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Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.","oabdelmaksoud\u002FAgention","oabdelmaksoud","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F50699149?v=4","01M6D5CVVN778ZCDP1WHS816SP","Omar Abdelmaksoud","01M6D8A4TE76V3DCSH3D94VG1V",2,"MIT","https:\u002F\u002Fgithub.com\u002Foabdelmaksoud\u002FAgention\u002Fblob\u002Fmain\u002Fupstream-import\u002Fclaude-skills\u002Freferences\u002Fproduct-team\u002Fproduct-manager-toolkit\u002FSKILL.md",[18,23,28],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000031","产品经理","PROFESSION","适用职业",{"categoryNo":29,"categoryName":30,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000038","人力资源",[32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],"toolkit","product","product manager toolkit","Product Manager","feature prioritization","go","go-to-market","user research","feature","strategies","frameworks","rice","interview","strategy","prioritization","discovery","analysis","development","documentation","customer","2026-11-10 10:12:30",false,"---\nname: product-manager-toolkit\ndescription: Comprehensive toolkit for product managers including RICE prioritization, customer interview analysis, PRD templates, discovery frameworks, and go-to-market strategies. Use for feature prioritization, user research synthesis, requirement documentation, and product strategy development.\n---\n\n# Product Manager Toolkit\n\nEssential tools and frameworks for modern product management, from discovery to delivery.\n\n---\n\n## Table of Contents\n\n- [Quick Start](#quick-start)\n- [Core Workflows](#core-workflows)\n  - [Feature Prioritization](#feature-prioritization-process)\n  - [Customer Discovery](#customer-discovery-process)\n  - [PRD Development](#prd-development-process)\n- [Tools Reference](#tools-reference)\n  - [RICE Prioritizer](#rice-prioritizer)\n  - [Customer Interview Analyzer](#customer-interview-analyzer)\n- [Input\u002FOutput Examples](#inputoutput-examples)\n- [Integration Points](#integration-points)\n- [Common Pitfalls](#common-pitfalls-to-avoid)\n\n---\n\n## Quick Start\n\n### For Feature Prioritization\n```bash\n# Create sample data file\npython scripts\u002Frice_prioritizer.py sample\n\n# Run prioritization with team capacity\npython scripts\u002Frice_prioritizer.py sample_features.csv --capacity 15\n```\n\n### For Interview Analysis\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py interview_transcript.txt\n```\n\n### For PRD Creation\n1. Choose template from `references\u002Fprd_templates.md`\n2. Fill sections based on discovery work\n3. Review with engineering for feasibility\n4. Version control in project management tool\n\n---\n\n## Core Workflows\n\n### Feature Prioritization Process\n\n```\nGather → Score → Analyze → Plan → Validate → Execute\n```\n\n#### Step 1: Gather Feature Requests\n- Customer feedback (support tickets, interviews)\n- Sales requests (CRM pipeline blockers)\n- Technical debt (engineering input)\n- Strategic initiatives (leadership goals)\n\n#### Step 2: Score with RICE\n```bash\n# Input: CSV with features\npython scripts\u002Frice_prioritizer.py features.csv --capacity 20\n```\n\nSee `references\u002Fframeworks.md` for RICE formula and scoring guidelines.\n\n#### Step 3: Analyze Portfolio\nReview the tool output for:\n- Quick wins vs big bets distribution\n- Effort concentration (avoid all XL projects)\n- Strategic alignment gaps\n\n#### Step 4: Generate Roadmap\n- Quarterly capacity allocation\n- Dependency identification\n- Stakeholder communication plan\n\n#### Step 5: Validate Results\n**Before finalizing the roadmap:**\n- [ ] Compare top priorities against strategic goals\n- [ ] Run sensitivity analysis (what if estimates are wrong by 2x?)