Growth product manager

Growth = Acquisition × Activation × Retention × Monetization × Referral

Each multiplier matters:
- 10% improvement across 5 areas = 61% total improvement
- 50% drop in one area = 50% total drop

    ┌─────────────────────────────────────────────┐
    │              ACQUISITION                     │
    │         (How do users find us?)             │
    ├─────────────────────────────────────────────┤
    │              ACTIVATION                      │
    │       (Do users have a great first          │
    │              experience?)                    │
    ├─────────────────────────────────────────────┤
    │              RETENTION                       │
    │         (Do users come back?)               │
    ├─────────────────────────────────────────────┤
    │              REVENUE                         │
    │        (Do users pay us money?)             │
    ├─────────────────────────────────────────────┤
    │              REFERRAL                        │
    │      (Do users tell others about us?)       │
    └─────────────────────────────────────────────┘

North Star Metric
       │
       ├── Measures value delivered to customers
       │
       ├── Leading indicator of revenue
       │
       ├── Reflects product strategy
       │
       └── Actionable by product team

Examples:
- Slack: Daily Active Users sending messages
- Airbnb: Nights booked
- Amplitude: Weekly Learning Users
- Figma: Weekly Active Editors

Activation = User completes the critical action(s) that predict long-term retention

It's NOT:
× Completing signup
× Verifying email
× Finishing onboarding flow

It IS:
✓ Experiencing the core value
✓ Having the "aha moment"
✓ Taking the action that predicts retention

Activation Rate = Users who complete activation event / Total signups

Example:
- 1,000 signups
- 230 complete activation event
- Activation rate = 23%

Benchmark: 20-40% is typical, 40%+ is excellent

Cohort Analysis:
┌──────────────────────────────────────────────────────────┐
│ Users who did action X in first 7 days                   │
│ → 65% still active at Day 30                            │
│                                                          │
│ Users who did NOT do action X in first 7 days           │
│ → 12% still active at Day 30                            │
│                                                          │
│ → Action X is your activation event                      │
└──────────────────────────────────────────────────────────┘

TTV Benchmarks:
┌─────────────────┬────────────────┬─────────────────────┐
│ Product Type    │ Target TTV     │ Example             │
├─────────────────┼────────────────┼─────────────────────┤
│ Consumer app    │ < 30 seconds   │ TikTok: see video   │
│ Productivity    │ < 5 minutes    │ Notion: create page │
│ Developer tool  │ < 30 minutes   │ Vercel: deploy app  │
│ B2B SaaS        │ < 1 hour       │ Intercom: install   │
│ Enterprise      │ < 1 day        │ Salesforce: import  │
└─────────────────┴────────────────┴─────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│                    ONBOARDING STAGES                         │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  SETUP (Minimize)          AHA (Maximize)       HABIT       │
│  ─────────────────        ─────────────        ─────────    │
│  • Account creation       • First success      • Triggers   │
│  • Essential config       • Core value seen    • Routines   │
│  • Permissions            • "Wow" moment       • Engagement │
│                                                             │
│  Goal: < 2 min            Goal: < 10 min       Goal: Day 7  │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Don't show everything. Reveal complexity as users need it.

Bad:  Sign up → 15 settings → 10 features → empty dashboard
Good: Sign up → 1 action → success → next action → expand

Don't start users with blank slate.

Bad:  "Create your first project" (blank screen)
Good: "Start with this template" (pre-populated)

Examples:
- Notion: Template gallery
- Figma: Starter files
- Airtable: Pre-built bases

Guide within the product, not with modals.

Bad:  5-step tutorial modal before using product
Good: Tooltips that appear as users explore
      Empty states with clear CTAs
      Checklists that track progress

Acknowledge progress to build momentum.

✓ "You created your first project!"
✓ Progress bar showing completion
✓ Confetti / celebration animation (use sparingly)
✓ "You're ahead of 80% of new users"

┌────────────────────────────────────────────────────────┐
│  Get started with [Product]                     3/5 ✓  │
├────────────────────────────────────────────────────────┤
│  ✓ Create your account                                 │
│  ✓ Install the browser extension                       │
│  ✓ Connect your first integration                      │
│  ○ Invite a team member                                │
│  ○ Complete your first [core action]                   │
│                                                        │
│  [Continue →]                                          │
└────────────────────────────────────────────────────────┘

Why it works:
- Clear progress visualization
- Completion psychology (Zeigarnik effect)
- Guides to activation event
- Can be dismissed but persistent

Signup         100%  ████████████████████
│
Email verify   85%   █████████████████
│
Onboarding     70%   ██████████████
│
Setup complete 55%   ███████████
│
Core action    35%   ███████
│
ACTIVATED      25%   █████

Why it works:
✓ Minimal signup (Google SSO)
✓ Asks role to personalize
✓ Pre-populates sample issues
✓ Keyboard shortcuts shown inline
✓ Empty states guide next action
✓ Can be productive in < 5 minutes

Why it fails:
✗ 10+ field signup form
✗ Email verification gate
✗ 30-minute setup wizard
✗ Requires IT involvement
✗ Empty dashboard on first login
✗ Value not seen for days/weeks

Engagement = Frequency × Depth × Breadth

Frequency: How often users return
Depth:     How much time/actions per session
Breadth:   How many features they use

DAU/MAU Ratio (Stickiness):

50%+   : Daily habit product (messaging, productivity)
         Example: Slack, WhatsApp

25-50% : Frequent use product (work tools)
         Example: Figma, Linear

10-25% : Weekly use product (planning, reporting)
         Example: Analytics tools, project management

<10%   : Occasional use (utilities, specific workflows)
         Example: Tax software, travel booking

