{"id":"9dc651d6-7354-4305-a4fd-1f67ddf24ea4","shortId":"bdW7S5","kind":"skill","title":"product-discovery","tagline":"Product discovery and market research expert. Use when validating product ideas, conducting market research, user interviews, competitive analysis, or opportunity assessment. Covers JTBD, Kano model, and Value Proposition Canvas.","description":"# Product Discovery\n\n## Core Principles\n\n- **Continuous Discovery** — Weekly user conversations, not episodic research\n- **Outcome-Driven** — Start with outcomes to achieve, not solutions to build\n- **Assumption Testing** — Validate risky assumptions before committing resources\n- **Co-Creation** — Build with customers, not just for them\n- **Data-Driven** — Use evidence over intuition and stakeholder opinions\n- **Problem-First** — Deeply understand the problem space before ideating solutions\n\n---\n\n## Hard Rules (Must Follow)\n\n> These rules are mandatory. Violating them means the skill is not working correctly.\n\n### No Solution-First Thinking\n\n**Never start with a solution. Always define the problem and outcome first.**\n\n```markdown\n❌ FORBIDDEN:\n\"We should build a search bar for the product page\"\n\"Let's add AI recommendations\"\n\"Users need a mobile app\"\n\n✅ REQUIRED:\n\"Problem: Users can't find products (40% exit rate on catalog)\nOutcome: Reduce exit rate to 20%\nPossible solutions:\n1. Search bar with filters\n2. AI-powered recommendations\n3. Better category navigation\n4. Visual product browsing\"\n```\n\n### Evidence-Based Decisions\n\n**Never assume user needs without evidence from real user research.**\n\n```markdown\n❌ FORBIDDEN:\n- \"Users probably want X\" (assumption without data)\n- \"Our competitor has X, so we need it too\" (copycat without validation)\n- \"The CEO thinks we should build X\" (HiPPO without evidence)\n- \"It's obvious users need X\" (intuition without validation)\n\n✅ REQUIRED:\n- \"5 out of 8 interviewed users mentioned X as a pain point\"\n- \"Analytics show 60% of users abandon at step 3\"\n- \"Prototype test: 7/10 users completed task successfully\"\n- \"Survey (n=500): 45% rated feature as 'must have'\"\n```\n\n### Minimum Interview Threshold\n\n**Never validate a problem with fewer than 5 user interviews per segment.**\n\n```markdown\n❌ FORBIDDEN:\n- \"We talked to 2 users and they loved the idea\"\n- \"One customer requested this feature\"\n- \"Based on a quick chat with sales...\"\n\n✅ REQUIRED:\n| Segment | Interviews | Key Finding |\n|---------|------------|-------------|\n| Power Users | 6 | 5/6 struggle with X |\n| New Users | 5 | 4/5 drop off at onboarding |\n| Churned | 5 | 3/5 cited missing feature Y |\n\nMinimum per segment: 5 interviews\nConfidence increases with more interviews\n```\n\n### Falsifiable Assumptions\n\n**Every assumption must be testable and falsifiable with clear success criteria.**\n\n```markdown\n❌ FORBIDDEN:\n- \"Users will like the new design\" (not falsifiable)\n- \"This will improve engagement\" (no success criteria)\n- \"The feature will be useful\" (vague)\n\n✅ REQUIRED:\n| Assumption | Test | Success Criteria | Result |\n|------------|------|------------------|--------|\n| Users will complete onboarding in new flow | Prototype test with 10 users | >70% completion | TBD |\n| Users prefer visual search | A/B test | >10% lift in conversions | TBD |\n| Price point is acceptable | Landing page test | >3% conversion | TBD |\n```\n\n---\n\n## Quick Reference\n\n### When to Use What\n\n| Scenario | Framework/Tool | Output |\n|----------|---------------|--------|\n| Validate product idea | Product Opportunity Assessment | Go/no-go decision |\n| Size market opportunity | TAM/SAM/SOM | Market size estimates |\n| Understand user needs | User Research (interviews, surveys) | User insights, pain points |\n| Analyze competition | Competitive Analysis | Competitive landscape map |\n| Discover user motivations | Jobs-to-be-Done (JTBD) | Job stories, outcomes |\n| Prioritize features | Kano Model | Feature categorization |\n| Define value proposition | Value Proposition Canvas | Value prop statement |\n| Test product concept | Lean Startup / MVP | Validated learnings |\n| Map opportunities | Opportunity Solution Tree | Prioritized opportunities |\n\n---\n\n## Continuous