\n- [ ] Review with key stakeholders for blind spots\n- [ ] Check for missing dependencies between features\n- [ ] Validate effort estimates with engineering\n\n#### Step 6: Execute and Iterate\n- Share roadmap with team\n- Track actual vs estimated effort\n- Revisit priorities quarterly\n- Update RICE inputs based on learnings\n\n---\n\n### Customer Discovery Process\n\n```\nPlan → Recruit → Interview → Analyze → Synthesize → Validate\n```\n\n#### Step 1: Plan Research\n- Define research questions\n- Identify target segments\n- Create interview script (see `references\u002Fframeworks.md`)\n\n#### Step 2: Recruit Participants\n- 5-8 interviews per segment\n- Mix of power users and churned users\n- Incentivize appropriately\n\n#### Step 3: Conduct Interviews\n- Use semi-structured format\n- Focus on problems, not solutions\n- Record with permission\n- Take minimal notes during interview\n\n#### Step 4: Analyze Insights\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py transcript.txt\n```\n\nExtracts:\n- Pain points with severity\n- Feature requests with priority\n- Jobs to be done patterns\n- Sentiment and key themes\n- Notable quotes\n\n#### Step 5: Synthesize Findings\n- Group similar pain points across interviews\n- Identify patterns (3+ mentions = pattern)\n- Map to opportunity areas using Opportunity Solution Tree\n- Prioritize opportunities by frequency and severity\n\n#### Step 6: Validate Solutions\n**Before building:**\n- [ ] Create solution hypotheses (see `references\u002Fframeworks.md`)\n- [ ] Test with low-fidelity prototypes\n- [ ] Measure actual behavior vs stated preference\n- [ ] Iterate based on feedback\n- [ ] Document learnings for future research\n\n---\n\n### PRD Development Process\n\n```\nScope → Draft → Review → Refine → Approve → Track\n```\n\n#### Step 1: Choose Template\nSelect from `references\u002Fprd_templates.md`:\n\n| Template | Use Case | Timeline |\n|----------|----------|----------|\n| Standard PRD | Complex features, cross-team | 6-8 weeks |\n| One-Page PRD | Simple features, single team | 2-4 weeks |\n| Feature Brief | Exploration phase | 1 week |\n| Agile Epic | Sprint-based delivery | Ongoing |\n\n#### Step 2: Draft Content\n- Lead with problem statement\n- Define success metrics upfront\n- Explicitly state out-of-scope items\n- Include wireframes or mockups\n\n#### Step 3: Review Cycle\n- Engineering: feasibility and effort\n- Design: user experience gaps\n- Sales: market validation\n- Support: operational impact\n\n#### Step 4: Refine Based on Feedback\n- Address technical constraints\n- Adjust scope to fit timeline\n- Document trade-off decisions\n\n#### Step 5: Approval and Kickoff\n- Stakeholder sign-off\n- Sprint planning integration\n- Communication to broader team\n\n#### Step 6: Track Execution\n**After launch:**\n- [ ] Compare actual metrics vs targets\n- [ ] Conduct user feedback sessions\n- [ ] Document what worked and what didn't\n- [ ] Update estimation accuracy data\n- [ ] Share learnings with team\n\n---\n\n## Tools Reference\n\n### RICE Prioritizer\n\nAdvanced RICE framework implementation with portfolio analysis.\n\n**Features:**\n- RICE score calculation with configurable weights\n- Portfolio balance analysis (quick wins vs big bets)\n- Quarterly roadmap generation based on capacity\n- Multiple output formats (text, JSON, CSV)\n\n**CSV Input Format:**\n```csv\nname,reach,impact,confidence,effort,description\nUser Dashboard Redesign,5000,high,high,l,Complete redesign\nMobile Push Notifications,10000,massive,medium,m,Add push support\nDark Mode,8000,medium,high,s,Dark theme option\n```\n\n**Commands:**\n```bash\n# Create sample data\npython scripts\u002Frice_prioritizer.py sample\n\n# Run with default capacity (10 person-months)\npython scripts\u002Frice_prioritizer.py features.csv\n\n# Custom capacity\npython scripts\u002Frice_prioritizer.py features.csv --capacity 20\n\n# JSON output for integration\npython scripts\u002Frice_prioritizer.py features.csv --output json\n\n# CSV output for spreadsheets\npython scripts\u002Frice_prioritizer.py features.csv --output csv\n```\n\n---\n\n### Customer Interview Analyzer\n\nNLP-based interview analysis for extracting actionable insights.