┌─────────────────────────────────────────────────────────────┐
│                    THE HOOK MODEL                           │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│         TRIGGER                                             │
│         (What prompts the user?)                            │
│              │                                              │
│              ↓                                              │
│         ACTION                                              │
│         (What's the simplest behavior?)                     │
│              │                                              │
│              ↓                                              │
│         VARIABLE REWARD                                     │
│         (What satisfies but leaves wanting more?)           │
│              │                                              │
│              ↓                                              │
│         INVESTMENT                                          │
│         (What work does user put in?)                       │
│              │                                              │
│              └─────────→ (Increases value, creates trigger) │
│                                                             │
└─────────────────────────────────────────────────────────────┘

TRIBE (Social Rewards):
- Likes, comments, followers
- Recognition from peers
- Social validation
Example: LinkedIn endorsements

HUNT (Information Rewards):
- New content to discover
- Answers to questions
- Relevant information
Example: Twitter feed

SELF (Achievement Rewards):
- Mastery, completion
- Progress tracking
- Personal growth
Example: Duolingo streaks

Goal: Build initial engagement pattern

Tactics:
□ Welcome sequence with daily tips
□ Quick wins to celebrate
□ Checklist progress gamification
□ Personal "aha moment" push
□ Low-friction daily trigger

Goal: Establish regular usage pattern

Tactics:
□ Feature discovery prompts
□ Usage streaks/achievements
□ Social features introduction
□ Integration suggestions
□ "Power user" tips

Goal: Deepen engagement and prevent decay

Tactics:
□ Advanced feature unlocks
□ Community involvement
□ Referral program
□ Exclusive content/features
□ Recognition/status

Bad Gamification:
✗ Points that mean nothing
✗ Badges for trivial actions
✗ Forced social competition
✗ Rewards unrelated to value
✗ Gamification that feels manipulative

Good Gamification:
✓ Celebrates real accomplishments
✓ Guides users to value
✓ Creates positive habits
✓ Feels natural to product

Priority 1: User-to-user (highest engagement)
            "Sarah mentioned you"

Priority 2: User-triggered events
            "Your export is ready"

Priority 3: Personalized insights
            "Your weekly summary"

Priority 4: Feature education
            "Have you tried X?"

Priority 5: Marketing (lowest engagement)
            "Check out our new feature"

Signal: No login in 3 days
→ Push: "You have 5 unread messages"

Signal: Decreased usage (50% drop)
→ Email: "We noticed you haven't used X"

Signal: Stopped using key feature
→ In-app: "Need help with [feature]?"

Signal: Approaching renewal
→ Email: "Here's what you accomplished"

Day 3:   "We miss you" + value reminder
Day 7:   "Here's what's new" + updates
Day 14:  "Your data is waiting" + FOMO
Day 30:  "Special offer to return" + incentive
Day 60:  "Last chance" + data deletion warning

┌─────────────────────────────────────────────────────────────┐
│              USER ENGAGEMENT SCORE                          │
├─────────────────────────────────────────────────────────────┤
│ FREQUENCY (0-30)                                            │
│ • Logged in today                 +10                       │
│ • Logged in 5+ days this week     +10                       │
│ • Logged in 15+ days this month   +10                       │
│                                                             │
│ DEPTH (0-40)                                                │
│ • Used core feature               +15                       │
│ • Session > 5 minutes             +10                       │
│ • 10+ actions per session         +15                       │
│                                                             │
│ BREADTH (0-30)                                              │
│ • Used 3+ features                +10                       │
│ • Connected integration           +10                       │
│ • Invited teammate                +10                       │
│                                                             │
│ ENGAGEMENT TIERS:                                           │
│ 80-100: Power User                                          │
│ 50-79:  Engaged                                             │
│ 25-49:  Casual                                              │
│ 0-24:   At Risk                                             │
└─────────────────────────────────────────────────────────────┘

Two types of product work:

BUILD MODE:                    GROWTH MODE:
─────────────────              ──────────────────
Big bets                       Small experiments
Months of work                 Days to weeks
High conviction                High velocity
Ship and iterate               Test and learn
"We believe..."                "We'll test..."

┌──────────────────────────────────────────────────────────────┐
│                EXPERIMENT LIFECYCLE                          │
├──────────────────────────────────────────────────────────────┤
│                                                              │
│  IDEATE → PRIORITIZE → DESIGN → BUILD → RUN → ANALYZE → LEARN
│     │                                                   │    │
│     └───────────────── LEARN & ITERATE ←───────────────┘    │
│                                                              │
└──────────────────────────────────────────────────────────────┘

ICE Score = Impact × Confidence × Ease

Impact (1-10):     How much will this move the metric?
Confidence (1-10): How sure are we of the impact?
Ease (1-10):       How easy is this to implement?

Example:
┌─────────────────────────────────────────────────────────────┐
│ Experiment              │ Impact │ Conf │ Ease │ ICE Score │
├─────────────────────────────────────────────────────────────┤
│ Simplify signup flow    │   8    │  7   │  9   │   504     │
│ Add social proof        │   5    │  6   │  8   │   240     │
│ Redesign onboarding     │   9    │  5   │  3   │   135     │
│ New referral program    │   7    │  4   │  4   │   112     │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│                    EXPERIMENT BRIEF                         │
├─────────────────────────────────────────────────────────────┤
│ EXPERIMENT NAME: [Clear, descriptive name]                  │
│                                                             │
│ HYPOTHESIS:                                                 │
│ If we [change], then [metric] will [improve] because        │
│ [rationale].                                                │
│                                                             │
│ METRICS:                                                    │
│ - Primary: [The metric this aims to move]                   │
│ - Secondary: [Related metrics to watch]                     │
│ - Guardrail: [Metrics that shouldn't degrade]               │
│                                                             │
│ AUDIENCE:                                                   │
│ - Who: [User segment]                                       │
│ - Sample: [% of traffic]                                    │
│ - Duration: [Expected runtime]                              │
│                                                             │
│ SUCCESS CRITERIA:                                           │
│ - Minimum detectable effect: [X%]                           │
│ - Statistical significance: [95%]                           │
│                                                             │
│ VARIANTS:                                                   │
│ - Control: [Current experience]                             │
│ - Treatment: [New experience]                               │
└─────────────────────────────────────────────────────────────┘

"Let's test a new onboarding flow"
- No expected outcome
- No rationale
- Can't be proven wrong

"If we show a personalized checklist during onboarding
(instead of a generic welcome screen),
then day-7 activation rate will increase by 15%
because users will have clear next steps tailored to their use case."