Discovery Habits\n\n### The Product Trio\n\nDiscovery is led by three roles working together weekly:\n\n```\nProduct Manager → Defines outcomes, owns roadmap\nDesigner        → Explores solutions, tests usability\nEngineer        → Assesses feasibility, proposes technical solutions\n```\n\n### Weekly Activities\n\n```markdown\n## 1. Customer Interviews (Weekly)\n- Schedule 3-5 interviews per week minimum\n- Mix of current users, churned users, prospects\n- Focus on understanding problems, not pitching solutions\n- Record and share insights with team\n\n## 2. Assumption Testing (Weekly)\n- Identify riskiest assumptions about solutions\n- Design quick tests (prototypes, landing pages, fake doors)\n- Run experiments with real users\n- Measure results against success criteria\n\n## 3. Opportunity Mapping (Ongoing)\n- Build opportunity solution tree\n- Map customer needs to potential solutions\n- Prioritize based on impact and feasibility\n- Update as you learn\n```\n\n### Discovery vs Delivery\n\n```\nDiscovery (What to Build)          Delivery (How to Build It)\n├─ Customer interviews             ├─ Sprint planning\n├─ Prototype testing               ├─ Development\n├─ Assumption validation           ├─ QA testing\n├─ Market research                 ├─ Deployment\n└─ Opportunity assessment          └─ Post-launch monitoring\n\nKey difference: Discovery reduces risk BEFORE committing to build\n```\n\n---\n\n## Product Opportunity Assessment\n\n### Marty Cagan's 10 Questions\n\nBefore starting any product initiative, answer these questions:\n\n```markdown\n## 1. Problem Definition\n**What problem are we solving?**\n- Be specific and measurable\n- Validate it's a real problem (not assumed)\n\n## 2. Target Market\n**For whom are we solving this problem?**\n- Define specific user segments\n- Size the addressable market (TAM/SAM/SOM)\n\n## 3. Opportunity Size\n**How big is the opportunity?**\n- Revenue potential\n- User growth potential\n- Strategic value\n\n## 4. Success Metrics\n**How will we measure success?**\n- Leading indicators (usage, engagement)\n- Lagging indicators (revenue, retention)\n- Define targets upfront\n\n## 5. Alternative Solutions\n**What alternatives exist today?**\n- Direct competitors\n- Indirect solutions\n- Current user workarounds\n\n## 6. Our Advantage\n**Why are we best suited to solve this?**\n- Unique capabilities\n- Market position\n- Technical advantages\n\n## 7. Strategic Fit\n**Why now? Why us?**\n- Market timing\n- Strategic alignment\n- Resource availability\n\n## 8. Dependencies\n**What do we need to succeed?**\n- Technical dependencies\n- Partnership requirements\n- Regulatory considerations\n\n## 9. Risks\n**What could go wrong?**\n- Market risk (will anyone want it?)\n- Execution risk (can we build it?)\n- Monetization risk (will they pay?)\n\n## 10. Cost of Delay\n**What happens if we don't build this?**\n- Competitive disadvantage\n- Lost revenue\n- Market opportunity window\n```\n\n### Value vs Effort Framework\n\nQuick prioritization of opportunities:\n\n```\nHigh Value, Low Effort  → Do First (Quick Wins)\nHigh Value, High Effort → Plan Strategically (Big Bets)\nLow Value, Low Effort   → Do Later (Fill Gaps)\nLow Value, High Effort  → Don't Do (Money Pit)\n```\n\n---\n\n## Discovery Methods\n\n### When to Use What Method\n\n```markdown\n## Generative Research (What problems exist?)\nUse when: Starting new product area, exploring unknown space\nMethods:\n- Ethnographic field studies\n- Contextual inquiry\n- Diary studies\n- Open-ended interviews\n\n## Evaluative Research (Does our solution work?)\nUse when: Testing specific solutions, validating designs\nMethods:\n- Usability testing\n- Prototype testing\n- A/B testing\n- Concept testing\n\n## Quantitative Research (How much? How many?)\nUse when: Need statistical validation, measuring impact\nMethods:\n- Surveys\n- Analytics analysis\n- A/B experiments\n- Market sizing\n\n## Qualitative Research (Why? How?)\nUse when: Understanding motivations, uncovering insights\nMethods:\n- User interviews\n- Focus groups\n- Customer advisory boards\n- User observation\n```\n\n### Interview Best Practices\n\n```markdown\n## Preparation\n- Define research goals and hypotheses\n- Create interview guide (but stay flexible)\n- Recruit right participants (6-8 per segment)\n- Schedule 45-60 min sessions\n\n## During Interview\n✓ Ask open-ended questions (\"Tell me about...