. 尽早解决顾虑
  5. 公开庆祝成果
  6. 坦诚从失败中学习

Common Pitfalls to Avoid

需避免的常见陷阱

  1. Solution-First Thinking: Jumping to features before understanding problems
  2. Analysis Paralysis: Over-researching without shipping
  3. Feature Factory: Shipping features without measuring impact
  4. Ignoring Technical Debt: Not allocating time for platform health
  5. Stakeholder Surprise: Not communicating early and often
  6. Metric Theater: Optimizing vanity metrics over real value
  1. 先解决方案后问题：在理解问题前就跳到功能开发
  2. 分析瘫痪：过度研究而不落地
  3. 功能工厂：只发布功能而不衡量影响
  4. 忽略技术债务：不为平台健康分配时间
  5. 利益方意外：未尽早且频繁沟通
  6. 指标假象：优化虚荣指标而非实际价值

Integration Points

集成点

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
此工具包可与以下工具集成：
  • 分析工具：Amplitude, Mixpanel, Google Analytics
  • 路线图工具：ProductBoard, Aha!, Roadmunk
  • 设计工具：Figma, Sketch, Miro
  • 开发工具：Jira, Linear, GitHub
  • 研究工具：Dovetail, UserVoice, Pendo
  • 沟通工具：Slack, Notion, Confluence

Quick Commands Cheat Sheet

快速命令 cheat sheet

bash
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bash
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Prioritization

优先级排序

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

Interview Analysis

访谈分析

python scripts/customer_interview_analyzer.py interview.txt
python scripts/customer_interview_analyzer.py interview.txt

Create sample data

创建示例数据

python scripts/rice_prioritizer.py sample
python scripts/rice_prioritizer.py sample

JSON outputs for integration

输出JSON用于集成

python scripts/rice_prioritizer.py features.csv --output json python scripts/customer_interview_analyzer.py interview.txt json
undefined
python scripts/rice_prioritizer.py features.csv --output json python scripts/customer_interview_analyzer.py interview.txt json
undefined