Product Discovery

Core Principles

• Continuous Discovery — Weekly user conversations, not episodic research
• Outcome-Driven — Start with outcomes to achieve, not solutions to build
• Assumption Testing — Validate risky assumptions before committing resources
• Co-Creation — Build with customers, not just for them
• Data-Driven — Use evidence over intuition and stakeholder opinions
• Problem-First — Deeply understand the problem space before ideating solutions

Hard Rules (Must Follow)

These rules are mandatory. Violating them means the skill is not working correctly.

No Solution-First Thinking

Never start with a solution. Always define the problem and outcome first.

❌ FORBIDDEN:
"We should build a search bar for the product page"
"Let's add AI recommendations"
"Users need a mobile app"

✅ REQUIRED:
"Problem: Users can't find products (40% exit rate on catalog)
Outcome: Reduce exit rate to 20%
Possible solutions:
1. Search bar with filters
2. AI-powered recommendations
3. Better category navigation
4. Visual product browsing"

Evidence-Based Decisions

Never assume user needs without evidence from real user research.

❌ FORBIDDEN:
- "Users probably want X" (assumption without data)
- "Our competitor has X, so we need it too" (copycat without validation)
- "The CEO thinks we should build X" (HiPPO without evidence)
- "It's obvious users need X" (intuition without validation)

✅ REQUIRED:
- "5 out of 8 interviewed users mentioned X as a pain point"
- "Analytics show 60% of users abandon at step 3"
- "Prototype test: 7/10 users completed task successfully"
- "Survey (n=500): 45% rated feature as 'must have'"

Minimum Interview Threshold

Never validate a problem with fewer than 5 user interviews per segment.

❌ FORBIDDEN:
- "We talked to 2 users and they loved the idea"
- "One customer requested this feature"
- "Based on a quick chat with sales..."

✅ REQUIRED:
| Segment | Interviews | Key Finding |
|---------|------------|-------------|
| Power Users | 6 | 5/6 struggle with X |
| New Users | 5 | 4/5 drop off at onboarding |
| Churned | 5 | 3/5 cited missing feature Y |

Minimum per segment: 5 interviews
Confidence increases with more interviews

Falsifiable Assumptions

Every assumption must be testable and falsifiable with clear success criteria.

❌ FORBIDDEN:
- "Users will like the new design" (not falsifiable)
- "This will improve engagement" (no success criteria)
- "The feature will be useful" (vague)

✅ REQUIRED:
| Assumption | Test | Success Criteria | Result |
|------------|------|------------------|--------|
| Users will complete onboarding in new flow | Prototype test with 10 users | >70% completion | TBD |
| Users prefer visual search | A/B test | >10% lift in conversions | TBD |
| Price point is acceptable | Landing page test | >3% conversion | TBD |

Quick Reference

When to Use What

Continuous Discovery Habits

The Product Trio

Discovery is led by three roles working together weekly:

Product Manager → Defines outcomes, owns roadmap
Designer        → Explores solutions, tests usability
Engineer        → Assesses feasibility, proposes technical solutions

Weekly Activities

## 1. Customer Interviews (Weekly)
- Schedule 3-5 interviews per week minimum
- Mix of current users, churned users, prospects
- Focus on understanding problems, not pitching solutions
- Record and share insights with team

## 2. Assumption Testing (Weekly)
- Identify riskiest assumptions about solutions
- Design quick tests (prototypes, landing pages, fake doors)
- Run experiments with real users
- Measure results against success criteria

## 3. Opportunity Mapping (Ongoing)
- Build opportunity solution tree
- Map customer needs to potential solutions
- Prioritize based on impact and feasibility
- Update as you learn

Discovery vs Delivery

Discovery (What to Build)          Delivery (How to Build It)
├─ Customer interviews             ├─ Sprint planning
├─ Prototype testing               ├─ Development
├─ Assumption validation           ├─ QA testing
├─ Market research                 ├─ Deployment
└─ Opportunity assessment          └─ Post-launch monitoring

Key difference: Discovery reduces risk BEFORE committing to build

Product Opportunity Assessment

Marty Cagan's 10 Questions

Before starting any product initiative, answer these questions:

## 1. Problem Definition
**What problem are we solving?**
- Be specific and measurable
- Validate it's a real problem (not assumed)

## 2. Target Market
**For whom are we solving this problem?**
- Define specific user segments
- Size the addressable market (TAM/SAM/SOM)

## 3. Opportunity Size
**How big is the opportunity?**
- Revenue potential
- User growth potential
- Strategic value

## 4. Success Metrics
**How will we measure success?**
- Leading indicators (usage, engagement)
- Lagging indicators (revenue, retention)
- Define targets upfront

## 5. Alternative Solutions
**What alternatives exist today?**
- Direct competitors
- Indirect solutions
- Current user workarounds

## 6. Our Advantage
**Why are we best suited to solve this?**
- Unique capabilities
- Market position
- Technical advantages

## 7. Strategic Fit
**Why now? Why us?**
- Market timing
- Strategic alignment
- Resource availability

## 8. Dependencies
**What do we need to succeed?**
- Technical dependencies
- Partnership requirements
- Regulatory considerations

## 9. Risks
**What could go wrong?**
- Market risk (will anyone want it?)
- Execution risk (can we build it?)
- Monetization risk (will they pay?)

## 10. Cost of Delay
**What happens if we don't build this?**
- Competitive disadvantage
- Lost revenue
- Market opportunity window

Value vs Effort Framework

Quick prioritization of opportunities:

High Value, Low Effort  → Do First (Quick Wins)
High Value, High Effort → Plan Strategically (Big Bets)
Low Value, Low Effort   → Do Later (Fill Gaps)
Low Value, High Effort  → Don't Do (Money Pit)

Discovery Methods

When to Use What Method

## Generative Research (What problems exist?)
Use when: Starting new product area, exploring unknown space
Methods:
- Ethnographic field studies
- Contextual inquiry
- Diary studies
- Open-ended interviews

## Evaluative Research (Does our solution work?)
Use when: Testing specific solutions, validating designs
Methods:
- Usability testing
- Prototype testing
- A/B testing
- Concept testing

## Quantitative Research (How much? How many?)
Use when: Need statistical validation, measuring impact
Methods:
- Surveys
- Analytics analysis
- A/B experiments
- Market sizing