\")\n✓ Follow up with \"Why?\" 5 times to get to root cause\n✓ Listen more than talk (80/20 rule)\n✓ Ask about past behavior, not future hypotheticals\n✓ Look for workarounds and pain points\n✓ Record and take notes\n\n✗ Don't ask leading questions\n✗ Don't pitch your solution\n✗ Don't ask \"Would you use X?\" (people lie)\n✗ Don't multi-task while interviewing\n\n## Example Questions\n- \"Walk me through the last time you [did task]\"\n- \"What's most frustrating about [current solution]?\"\n- \"How are you solving this problem today?\"\n- \"What would make [task] easier for you?\"\n- \"Tell me more about that...\"\n```\n\n### Survey Best Practices\n\n```markdown\n## When to Survey\n✓ Validate findings from qualitative research\n✓ Measure satisfaction or sentiment at scale\n✓ Prioritize features (Kano surveys)\n✓ Segment users by behavior/needs\n\n## Survey Design\n- Keep it short (<10 min to complete)\n- One question per screen on mobile\n- Mix question types (multiple choice, scale, open-ended)\n- Avoid leading or biased questions\n- Test survey with 5 people before sending\n\n## Question Types\n- Multiple choice → Segmentation, categorization\n- Likert scale (1-5) → Satisfaction, importance\n- Open-ended → Qualitative insights\n- Ranking → Prioritization\n- NPS (0-10) → Loyalty measurement\n\n## Distribution\n- In-app surveys (high response, biased to engaged users)\n- Email surveys (broader reach, lower response)\n- Incentivize thoughtful responses ($10 gift card, early access)\n- Follow up with interviews for interesting responses\n```\n\n---\n\n## 2025 Trends in Product Discovery\n\n### AI-Powered Research\n\n```markdown\n## AI Tools for Discovery\n- **Insight synthesis** — AI analyzes interview transcripts, identifies patterns\n- **Synthetic personas** — AI-generated user proxies for rapid testing\n- **Market intelligence** — AI tracks competitor moves, pricing changes\n- **Survey analysis** — Automated sentiment analysis, theme extraction\n- **Trend detection** — AI identifies emerging market trends early\n\n## Examples\n- Crayon → Competitive intelligence automation\n- Glimpse → Trend detection from web data\n- Delve AI → Automated persona creation\n- Attest → AI-powered survey insights\n- Quantilope → Machine learning research automation\n\n## Best Practices\n✓ Use AI to scale research, not replace human insight\n✓ Validate AI findings with real user conversations\n✓ Combine AI analysis with qualitative depth\n✗ Don't rely solely on synthetic users\n✗ Don't skip talking to real customers\n```\n\n### Continuous Discovery at Scale\n\n```markdown\n## Modern Approach\n- Discovery is embedded in every sprint, not a phase\n- Weekly user touchpoints (interviews, tests, feedback)\n- Rapid experimentation (dozens of tests running)\n- Fast pivots based on evidence (days, not months)\n\n## Team Structure\n- Product trios own discovery for their area\n- Centralized research team supports (tools, methods)\n- Customer success shares feedback loop\n- Data analysts provide quantitative insights\n\n## Cadence\n- Weekly: Customer interviews, prototype tests\n- Bi-weekly: Opportunity review, assumption validation\n- Monthly: Market analysis, competitive review\n- Quarterly: Strategic discovery (new markets, big bets)\n```\n\n---\n\n## Opportunity Solution Tree\n\n### What It Is\n\nVisual framework for mapping the path from outcome to solution:\n\n```\n        OUTCOME (Business goal)\n             |\n    ┌────────┴────────┐\n    │                 │\nOPPORTUNITY 1    OPPORTUNITY 2\n    │                 │\n    ├─ Solution A     ├─ Solution C\n    ├─ Solution B     └─ Solution D\n    └─ Solution C\n```\n\n### How to Build One\n\n```markdown\n## Step 1: Define Outcome\nStart with measurable business outcome\nExample: \"Increase Day 30 retention from 20% to 30%\"\n\n## Step 2: Map Opportunities\nDiscover customer needs/pain points through research\nExample: \"Users don't understand core features\"\n\n## Step 3: Generate Solutions\nFor each opportunity, brainstorm multiple solutions\nExample:\n- Better onboarding tutorial\n- In-app tooltips\n- Interactive