Components:
- Specific change
- Measurable outcome
- Rationale/belief

Minimum Sample Size per Variant:

n = (Z² × p × (1-p)) / E²

Where:
Z = 1.96 (for 95% confidence)
p = baseline conversion rate
E = minimum detectable effect

Example:
- Baseline: 5% conversion
- Want to detect: 10% relative lift (5% → 5.5%)
- Need: ~30,000 users per variant

Use: https://www.evanmiller.org/ab-testing/sample-size.html

Never stop early based on results!

Common mistake:
Day 3: Treatment winning by 20%! → Ship it!
Day 14: Treatment actually -5% → Oops.

Why: Early results are noisy. Statistical power requires full sample.

Minimum: 1-2 full business cycles (usually 2+ weeks)

Monday:    Review last week's results
           Prioritize this week's experiments

Tuesday-   Design and build experiments
Thursday:  Launch when ready

Friday:    Review early data
           Plan next week's experiments
           Document learnings

                Statistical Significance
                  Yes              No
            ┌─────────────┬─────────────┐
    Positive│   SHIP IT   │   EXTEND    │
    Result  │             │   TEST      │
            ├─────────────┼─────────────┤
    Negative│   LEARN &   │   CALL IT   │
    Result  │   ITERATE   │   (Neutral) │
            └─────────────┴─────────────┘

□ Did we reach required sample size?
□ Did we run for full business cycles?
□ Is the result statistically significant (p < 0.05)?
□ Is the effect size practically meaningful?
□ Did guardrail metrics hold?
□ Are there segment-level differences?
□ Can we explain the result?

┌─────────────────────────────────────────────────────────────┐
│                EXPERIMENT RESULTS                           │
├─────────────────────────────────────────────────────────────┤
│ RESULT: [Win / Loss / Neutral]                              │
│                                                             │
│ DATA:                                                       │
│ - Control: [X% conversion]                                  │
│ - Treatment: [Y% conversion]                                │
│ - Lift: [Z%]                                                │
│ - Significance: [p-value]                                   │
│                                                             │
│ DECISION: [Ship / Iterate / Kill]                           │
│                                                             │
│ LEARNINGS:                                                  │
│ - What did we learn about users?                            │
│ - What hypotheses does this generate?                       │
│ - What should we test next?                                 │
│                                                             │
│ NEXT STEPS: [Follow-up experiments]                         │
└─────────────────────────────────────────────────────────────┘

GROWTH LOOP (Tactical):               FLYWHEEL (Strategic):
───────────────────────               ─────────────────────────
User-level mechanic                   Business-level system
Single cycle                          Multiple reinforcing cycles
Weeks to optimize                     Years to build
Copyable by competitors               Creates defensible moat

Example: Invite flow                  Example: Amazon's ecosystem

                    ┌────────────────┐
                    │   Lower Prices │
                    └───────┬────────┘
                            │
            ┌───────────────┴───────────────┐
            ↓                               │
    ┌───────────────┐               ┌───────────────┐
    │ More Customers│───────────────→│ More Sellers  │
    └───────┬───────┘               └───────┬───────┘
            │                               │
            ↓                               ↓
    ┌───────────────┐               ┌───────────────┐
    │ More Revenue  │               │ More Selection│
    └───────┬───────┘               └───────┬───────┘
            │                               │
            └───────────────┬───────────────┘
                            ↓
                    ┌────────────────┐
                    │ Lower Costs    │
                    │ (economies of  │
                    │    scale)      │
                    └────────────────┘
                            │
                            └────────→ (back to lower prices)

                    ┌────────────────────┐
                    │  Users Experience  │
                    │      Value         │
                    └─────────┬──────────┘
                              │
            ┌─────────────────┴─────────────────┐
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ Users Share/  │                   │ Product       │
    │ Invite Others │                   │ Improves      │
    └───────┬───────┘                   └───────┬───────┘
            │                                   ↑
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ More Users    │                   │ More Revenue  │
    │ Sign Up       │                   │ to Invest     │
    └───────┬───────┘                   └───────────────┘
            │                                   ↑
            └───────────────────────────────────┘

                    ┌────────────────────┐
                    │  Create Quality    │
                    │     Content        │
                    └─────────┬──────────┘
                              │
            ┌─────────────────┴─────────────────┐
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ Content Ranks │                   │ Revenue       │
    │ on Google     │                   │ Funds Team    │
    └───────┬───────┘                   └───────┬───────┘
            │                                   ↑
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ Organic       │──────────────────→│ Customers     │
    │ Traffic       │                   │ Convert       │
    └───────────────┘                   └───────────────┘

                    ┌────────────────────┐
                    │  Community Members │
                    │    Join            │
                    └─────────┬──────────┘
                              │
            ┌─────────────────┴─────────────────┐
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ Members       │                   │ Better        │
    │ Help Others   │                   │ Product       │
    └───────┬───────┘                   └───────┬───────┘
            │                                   ↑
            ↓                                   │
    ┌───────────────┐                   ┌───────────────┐
    │ Knowledge     │──────────────────→│ Feedback      │
    │ Base Grows    │                   │ Loop          │
    └───────────────┘                   └───────────────┘

Questions:
1. What value do you create for users?
2. How does that value compound?
3. What do users give back that helps you create more value?
4. What advantages accumulate over time?