\n\n**Capabilities:**\n- Pain point extraction with severity assessment\n- Feature request identification and classification\n- Jobs-to-be-done pattern recognition\n- Sentiment analysis per section\n- Theme and quote extraction\n- Competitor mention detection\n\n**Commands:**\n```bash\n# Analyze interview transcript\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n\n# JSON output for aggregation\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json\n```\n\n---\n\n## Input\u002FOutput Examples\n\n### RICE Prioritizer Example\n\n**Input (features.csv):**\n```csv\nname,reach,impact,confidence,effort\nOnboarding Flow,20000,massive,high,s\nSearch Improvements,15000,high,high,m\nSocial Login,12000,high,medium,m\nPush Notifications,10000,massive,medium,m\nDark Mode,8000,medium,high,s\n```\n\n**Command:**\n```bash\npython scripts\u002Frice_prioritizer.py features.csv --capacity 15\n```\n\n**Output:**\n```\n============================================================\nRICE PRIORITIZATION RESULTS\n============================================================\n\n? TOP PRIORITIZED FEATURES\n\n1. Onboarding Flow\n   RICE Score: 16000.0\n   Reach: 20000 | Impact: massive | Confidence: high | Effort: s\n\n2. Search Improvements\n   RICE Score: 4800.0\n   Reach: 15000 | Impact: high | Confidence: high | Effort: m\n\n3. Social Login\n   RICE Score: 3072.0\n   Reach: 12000 | Impact: high | Confidence: medium | Effort: m\n\n4. Push Notifications\n   RICE Score: 3840.0\n   Reach: 10000 | Impact: massive | Confidence: medium | Effort: m\n\n5. Dark Mode\n   RICE Score: 2133.33\n   Reach: 8000 | Impact: medium | Confidence: high | Effort: s\n\n? PORTFOLIO ANALYSIS\n\nTotal Features: 5\nTotal Effort: 19 person-months\nTotal Reach: 65,000 users\nAverage RICE Score: 5969.07\n\n? Quick Wins: 2 features\n   • Onboarding Flow (RICE: 16000.0)\n   • Dark Mode (RICE: 2133.33)\n\n? Big Bets: 0 features\n\n? SUGGESTED ROADMAP\n\nQ1 - Capacity: 11\u002F15 person-months\n   • Onboarding Flow (RICE: 16000.0)\n   • Search Improvements (RICE: 4800.0)\n   • Dark Mode (RICE: 2133.33)\n\nQ2 - Capacity: 10\u002F15 person-months\n   • Push Notifications (RICE: 3840.0)\n   • Social Login (RICE: 3072.0)\n```\n\n---\n\n### Customer Interview Analyzer Example\n\n**Input (interview.txt):**\n```\nCustomer: Jane, Enterprise PM at TechCorp\nDate: 2024-01-15\n\nInterviewer: What's the hardest part of your current workflow?\n\nJane: The biggest frustration is the lack of real-time collaboration.\nWhen I'm working on a PRD, I have to constantly ping my team on Slack\nto get updates. It's really frustrating to wait for responses,\nespecially when we're on a tight deadline.\n\nI've tried using Google Docs for collaboration, but it doesn't\nintegrate with our roadmap tools. I'd pay extra for something that\njust worked seamlessly.\n\nInterviewer: How often does this happen?\n\nJane: Literally every day. I probably waste 30 minutes just on\nback-and-forth messages. It's my biggest pain point right now.\n```\n\n**Command:**\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n```\n\n**Output:**\n```\n============================================================\nCUSTOMER INTERVIEW ANALYSIS\n============================================================\n\n? INTERVIEW METADATA\nSegments found: 1\nLines analyzed: 15\n\n? PAIN POINTS (3 found)\n\n1. [HIGH] Lack of real-time collaboration\n   \"I have to constantly ping my team on Slack to get updates\"\n\n2. [MEDIUM] Tool integration gaps\n   \"Google Docs...doesn't integrate with our roadmap tools\"\n\n3. [HIGH] Time wasted on communication\n   \"waste 30 minutes just on back-and-forth messages\"\n\n? FEATURE REQUESTS (2 found)\n\n1. Real-time collaboration - Priority: High\n2. Seamless tool integration - Priority: Medium\n\n? JOBS TO BE DONE\n\nWhen working on PRDs with tight deadlines\nI want real-time visibility into team updates\nSo I can avoid wasted time on status checks\n\n? SENTIMENT ANALYSIS\n\nOverall: Negative (pain-focused interview)\nKey emotions: Frustration, Time pressure\n\n? KEY QUOTES\n\n• \"It's really frustrating to wait for responses\"\n• \"I'd pay extra for something that just worked seamlessly\"\n• \"It's my biggest pain point right now\"\n\n?