product tour\n\n## Step 4: Test Assumptions\nFor each solution, identify riskiest assumption and test\nExample: \"Users will complete a 5-step tutorial\"\nTest: Build simple prototype, test with 10 users\n\n## Step 5: Compare Solutions\nUse evidence to choose best path forward\nBuild what tests validate, discard what fails\n```\n\n### Benefits\n\n```\n✓ Visualizes multiple paths to outcome\n✓ Prevents jumping to first solution\n✓ Encourages broad exploration before narrowing\n✓ Documents why decisions were made\n✓ Keeps team aligned on priorities\n```\n\n---\n\n## Integrating Discovery with Delivery\n\n### Discovery Kanban\n\n```markdown\n## Discovery Board Columns\n\n┌─────────────┬──────────────┬──────────────┬─────────────┐\n│ OPPORTUNITIES│ ASSUMPTIONS  │  EXPERIMENTS │  VALIDATED  │\n│             │              │              │             │\n│ Customer    │ Riskiest     │ Running      │ Ready to    │\n│ needs we've │ assumptions  │ tests        │ build       │\n│ identified  │ to validate  │              │             │\n└─────────────┴──────────────┴──────────────┴─────────────┘\n\n## Flow\n1. Opportunities flow from research\n2. Solutions generate assumptions to test\n3. Experiments validate/invalidate assumptions\n4. Validated solutions enter delivery backlog\n```\n\n### Definition of Ready\n\nBefore moving from discovery to delivery:\n\n```markdown\n## Discovery Checklist\n- [ ] Customer problem validated (5+ interviews)\n- [ ] Solution tested with prototype (10+ users)\n- [ ] Success metrics defined and measurable\n- [ ] Technical feasibility confirmed by engineering\n- [ ] Business case approved (revenue/retention impact)\n- [ ] Design mocks completed and tested\n- [ ] Open questions resolved or explicitly acknowledged\n- [ ] Story broken into shippable increments\n```\n\n---\n\n## Common Anti-Patterns\n\n### What NOT to Do\n\n```markdown\n## ✗ Solution-First Discovery\nStarting with \"We should build X\" then finding evidence to support it\n→ Instead: Start with outcome and problem, explore multiple solutions\n\n## ✗ Episodic Research\nDoing discovery as a phase, then stopping when development starts\n→ Instead: Continuous weekly discovery throughout product lifecycle\n\n## ✗ Confirmation Bias\nOnly talking to users who will validate your ideas\n→ Instead: Seek disconfirming evidence, talk to churned users\n\n## ✗ Fake Validation\nAsking \"Would you use this?\" and trusting the answer\n→ Instead: Test with realistic prototypes, measure actual behavior\n\n## ✗ Analysis Paralysis\nEndless research without ever shipping\n→ Instead: Define upfront what evidence is \"enough\" to move forward\n\n## ✗ Building for Everyone\nTrying to solve for all users at once\n→ Instead: Focus on specific segment, nail it, then expand\n\n## ✗ Ignoring Weak Signals\nDismissing early negative feedback as \"just a few users\"\n→ Instead: Treat complaints as early warning signs, investigate\n```\n\n---\n\n## See Also\n\n- [reference/market-research.md](reference/market-research.md) — TAM/SAM/SOM, Porter's Five Forces\n- [reference/user-research.md](reference/user-research.md) — Interview guides, survey methods, ethnography\n- [reference/competitive-analysis.md](reference/competitive-analysis.md) — Competitive frameworks and analysis\n- [reference/opportunity-frameworks.md](reference/opportunity-frameworks.md) — JTBD, Kano, Value Proposition Canvas\n- [templates/discovery-template.md](templates/discovery-template.md) — Product discovery document template","tags":["product","discovery","claude","arsenal","majiayu000","agent-skills","ai-agents","ai-coding-assistant","automation","claude-code","code-review","developer-tools"],"capabilities":["skill","source-majiayu000","skill-product-discovery","topic-agent-skills","topic-ai-agents","topic-ai-coding-assistant","topic-automation","topic-claude","topic-claude-code","topic-code-review","topic-developer-tools","topic-devops","topic-productivity","topic-prompt-engineering","topic-python"],"categories":["claude-arsenal"],"synonyms":[],"warnings":[],"endpointUrl":"https://skills.sh/majiayu000/claude-arsenal/product-discovery","protocol":"skill","transport":"skills-sh","auth":{"type":"none","details":{"cli":"npx skills add 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