Template:
┌─────────────────────────────────────────────────────────────┐
│                    YOUR FLYWHEEL                            │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  COMPONENT 1: _____________ (What starts the cycle?)        │
│       │                                                     │
│       ↓                                                     │
│  COMPONENT 2: _____________ (What does that enable?)        │
│       │                                                     │
│       ↓                                                     │
│  COMPONENT 3: _____________ (What does that create?)        │
│       │                                                     │
│       ↓                                                     │
│  COMPONENT 4: _____________ (How does that reinforce #1?)   │
│       │                                                     │
│       └──────────────────→ (back to Component 1)            │
│                                                             │
└─────────────────────────────────────────────────────────────┘

For each component, ask:
- What makes this component spin faster?
- What slows it down (friction)?
- How can we accelerate it?
- What metric tracks its velocity?

Designers create in Figma
       │
       ↓
Share designs with stakeholders (view links)
       │
       ↓
Stakeholders see Figma value, request it
       │
       ↓
More designers at company adopt
       │
       ↓
Community creates plugins/resources
       │
       ↓
Figma becomes more valuable
       │
       └────→ (More designers create in Figma)

Create educational content
       │
       ↓
Content ranks, drives traffic
       │
       ↓
Visitors convert to free tools
       │
       ↓
Free users upgrade to paid
       │
       ↓
Revenue funds more content + product
       │
       └────→ (Create more educational content)

Users create documents/templates
       │
       ↓
Templates shared publicly
       │
       ↓
Templates indexed by Google
       │
       ↓
Searchers discover, sign up to use
       │
       ↓
New users create their own templates
       │
       └────→ (More content in ecosystem)

The flywheel is heavy. Takes significant effort to get moving.
- Manual effort required
- Slow initial progress
- Feels like it's not working
- Temptation to give up

Action: Focus all energy on getting first rotation.

The flywheel starts helping itself.
- Less effort per rotation
- Components reinforce each other
- Measurable acceleration
- Competitive advantage emerging

Action: Identify and remove friction.

The flywheel is unstoppable.
- Self-reinforcing growth
- Competitors can't catch up
- Moat is established
- Focus shifts to efficiency

Action: Protect the flywheel, optimize efficiency.

1. Too Many Components
   Bad: 10-step flywheel
   Good: 3-5 components max

2. No Clear Reinforcement
   Bad: Components don't actually help each other
   Good: Each component directly accelerates others

3. Ignoring Friction
   Bad: Flywheel looks good on paper but doesn't spin
   Good: Identify and remove friction at each step

4. Premature Optimization
   Bad: Optimizing before flywheel turns
   Good: Get it turning, then optimize

5. Single Point of Failure
   Bad: If one component breaks, flywheel stops
   Good: Redundant reinforcement mechanisms

┌─────────────────────────────────────────────────────────────┐
│                  FLYWHEEL HEALTH                            │
├─────────────────────────────────────────────────────────────┤
│ VELOCITY                                                    │
│ Cycle time: 14 days (↓ 2 days from last month)             │
│                                                             │
│ COMPONENT HEALTH                                            │
│ 1. User activation:   78% (↑ 3%)    ████████░░ Good        │
│ 2. Viral sharing:     12% (↓ 1%)    ██░░░░░░░░ Needs work  │
│ 3. Content creation:  45% (↑ 5%)    █████░░░░░ Improving   │
│ 4. Revenue growth:    8% MoM        ████░░░░░░ On track    │
│                                                             │
│ MOMENTUM INDICATORS                                         │
│ • Organic % of signups: 34% (target: 50%)                  │
│ • Content library: 1,200 pieces (↑ 150 this month)         │
│ • Community members: 8,500 (↑ 12% MoM)                     │
└─────────────────────────────────────────────────────────────┘

Traditional Funnel (Linear):              Growth Loop (Compounding):

Acquisition → Activation → Revenue        ┌──────────────────────┐
      ↓             ↓           ↓        │     New Users        │
   (lost)        (lost)      (end)       └──────────┬───────────┘
                                                     ↓
                                          ┌──────────────────────┐
                                          │   Experience Value   │
                                          └──────────┬───────────┘
                                                     ↓
                                          ┌──────────────────────┐
                                          │   Take Action        │
                                          │ (Share/Create/Invite)│
                                          └──────────┬───────────┘
                                                     ↓
                                          ┌──────────────────────┐
                                          │    Generate New      │
                                          │       Users          │
                                          └──────────┬───────────┘
                                                     │
                                                     └────────────→ (loops back)

Questions to answer:
1. What action do activated users take?
2. How does that action reach new potential users?
3. What makes those new users sign up?
4. How long is the cycle time?