️ THEMES\n\n- Collaboration friction\n- Tool fragmentation\n- Time efficiency\n```\n\n---\n\n## Integration Points\n\nCompatible tools and platforms:\n\n| Category | Platforms |\n|----------|-----------|\n| **Analytics** | Amplitude, Mixpanel, Google Analytics |\n| **Roadmapping** | ProductBoard, Aha!, Roadmunk, Productplan |\n| **Design** | Figma, Sketch, Miro |\n| **Development** | Jira, Linear, GitHub, Asana |\n| **Research** | Dovetail, UserVoice, Pendo, Maze |\n| **Communication** | Slack, Notion, Confluence |\n\n**JSON export enables integration with most tools:**\n```bash\n# Export for Jira import\npython scripts\u002Frice_prioritizer.py features.csv --output json > priorities.json\n\n# Export for dashboard\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json > insights.json\n```\n\n---\n\n## Common Pitfalls to Avoid\n\n| Pitfall | Description | Prevention |\n|---------|-------------|------------|\n| **Solution-First** | Jumping to features before understanding problems | Start every PRD with problem statement |\n| **Analysis Paralysis** | Over-researching without shipping | Set time-boxes for research phases |\n| **Feature Factory** | Shipping features without measuring impact | Define success metrics before building |\n| **Ignoring Tech Debt** | Not allocating time for platform health | Reserve 20% capacity for maintenance |\n| **Stakeholder Surprise** | Not communicating early and often | Weekly async updates, monthly demos |\n| **Metric Theater** | Optimizing vanity metrics over real value | Tie metrics to user value delivered |\n\n---\n\n## Best Practices\n\n**Writing Great PRDs:**\n- Start with the problem, not the solution\n- Include clear success metrics upfront\n- Explicitly state what's out of scope\n- Use visuals (wireframes, flows, diagrams)\n- Keep technical details in appendix\n- Version control all changes\n\n**Effective Prioritization:**\n- Mix quick wins with strategic bets\n- Consider opportunity cost of delays\n- Account for dependencies between features\n- Buffer 20% for unexpected work\n- Revisit priorities quarterly\n- Communicate decisions with context\n\n**Customer Discovery:**\n- Ask \"why\" five times to find root cause\n- Focus on past behavior, not future intentions\n- Avoid leading questions (\"Wouldn't you love...\")\n- Interview in the user's natural environment\n- Watch for emotional reactions (pain = opportunity)\n- Validate qualitative with quantitative data\n\n---\n\n## Quick Reference\n\n```bash\n# Prioritization\npython scripts\u002Frice_prioritizer.py features.csv --capacity 15\n\n# Interview Analysis\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n\n# Generate sample data\npython scripts\u002Frice_prioritizer.py sample\n\n# JSON outputs\npython scripts\u002Frice_prioritizer.py features.csv --output json\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json\n```\n\n---\n\n## Reference Documents\n\n- `references\u002Fprd_templates.md` - PRD templates for different contexts\n- `references\u002Fframeworks.md` - Detailed framework documentation (RICE, MoSCoW, Kano, JTBD, etc.)\n","# Product Manager Toolkit\n\nEssential tools and frameworks for modern product management, from discovery to delivery.\n\n---\n\n## Table of Contents\n\n- [Quick Start](#quick-start)\n- [Core Workflows](#core-workflows)\n  - [Feature Prioritization](#feature-prioritization-process)\n  - [Customer Discovery](#customer-discovery-process)\n  - [PRD Development](#prd-development-process)\n- [Tools Reference](#tools-reference)\n  - [RICE Prioritizer](#rice-prioritizer)\n  - [Customer Interview Analyzer](#customer-interview-analyzer)\n- [Input\u002FOutput Examples](#inputoutput-examples)\n- [Integration Points](#integration-points)\n- [Common Pitfalls](#common-pitfalls-to-avoid)\n\n---\n\n## Quick Start\n\n### For Feature Prioritization\n```bash\n# Create sample data file\npython scripts\u002Frice_prioritizer.py sample\n\n# Run prioritization with team capacity\npython scripts\u002Frice_prioritizer.py sample_features.csv --capacity 15\n```\n\n### For Interview Analysis\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py interview_transcript.txt\n```\n\n### For PRD Creation\n1. Choose template from `references\u002Fprd_templates.md`\n2. Fill sections based on discovery work\n3. Review with engineering for feasibility\n4. Version control in project management tool\n\n---\n\n## Core Workflows\n\n### Feature Prioritization Process\n\n```\nGather → Score → Analyze → Plan → Validate → Execute\n```\n\n#### Step 1: Gather Feature Requests\n- Customer feedback (support tickets, interviews)\n- Sales requests (CRM pipeline blockers)\n- Technical debt (engineering input)\n- Strategic initiatives (leadership goals)\n\n#### Step 2: Score with RICE\n```bash\n# Input: CSV with features\npython scripts\u002Frice_prioritizer.py features.csv --capacity 20\n```\n\nSee `references\u002Fframeworks.md` for RICE formula and scoring guidelines.