travisjneuman/.claude/product-management

VISION COMPONENTS:
 
TARGET CUSTOMER:
- Who are we building for?
- What segments? What personas?
 
CUSTOMER NEED:
- What problem are we solving?
- What job to be done?
 
KEY BENEFIT:
- Primary value proposition
- Why customers will choose us
 
DIFFERENTIATOR:
- What makes us unique?
- Competitive advantage
 
AMAZON PRESS RELEASE FORMAT:
- Headline
- Summary (who, what, when, where, why)
- Problem statement
- Solution description
- Customer quote
- How to get started

PMF INDICATORS:
 
QUANTITATIVE:
- 40%+ would be "very disappointed" without product (Sean Ellis)
- Strong organic growth/referrals
- Low churn, high retention
- Improving unit economics
 
QUALITATIVE:
- Customers actively advocating
- Word of mouth driving acquisition
- Pull from market (not push)
- Customers expanding usage
 
PMF SURVEY:
"How would you feel if you could no longer use [product]?"
- Very disappointed → Target 40%+
- Somewhat disappointed
- Not disappointed
 
PMF STAGES:
1. Problem-Solution Fit: Validated problem worth solving
2. Product-Market Fit: Solution resonates with market
3. Business Model Fit: Sustainable economics
4. Scale: Growth mechanics work

JOB STATEMENT:
When [situation], I want to [motivation], so I can [expected outcome].
 
FORCES OF PROGRESS:
Push: Current pain/frustration
Pull: Attraction to new solution
Anxiety: Concerns about switching
Habit: Comfort with status quo

PRODUCT OKR STRUCTURE:
 
OBJECTIVE: [Qualitative goal]
 
KEY RESULT 1: [Metric] from [X] to [Y]
KEY RESULT 2: [Metric] from [X] to [Y]
KEY RESULT 3: [Metric] from [X] to [Y]
 
EXAMPLE:
O: Become the preferred solution for enterprise customers
KR1: Increase enterprise NPS from 40 to 60
KR2: Reduce enterprise churn from 8% to 4%
KR3: Increase enterprise ACV from $50K to $75K

RICE SCORE = (Reach x Impact x Confidence) / Effort
 
REACH: How many customers affected per quarter
- Count: Number of users, customers, transactions
 
IMPACT: Effect on individual customer
- 3 = Massive
- 2 = High
- 1 = Medium
- 0.5 = Low
- 0.25 = Minimal
 
CONFIDENCE: How sure are we
- 100% = High confidence
- 80% = Medium
- 50% = Low
 
EFFORT: Person-months of work
- Engineering time
- Design time
- PM time
 
EXAMPLE:
| Feature | Reach | Impact | Conf | Effort | RICE |
|---------|-------|--------|------|--------|------|
| A | 5000 | 2 | 80% | 3 | 2667 |
| B | 1000 | 3 | 100% | 1 | 3000 |
| C | 10000 | 1 | 50% | 5 | 1000 |

ICE SCORE = Impact x Confidence x Ease
 
IMPACT (1-10):
How much will this move our key metric?
 
CONFIDENCE (1-10):
How sure are we about impact estimate?
 
EASE (1-10):
How easy to implement?
 
Note: Simpler than RICE, good for quick decisions

CATEGORIES:
 
BASIC (Must-be):
- Expected features
- Absence causes dissatisfaction
- Example: Login functionality
 
PERFORMANCE (Linear):
- More is better
- Satisfaction proportional to fulfillment
- Example: Speed, capacity
 
DELIGHTERS (Excitement):
- Unexpected features
- Absence doesn't cause dissatisfaction
- Presence greatly increases satisfaction
- Example: Innovative features

PIRATE METRICS (AARRR):
 
ACQUISITION:
- How do users find us?
- Metrics: Traffic, signups, installs
 
ACTIVATION:
- First positive experience
- Metrics: Onboarding completion, first value
 
RETENTION:
- Do they come back?
- Metrics: DAU/MAU, cohort retention
 
REVENUE:
- Do they pay?
- Metrics: Conversion, ARPU, LTV
 
REFERRAL:
- Do they tell others?
- Metrics: NPS, referral rate, viral coefficient

EXPERIMENT DESIGN:
 
HYPOTHESIS:
If we [change], then [metric] will [improve/decrease] because [rationale].
 
METRICS:
- Primary: The metric you're trying to move
- Secondary: Other metrics to monitor
- Guardrails: Metrics that shouldn't degrade
 
SAMPLE SIZE:
Use calculator based on:
- Baseline conversion rate
- Minimum detectable effect (MDE)
- Statistical significance (usually 95%)
- Power (usually 80%)
 
DURATION:
- At least 1 business cycle
- Adequate sample size
- Account for novelty effects

PRE-LAUNCH:
- [ ] Feature complete and tested
- [ ] Documentation ready
- [ ] Support team trained
- [ ] Marketing materials prepared
- [ ] Sales team enabled
- [ ] Beta feedback incorporated
- [ ] Success metrics defined
 
LAUNCH:
- [ ] Staged rollout plan
- [ ] Monitoring dashboards live
- [ ] War room established
- [ ] Communication sent
- [ ] Feature flags enabled
 
POST-LAUNCH:
- [ ] Monitor metrics and feedback
- [ ] Address critical issues
- [ ] Gather early learnings
- [ ] Celebrate wins
- [ ] Retrospective scheduled

OPPORTUNITY CANVAS:
 
PROBLEM:
What problem are we solving?
Who has this problem?
How do they solve it today?
 
EVIDENCE:
What data supports this?
Customer quotes/feedback?
Market research?
 
SOLUTION:
What are we proposing?
Why will it work?
What's the MVP?
 
ASSUMPTIONS:
What must be true?
What risks exist?
How will we validate?
 
OUTCOME:
Success metrics?
Business impact?
Customer impact?

1. EXECUTIVE SUMMARY (3-4 sentences)
- What: One-line description
- Why: Core problem being solved
- Who: Target users
- Success: How we'll measure it
 
2. BACKGROUND & CONTEXT
- Current situation and pain points
- Supporting data
- Strategic alignment
 
3. GOALS & SUCCESS METRICS
- Primary goal and success metric
- Secondary goals and metrics
- Guardrail metrics
 
4. USER STORIES
Format: "As a [persona], I want to [action], so that [benefit]"
- Acceptance criteria
- Priority (Must/Should/Could Have)
 
5. SOLUTION OVERVIEW
- High-level description
- Key user flows
- Out of scope
 
6. DESIGN & TECHNICAL CONSIDERATIONS
- Mockups/wireframes
- Dependencies
- Scalability
 
7. LAUNCH PLAN
- Rollout strategy
- Success criteria
- Risk mitigation
 
8. OPEN QUESTIONS
- Unresolved decisions
- Areas needing research