┌─────────────────────────────────────────────────────────────┐
│                     YOUR GROWTH LOOP                        │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│   INPUT: _____________ (New user / $ / Content piece)       │
│                                                             │
│   STEP 1: _____________ (What do they do?)                  │
│                                                             │
│   STEP 2: _____________ (How does it spread?)               │
│                                                             │
│   STEP 3: _____________ (Who sees it?)                      │
│                                                             │
│   OUTPUT: _____________ (New input for the loop)            │
│                                                             │
│   CYCLE TIME: _____________ (How long per loop?)            │
│                                                             │
└─────────────────────────────────────────────────────────────┘

1. User creates Calendly account
2. User shares scheduling link
3. Recipient sees "Powered by Calendly"
4. Recipient signs up to send their own links
→ Loop time: ~1 week
→ Each user exposes ~10 potential users

1. User creates template
2. Template published to Notion template gallery
3. Google indexes template page
4. Searcher finds template, signs up to use it
5. New user creates their own templates
→ Loop time: ~2-4 weeks
→ Templates compound forever

1. HubSpot publishes blog content
2. Content ranks on Google
3. Visitor reads content, sees CTA
4. Visitor signs up for free tool
5. User becomes customer, generates revenue
6. Revenue funds more content
→ Loop time: ~3-6 months
→ 100,000+ indexed pages

K-factor = i × c

i = invites per user
c = conversion rate

K > 1: Exponential growth
K = 1: Stable
K < 1: Declining (need other loops)

Example:
- 5 invites per user, 20% convert
- K = 5 × 0.2 = 1.0 (stable)
- Improve conversion to 25%: K = 1.25 (viral!)

Content Velocity = New pages × Rank probability × Traffic per page × Conversion rate

Example:
- 100 new pages/month
- 30% rank on page 1
- 500 visits/month per ranking page
- 2% conversion
= 100 × 0.3 × 500 × 0.02 = 300 new users/month

After 12 months of compounding:
= 3,600+ new users/month from content alone

Layer 1: Paid Loop (immediate, controllable)
         Revenue → Ads → Signups → Revenue

Layer 2: Viral Loop (medium-term, scalable)
         User → Invites → New Users → Invites

Layer 3: Content Loop (long-term, defensible)
         Content → SEO → Traffic → Users → Content

Why it works:
✓ Loop is inherent to product value (collaboration)
✓ Short cycle time (days)
✓ High loop conversion (team adoption)
✓ Each user exposes entire team
✓ Network effects strengthen retention

Why it fails:
✗ Incentive not aligned with value (give $20, get $20)
✗ Users game the system
✗ No natural reason to share
✗ One-time action, not repeating
✗ Feels spammy to recipients

A North Star Metric is the single metric that best captures
the core value your product delivers to customers.

Characteristics:
✓ Measures value delivered (not captured)
✓ Leading indicator of revenue
✓ Actionable by product/growth teams
✓ Easy to understand company-wide
✓ Reflects your product strategy

Questions to answer:
1. What job does our product do for users?
2. When do users say "this is valuable"?
3. What action indicates they got value?
4. What predicts they'll stay and pay?

For each candidate metric, check:

□ Does it measure VALUE delivered (not just activity)?
□ Does it CORRELATE with revenue?
□ Can teams INFLUENCE it?
□ Is it SIMPLE to explain?
□ Does it ALIGN with strategy?

Score each 1-5. Highest total = best candidate.

Correlation analysis:
- Does higher metric → higher retention?
- Does higher metric → higher revenue?
- Does higher metric → higher referral?

If yes to all three, you have a strong North Star.

                    NORTH STAR METRIC
                           │
        ┌──────────────────┼──────────────────┐
        │                  │                  │
   INPUT 1            INPUT 2            INPUT 3
   (Breadth)          (Depth)            (Frequency)
        │                  │                  │
   Sub-metrics        Sub-metrics        Sub-metrics

                Time Spent Listening
                        │
        ┌───────────────┼───────────────┐
        │               │               │
   Total Users      Sessions/User    Time/Session
   (Breadth)         (Frequency)       (Depth)
        │               │               │
   • New users      • Push opens     • Playlist quality
   • Reactivated    • Home screen    • Skip rate
                    • Recommendations • Completion rate

Single metric everyone knows
Example: Weekly Active Users

4-6 metrics that feed the North Star
Example: New users, Activation rate, Retention, ARPU

Specific metrics each team owns
Example: Onboarding completion, Feature adoption, Support tickets

Granular metrics for experiments
Example: CTA click rate, Form completion, Time on page

Stage        │ Definition              │ Example Metrics
─────────────┼─────────────────────────┼──────────────────────
ACQUISITION  │ User discovers product  │ Visitors, signups, CAC
ACTIVATION   │ User experiences value  │ Activation rate, TTV
RETENTION    │ User keeps coming back  │ D7/D30 retention, churn
REVENUE      │ User pays money         │ Conversion, ARPU, LTV
REFERRAL     │ User brings others      │ K-factor, NPS, referrals

New Users This Period =
  + New signups (acquisition)
  + Resurrected users (win-back)
  - Churned users (retention)

Growth Accounting Table:
┌──────────────────────────────────────────────────────────┐
│ Month      │ Start │ +New │ +Resur │ -Churn │ End    │
├──────────────────────────────────────────────────────────┤
│ January    │ 1000  │ +200 │ +30    │ -80    │ 1150   │
│ February   │ 1150  │ +250 │ +40    │ -90    │ 1350   │
│ March      │ 1350  │ +280 │ +50    │ -100   │ 1580   │
└──────────────────────────────────────────────────────────┘

"Monthly Active Users" could mean:
- Logged in at least once
- Performed any action
- Performed core action
- Performed core action on X days
- Paid users who logged in

Define exactly what counts, document it, don't change it.

Metric: Weekly Active Users (WAU)

Definition:
"Unique users who completed at least one [core action]
in the trailing 7-day period, excluding:
- Internal/test accounts
- Users in trial who never activated
- Bot/automated accounts"

Why: This measures users receiving value, not just logging in.