\n\n#### Step 3: Analyze Portfolio\nReview the tool output for:\n- Quick wins vs big bets distribution\n- Effort concentration (avoid all XL projects)\n- Strategic alignment gaps\n\n#### Step 4: Generate Roadmap\n- Quarterly capacity allocation\n- Dependency identification\n- Stakeholder communication plan\n\n#### Step 5: Validate Results\n**Before finalizing the roadmap:**\n- [ ] Compare top priorities against strategic goals\n- [ ] Run sensitivity analysis (what if estimates are wrong by 2x?)\n- [ ] Review with key stakeholders for blind spots\n- [ ] Check for missing dependencies between features\n- [ ] Validate effort estimates with engineering\n\n#### Step 6: Execute and Iterate\n- Share roadmap with team\n- Track actual vs estimated effort\n- Revisit priorities quarterly\n- Update RICE inputs based on learnings\n\n---\n\n### Customer Discovery Process\n\n```\nPlan → Recruit → Interview → Analyze → Synthesize → Validate\n```\n\n#### Step 1: Plan Research\n- Define research questions\n- Identify target segments\n- Create interview script (see `references\u002Fframeworks.md`)\n\n#### Step 2: Recruit Participants\n- 5-8 interviews per segment\n- Mix of power users and churned users\n- Incentivize appropriately\n\n#### Step 3: Conduct Interviews\n- Use semi-structured format\n- Focus on problems, not solutions\n- Record with permission\n- Take minimal notes during interview\n\n#### Step 4: Analyze Insights\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py transcript.txt\n```\n\nExtracts:\n- Pain points with severity\n- Feature requests with priority\n- Jobs to be done patterns\n- Sentiment and key themes\n- Notable quotes\n\n#### Step 5: Synthesize Findings\n- Group similar pain points across interviews\n- Identify patterns (3+ mentions = pattern)\n- Map to opportunity areas using Opportunity Solution Tree\n- Prioritize opportunities by frequency and severity\n\n#### Step 6: Validate Solutions\n**Before building:**\n- [ ] Create solution hypotheses (see `references\u002Fframeworks.md`)\n- [ ] Test with low-fidelity prototypes\n- [ ] Measure actual behavior vs stated preference\n- [ ] Iterate based on feedback\n- [ ] Document learnings for future research\n\n---\n\n### PRD Development Process\n\n```\nScope → Draft → Review → Refine → Approve → Track\n```\n\n#### Step 1: Choose Template\nSelect from `references\u002Fprd_templates.md`:\n\n| Template | Use Case | Timeline |\n|----------|----------|----------|\n| Standard PRD | Complex features, cross-team | 6-8 weeks |\n| One-Page PRD | Simple features, single team | 2-4 weeks |\n| Feature Brief | Exploration phase | 1 week |\n| Agile Epic | Sprint-based delivery | Ongoing |\n\n#### Step 2: Draft Content\n- Lead with problem statement\n- Define success metrics upfront\n- Explicitly state out-of-scope items\n- Include wireframes or mockups\n\n#### Step 3: Review Cycle\n- Engineering: feasibility and effort\n- Design: user experience gaps\n- Sales: market validation\n- Support: operational impact\n\n#### Step 4: Refine Based on Feedback\n- Address technical constraints\n- Adjust scope to fit timeline\n- Document trade-off decisions\n\n#### Step 5: Approval and Kickoff\n- Stakeholder sign-off\n- Sprint planning integration\n- Communication to broader team\n\n#### Step 6: Track Execution\n**After launch:**\n- [ ] Compare actual metrics vs targets\n- [ ] Conduct user feedback sessions\n- [ ] Document what worked and what didn't\n- [ ] Update estimation accuracy data\n- [ ] Share learnings with team\n\n---\n\n## Tools Reference\n\n### RICE Prioritizer\n\nAdvanced RICE framework implementation with portfolio analysis.