┌─────────────────────────────────────────────────────────────┐
│                    GROWTH DASHBOARD                         │
├─────────────────────────────────────────────────────────────┤
│ NORTH STAR                                                  │
│ Weekly Active Users: 12,450 (+8% WoW)                       │
├─────────────────────────────────────────────────────────────┤
│ ACQUISITION          │ ACTIVATION      │ RETENTION          │
│ Signups: 2,100       │ Rate: 34%       │ D7: 42%           │
│ CAC: $45             │ TTV: 8 min      │ D30: 28%          │
├─────────────────────────────────────────────────────────────┤
│ REVENUE              │ REFERRAL        │ EXPERIMENTS        │
│ MRR: $125K           │ K-factor: 0.3   │ Active: 4          │
│ Conversion: 5.2%     │ NPS: 52         │ Last win: +12%     │
└─────────────────────────────────────────────────────────────┘

Agenda (30-60 min):
1. North Star trend (5 min)
2. Input metric review (10 min)
3. Experiment results (15 min)
4. Anomalies and insights (10 min)
5. Priorities for next week (10 min)

Agenda (2 hours):
1. Month-over-month trends
2. Cohort analysis
3. Channel performance
4. Experiment portfolio review
5. Roadmap alignment check

Warning Signs:
⚠ Metric going up but revenue flat
⚠ Metric looks good but customers churning
⚠ Teams gaming the metric
⚠ Metric impossible to move
⚠ Different teams measuring differently
⚠ No one can explain what the metric means

Revenue = Users × Conversion Rate × ARPU × Retention

Levers:
- More users (acquisition)
- Better conversion (monetization)
- Higher ARPU (pricing/packaging)
- Longer retention (product/success)

✓ Large addressable market (100K+ potential users)
✓ Low marginal cost to serve free users
✓ Product improves with more users (network effects)
✓ Free users provide value (content, data, virality)
✓ Clear upgrade triggers exist
✓ Self-serve motion works

✗ High cost to serve
✗ Small, defined market
✗ Complex product requiring sales
✗ No natural upgrade trigger
✗ Free users provide no value

                        Product Complexity
                    Low                 High
                ┌──────────────────────────────────┐
         Large  │  FREEMIUM            FREE TRIAL  │
Market         │  (Slack, Notion)     (HubSpot)    │
  Size          │                                  │
         Small  │  FREEMIUM + LIMIT    DEMO/SALES  │
                │  (Limited features)  (Enterprise) │
                └──────────────────────────────────┘

Good Triggers (Value-Aligned):
✓ User hits limit while getting value
✓ Team needs collaboration features
✓ Business requirement (SSO, compliance)
✓ Power user needs advanced features

Bad Triggers (Value-Misaligned):
✗ Arbitrary limits unrelated to value
✗ Hiding basic features behind paywall
✗ Bait-and-switch pricing
✗ Nagging before user sees value

┌─────────────────────────────────────────────────────────────┐
│                    PRICING TIERS                            │
├──────────────┬──────────────┬──────────────┬───────────────┤
│     FREE     │    BASIC     │     PRO      │  ENTERPRISE   │
├──────────────┼──────────────┼──────────────┼───────────────┤
│ Individual   │ Individual   │ Teams        │ Organization  │
│ Limited      │ Full access  │ + Collab     │ + Admin       │
│              │              │ + Integrations│ + SSO/SCIM   │
│              │              │              │ + Support     │
├──────────────┼──────────────┼──────────────┼───────────────┤
│ $0           │ $10/mo       │ $20/seat/mo  │ Contact us    │
├──────────────┼──────────────┼──────────────┼───────────────┤
│ Acquisition  │ Monetization │ Expansion    │ Enterprise    │
│ funnel       │ entry point  │ driver       │ land          │
└──────────────┴──────────────┴──────────────┴───────────────┘

NRR = (Starting ARR + Expansion - Contraction - Churn) / Starting ARR

Example:
- Starting ARR: $1M
- Expansion: $200K (more seats, upgrades)
- Contraction: $50K (downgrades)
- Churn: $100K (cancellations)
- NRR = ($1M + $200K - $50K - $100K) / $1M = 105%

Top SaaS companies: 120-150% NRR

┌─────────────────────────────────────────────────────────────┐
│                   PRICING PAGE                              │
├─────────────────────────────────────────────────────────────┤
│ 1. Clear tier differentiation                               │
│    → Who is each tier for?                                  │
│                                                             │
│ 2. Recommended tier highlighted                             │
│    → "Most popular" badge                                   │
│                                                             │
│ 3. Feature comparison table                                 │
│    → Easy to scan differences                               │
│                                                             │
│ 4. Annual discount visible                                  │
│    → "Save 20% with annual"                                 │
│                                                             │
│ 5. Social proof                                             │
│    → Customer logos, testimonials                           │
│                                                             │
│ 6. FAQ section                                              │
│    → Handle objections                                      │
│                                                             │
│ 7. Clear CTA                                                │
│    → "Start free trial" > "Get started"                    │
└─────────────────────────────────────────────────────────────┘

Traditional MQL:              PQL:
─────────────────            ────────────────
Downloaded ebook      vs.    Activated in product
Attended webinar             Invited teammates
Filled out form              Hit usage threshold
                             Used premium feature

PQLs are 6x more likely to convert than MQLs

Traditional GTM:              Product-Led GTM:
──────────────────            ──────────────────────────
Marketing → Lead              Product → User
Sales → Demo                  User → Activation
Sales → Close                 User → Conversion (self-serve)
CSM → Expand                  Product → Expansion

PLG companies let users experience value before paying.