\n\n**Features:**\n- RICE score calculation with configurable weights\n- Portfolio balance analysis (quick wins vs big bets)\n- Quarterly roadmap generation based on capacity\n- Multiple output formats (text, JSON, CSV)\n\n**CSV Input Format:**\n```csv\nname,reach,impact,confidence,effort,description\nUser Dashboard Redesign,5000,high,high,l,Complete redesign\nMobile Push Notifications,10000,massive,medium,m,Add push support\nDark Mode,8000,medium,high,s,Dark theme option\n```\n\n**Commands:**\n```bash\n# Create sample data\npython scripts\u002Frice_prioritizer.py sample\n\n# Run with default capacity (10 person-months)\npython scripts\u002Frice_prioritizer.py features.csv\n\n# Custom capacity\npython scripts\u002Frice_prioritizer.py features.csv --capacity 20\n\n# JSON output for integration\npython scripts\u002Frice_prioritizer.py features.csv --output json\n\n# CSV output for spreadsheets\npython scripts\u002Frice_prioritizer.py features.csv --output csv\n```\n\n---\n\n### Customer Interview Analyzer\n\nNLP-based interview analysis for extracting actionable insights.\n\n**Capabilities:**\n- Pain point extraction with severity assessment\n- Feature request identification and classification\n- Jobs-to-be-done pattern recognition\n- Sentiment analysis per section\n- Theme and quote extraction\n- Competitor mention detection\n\n**Commands:**\n```bash\n# Analyze interview transcript\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n\n# JSON output for aggregation\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json\n```\n\n---\n\n## Input\u002FOutput Examples\n\n### RICE Prioritizer Example\n\n**Input (features.csv):**\n```csv\nname,reach,impact,confidence,effort\nOnboarding Flow,20000,massive,high,s\nSearch Improvements,15000,high,high,m\nSocial Login,12000,high,medium,m\nPush Notifications,10000,massive,medium,m\nDark Mode,8000,medium,high,s\n```\n\n**Command:**\n```bash\npython scripts\u002Frice_prioritizer.py features.csv --capacity 15\n```\n\n**Output:**\n```\n============================================================\nRICE PRIORITIZATION RESULTS\n============================================================\n\n? TOP PRIORITIZED FEATURES\n\n1. Onboarding Flow\n   RICE Score: 16000.0\n   Reach: 20000 | Impact: massive | Confidence: high | Effort: s\n\n2. Search Improvements\n   RICE Score: 4800.0\n   Reach: 15000 | Impact: high | Confidence: high | Effort: m\n\n3. Social Login\n   RICE Score: 3072.0\n   Reach: 12000 | Impact: high | Confidence: medium | Effort: m\n\n4. Push Notifications\n   RICE Score: 3840.0\n   Reach: 10000 | Impact: massive | Confidence: medium | Effort: m\n\n5. Dark Mode\n   RICE Score: 2133.33\n   Reach: 8000 | Impact: medium | Confidence: high | Effort: s\n\n? PORTFOLIO ANALYSIS\n\nTotal Features: 5\nTotal Effort: 19 person-months\nTotal Reach: 65,000 users\nAverage RICE Score: 5969.07\n\n? Quick Wins: 2 features\n   • Onboarding Flow (RICE: 16000.0)\n   • Dark Mode (RICE: 2133.33)\n\n? Big Bets: 0 features\n\n? SUGGESTED ROADMAP\n\nQ1 - Capacity: 11\u002F15 person-months\n   • Onboarding Flow (RICE: 16000.0)\n   • Search Improvements (RICE: 4800.0)\n   • Dark Mode (RICE: 2133.33)\n\nQ2 - Capacity: 10\u002F15 person-months\n   • Push Notifications (RICE: 3840.0)\n   • Social Login (RICE: 3072.0)\n```\n\n---\n\n### Customer Interview Analyzer Example\n\n**Input (interview.txt):**\n```\nCustomer: Jane, Enterprise PM at TechCorp\nDate: 2024-01-15\n\nInterviewer: What's the hardest part of your current workflow?\n\nJane: The biggest frustration is the lack of real-time collaboration.\nWhen I'm working on a PRD, I have to constantly ping my team on Slack\nto get updates. It's really frustrating to wait for responses,\nespecially when we're on a tight deadline.\n\nI've tried using Google Docs for collaboration, but it doesn't\nintegrate with our roadmap tools. I'd pay extra for something that\njust worked seamlessly.\n\nInterviewer: How often does this happen?\n\nJane: Literally every day. I probably waste 30 minutes just on\nback-and-forth messages. It's my biggest pain point right now.