┌─────────────────────────────────────────────────────────────┐
│                    PLG MODEL TYPES                          │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  FREE TRIAL          │  FREEMIUM           │  OPEN SOURCE  │
│  ────────────────    │  ────────────────   │  ──────────── │
│  Full access         │  Limited free tier  │  Core is free │
│  Time-limited        │  Upgrade for more   │  Premium adds │
│  14-30 days          │  Forever free       │  Hosting/      │
│  Convert or lose     │  Convert when ready │  support paid  │
│                      │                     │                │
│  Example:            │  Example:           │  Example:      │
│  Salesforce          │  Slack, Notion      │  GitLab       │
│                                                             │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  REVERSE TRIAL       │  USAGE-BASED        │  HYBRID       │
│  ────────────────    │  ────────────────   │  ──────────── │
│  Premium first       │  Pay for what you   │  Multiple     │
│  Downgrade to free   │  use                │  models       │
│  Experience value    │  Scales with value  │  combined     │
│                      │                     │                │
│  Example:            │  Example:           │  Example:      │
│  Ahrefs              │  Twilio, AWS        │  HubSpot      │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Traditional Funnel:          PLG Funnel:
─────────────────            ─────────────────────────
Awareness                    Awareness
  ↓                            ↓
Interest                     Signup (self-serve)
  ↓                            ↓
MQL                          Activation (in-product)
  ↓                            ↓
SQL                          PQL (product-qualified)
  ↓                            ↓
Demo                         Conversion (in-product or sales)
  ↓                            ↓
Close                        Expansion (in-product or sales)

Users should experience core value in:
- Consumer: < 30 seconds
- Prosumer: < 5 minutes
- SMB SaaS: < 30 minutes
- Mid-market: < 1 day

If it takes a week to see value, it's not PLG.

Product must do the work of:
- Explaining value proposition
- Demonstrating features
- Overcoming objections
- Creating urgency
- Facilitating conversion

Every screen is a sales conversation.

Good: User hits limit while getting value → upgrade prompt
Bad: User must upgrade to see any value → frustration

The free tier should deliver real value.
The paid tier should deliver 10x more.

A PQL is a user who has:
1. Completed activation actions
2. Demonstrated buying intent through usage
3. Fits your ideal customer profile

PQLs convert 5-6x better than MQLs.

┌─────────────────────────────────────────────────────────────┐
│                    PQL SCORING                              │
├─────────────────────────────────────────────────────────────┤
│ ACTIVATION SCORE (0-40)                                     │
│ • Completed onboarding          +10                         │
│ • Used core feature             +15                         │
│ • Created content/data          +15                         │
│                                                             │
│ ENGAGEMENT SCORE (0-30)                                     │
│ • Daily active last 7 days      +5 per day                  │
│ • Invited teammates             +10                         │
│ • Connected integration         +10                         │
│                                                             │
│ FIT SCORE (0-30)                                            │
│ • Company size > 50             +10                         │
│ • Business email domain         +10                         │
│ • Target industry               +10                         │
│                                                             │
│ PQL THRESHOLD: 60+                                          │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│                 IN-PRODUCT UPGRADE                          │
├─────────────────────────────────────────────────────────────┤
│ 1. Show current plan usage                                  │
│    "You're on Free: 3/5 projects used"                      │
│                                                             │
│ 2. Highlight relevant value                                 │
│    "Pro includes: Unlimited projects, analytics, SSO"       │
│                                                             │
│ 3. Provide social proof                                     │
│    "12,000 teams upgraded last month"                       │
│                                                             │
│ 4. Make it easy                                             │
│    Credit card on file? One-click upgrade                   │
│                                                             │
│ 5. Reduce risk                                              │
│    "14-day money-back guarantee"                            │
└─────────────────────────────────────────────────────────────┘

Pure PLG (self-serve only):
- ACV < $1,000
- Simple product
- Individual buyers
- High volume

PLG + Sales:
- ACV > $10,000
- Enterprise features needed
- Multiple stakeholders
- Complex security/compliance

┌─────────────────────────────────────────────────────────────┐
│              PRODUCT-LED SALES MOTION                       │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  Self-Serve ──────────────────────────────────────→ Convert │
│       │                                                     │
│       │  [PQL Score > Threshold]                            │
│       ↓                                                     │
│  Sales Touches ────────→ Enterprise Close                   │
│       │                                                     │
│       │  • Account research                                 │
│       │  • Personalized outreach                            │
│       │  • Demo of advanced features                        │
│       │  • Security/compliance questions                    │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Retention compounds. Churn kills.

Starting with 1,000 users:
┌──────────────────────────────────────────────────────────────┐
│                Monthly Churn: 5%    vs    Monthly Churn: 10% │
├──────────────────────────────────────────────────────────────┤
│ Month 1:     950 users             900 users                 │
│ Month 6:     735 users             531 users                 │
│ Month 12:    540 users             282 users                 │
│ Month 24:    292 users              79 users                 │
└──────────────────────────────────────────────────────────────┘

Same acquisition, wildly different outcomes.

RETENTION CURVE PATTERNS

% Active
100% │●
     │ ●
 80% │  ●          Flattening (Good!)
     │   ●●●●●●●●●●●●●●●●●●●●
 60% │
     │ ●
 40% │  ●           Declining (Bad!)
     │   ●●
 20% │     ●●●●
     │          ●●●●●●●●●●
  0% └────────────────────────────────→ Time
     D1  D7  D14  D30  D60  D90

Goal: Curve that flattens, indicating retained cohort

┌─────────────────────────────────────────────────────────────┐
│                    RETENTION STACK                          │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  Layer 4: SWITCHING COSTS                                   │
│           Data, integrations, workflows, team adoption      │
│                                                             │
│  Layer 3: HABIT FORMATION                                   │
│           Triggers, routines, variable rewards              │
│                                                             │
│  Layer 2: VALUE DELIVERY                                    │
│           Core job done well, consistent experience         │
│                                                             │
│  Layer 1: ACTIVATION                                        │
│           Users experience value (foundation of retention)  │
│                                                             │
└─────────────────────────────────────────────────────────────┘