\n```\n\n**Command:**\n```bash\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n```\n\n**Output:**\n```\n============================================================\nCUSTOMER INTERVIEW ANALYSIS\n============================================================\n\n? INTERVIEW METADATA\nSegments found: 1\nLines analyzed: 15\n\n? PAIN POINTS (3 found)\n\n1. [HIGH] Lack of real-time collaboration\n   \"I have to constantly ping my team on Slack to get updates\"\n\n2. [MEDIUM] Tool integration gaps\n   \"Google Docs...doesn't integrate with our roadmap tools\"\n\n3. [HIGH] Time wasted on communication\n   \"waste 30 minutes just on back-and-forth messages\"\n\n? FEATURE REQUESTS (2 found)\n\n1. Real-time collaboration - Priority: High\n2. Seamless tool integration - Priority: Medium\n\n? JOBS TO BE DONE\n\nWhen working on PRDs with tight deadlines\nI want real-time visibility into team updates\nSo I can avoid wasted time on status checks\n\n? SENTIMENT ANALYSIS\n\nOverall: Negative (pain-focused interview)\nKey emotions: Frustration, Time pressure\n\n? KEY QUOTES\n\n• \"It's really frustrating to wait for responses\"\n• \"I'd pay extra for something that just worked seamlessly\"\n• \"It's my biggest pain point right now\"\n\n?️ THEMES\n\n- Collaboration friction\n- Tool fragmentation\n- Time efficiency\n```\n\n---\n\n## Integration Points\n\nCompatible tools and platforms:\n\n| Category | Platforms |\n|----------|-----------|\n| **Analytics** | Amplitude, Mixpanel, Google Analytics |\n| **Roadmapping** | ProductBoard, Aha!, Roadmunk, Productplan |\n| **Design** | Figma, Sketch, Miro |\n| **Development** | Jira, Linear, GitHub, Asana |\n| **Research** | Dovetail, UserVoice, Pendo, Maze |\n| **Communication** | Slack, Notion, Confluence |\n\n**JSON export enables integration with most tools:**\n```bash\n# Export for Jira import\npython scripts\u002Frice_prioritizer.py features.csv --output json > priorities.json\n\n# Export for dashboard\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json > insights.json\n```\n\n---\n\n## Common Pitfalls to Avoid\n\n| Pitfall | Description | Prevention |\n|---------|-------------|------------|\n| **Solution-First** | Jumping to features before understanding problems | Start every PRD with problem statement |\n| **Analysis Paralysis** | Over-researching without shipping | Set time-boxes for research phases |\n| **Feature Factory** | Shipping features without measuring impact | Define success metrics before building |\n| **Ignoring Tech Debt** | Not allocating time for platform health | Reserve 20% capacity for maintenance |\n| **Stakeholder Surprise** | Not communicating early and often | Weekly async updates, monthly demos |\n| **Metric Theater** | Optimizing vanity metrics over real value | Tie metrics to user value delivered |\n\n---\n\n## Best Practices\n\n**Writing Great PRDs:**\n- Start with the problem, not the solution\n- Include clear success metrics upfront\n- Explicitly state what's out of scope\n- Use visuals (wireframes, flows, diagrams)\n- Keep technical details in appendix\n- Version control all changes\n\n**Effective Prioritization:**\n- Mix quick wins with strategic bets\n- Consider opportunity cost of delays\n- Account for dependencies between features\n- Buffer 20% for unexpected work\n- Revisit priorities quarterly\n- Communicate decisions with context\n\n**Customer Discovery:**\n- Ask \"why\" five times to find root cause\n- Focus on past behavior, not future intentions\n- Avoid leading questions (\"Wouldn't you love...\")\n- Interview in the user's natural environment\n- Watch for emotional reactions (pain = opportunity)\n- Validate qualitative with quantitative data\n\n---\n\n## Quick Reference\n\n```bash\n# Prioritization\npython scripts\u002Frice_prioritizer.py features.csv --capacity 15\n\n# Interview Analysis\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt\n\n# Generate sample data\npython scripts\u002Frice_prioritizer.py sample\n\n# JSON outputs\npython scripts\u002Frice_prioritizer.py features.csv --output json\npython scripts\u002Fcustomer_interview_analyzer.py interview.txt json\n```\n\n---\n\n## Reference Documents\n\n- `references\u002Fprd_templates.md` - 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