        ┌──────────────┐
        │   TRIGGER    │ ← External (notification) or Internal (emotion)
        └──────┬───────┘
               ↓
        ┌──────────────┐
        │    ACTION    │ ← Simple behavior in anticipation of reward
        └──────┬───────┘
               ↓
        ┌──────────────┐
        │   VARIABLE   │ ← Unpredictable reward creates craving
        │    REWARD    │
        └──────┬───────┘
               ↓
        ┌──────────────┐
        │  INVESTMENT  │ ← User puts something in, increases value
        └──────┬───────┘
               │
               └────────→ (loops back to trigger)

Good Notifications:                 Bad Notifications:
✓ Timely (when relevant)           ✗ Spam (daily digest no one wants)
✓ Personal (your data/activity)    ✗ Generic (new feature!)
✓ Actionable (clear next step)     ✗ Dead-end (FYI only)
✓ Valuable (saves time/effort)     ✗ Selfish (please come back)

Notification Hierarchy:
1. Activity from people you follow
2. Mentions/responses to your actions
3. Important status changes
4. Educational/onboarding
5. Product updates (sparingly)

Lifecycle Email Strategy:

Day 1:   Welcome + quick start
Day 3:   Activation push (if not activated)
Day 7:   Feature highlight
Day 14:  Case study / social proof
Day 21:  Re-engagement (if inactive)
Day 30:  Value recap + upgrade prompt
Day 45:  Win-back (if churned)

Churn Risk Signals → Intervention

Signal: No login in 7 days
→ Email: "Here's what you missed"

Signal: Decreased usage
→ In-app: "Need help with anything?"

Signal: Not using key feature
→ Email: "Have you tried [feature]?"

Signal: Support ticket unresolved
→ Alert: Priority follow-up

Signal: Downgrade intent
→ Offer: Personalized retention offer

                     Week After Signup
              W1    W2    W3    W4    W5    W6    W7    W8
Jan Cohort   100%   67%   52%   45%   42%   40%   39%   38%
Feb Cohort   100%   72%   58%   51%   47%   44%   42%   41%
Mar Cohort   100%   75%   62%   55%   52%   49%   47%   --

↑ Improving cohort retention = product improvements working

K = i × c

Where:
i = Number of invites/exposures per user
c = Conversion rate of those invites

K > 1: Exponential growth (each user brings >1 user)
K = 1: Stable (each user replaces themselves)
K < 1: Declining (need other acquisition channels)

Calendly:
- Each user sends ~20 scheduling links/month
- Each link seen by 1 unique person
- 5% of recipients sign up
- K = 20 × 0.05 = 1.0 (stable viral)

If product improves:
- Better conversion page → 7% signup
- K = 20 × 0.07 = 1.4 (viral growth!)

Viral Cycle Time = Time from signup to generating new signup

Faster cycles = faster compounding

Day 1:    1 user
Day 7:    K^1 users (if 7-day cycle)
Day 14:   K^2 users
Day 30:   K^4 users

With K=1.5 and 7-day cycle:
Day 1:    1 user
Day 30:   5 users
Day 60:   25 users
Day 90:   125 users

1. Does using the product naturally expose it to non-users?
   - Calendly: Recipients see your booking page
   - Figma: Collaborators see the tool
   - Loom: Viewers see the player

2. Does the product become more valuable with more users?
   - Slack: More teammates = more valuable
   - Notion: Team knowledge base
   - Linear: Team issue tracking

3. Can users accomplish their goal only by involving others?
   - Figma: Real-time collaboration
   - Calendly: Scheduling requires recipient
   - DocuSign: Signing requires counterparty

┌─────────────────────────────────────────────────────────┐
│                REFERRAL PROGRAM DESIGN                  │
├─────────────────────────────────────────────────────────┤
│                                                         │
│  INCENTIVE        │  MECHANIC         │  TIMING        │
│  ─────────────────│───────────────────│────────────────│
│  • Credit/money   │  • Unique code    │  • After aha   │
│  • Free months    │  • Share link     │  • At value    │
│  • Feature unlock │  • In-product     │  • Natural     │
│  • Status/badge   │  • Email invite   │    moment      │
│  • Charitable     │  • Social share   │  • Not during  │
│                   │                   │    onboarding  │
│                                                         │
│  BOTH SIDES WIN: Referrer + Referred get value         │
│                                                         │
└─────────────────────────────────────────────────────────┘

Placement matters:
✓ Visible but not intrusive
✓ Links to signup page
✓ Contextual (shows what product does)

Examples:
- Typeform: "Create your own form"
- Calendly: "Powered by Calendly"
- Webflow: "Made in Webflow"

Make outputs naturally shareable:

Canva:
- Design → Download → Share (with watermark option)
- Or share Canva link

Loom:
- Record → Share link
- Viewer sees "Record your own Loom"

Figma:
- Design → Share → View-only link
- Viewer can sign up to edit

Good Invite Flow:
┌─────────────────────────────────────────────┐
│ 1. User takes action that benefits from     │
│    collaboration                            │
│                                             │
│ 2. Prompt: "Share with your team"           │
│    [Enter emails]                           │
│                                             │
│ 3. Personalized invite sent                 │
│                                             │
│ 4. Recipient sees context                   │
│    (why they're invited, what they'll do)   │
│                                             │
│ 5. Frictionless signup                      │
│                                             │
│ 6. Recipient lands in shared context        │
└─────────────────────────────────────────────┘

Invite Sent          100%  ████████████████████
│
Invite Opened        60%   ████████████
│
Clicked CTA          30%   ██████
│
Started Signup       20%   ████
│
Completed Signup     15%   ███
│
Activated            8%    ██

STEPPS Framework (Jonah Berger):

S - Social Currency    : Makes them look good
T - Triggers           : Top of mind
E - Emotion            : Strong feelings
P - Public             : Visible usage
P - Practical Value    : Useful to share
S - Stories            : Narrative to tell