ID8GROWTH - Growth Engine

Purpose

Scale your launched product through systematic experimentation. Growth is not magic—it's methodology.

Philosophy: Retention beats acquisition. One channel mastered beats five attempted. Data over intuition.

When to Use

• •Product is launched and has initial users
• •User needs to grow user base
• •User asks "how do I get more users?"
• •User wants to improve retention
• •User needs help with analytics
• •User wants to optimize conversion
• •Project is in LAUNCHING or GROWING state

Commands

/growth <project-slug>

Run full growth analysis and planning.

Process:

1. •BASELINE - Understand current metrics
2. •MODEL - Map growth mechanics
3. •DIAGNOSE - Find bottlenecks
4. •HYPOTHESIZE - Generate experiments
5. •PRIORITIZE - ICE scoring
6. •EXECUTE - Run experiments
7. •LEARN - Analyze and iterate

/growth metrics

Audit current analytics and define key metrics.

/growth funnel

Analyze conversion funnel and identify drop-offs.

/growth experiment <hypothesis>

Design a specific growth experiment.

/growth retention

Deep dive on retention and engagement.

Growth Philosophy

Solo Builder Reality

Growth Priorities

Stage 1: Pre-PMF (< 100 users)

• •Focus: Finding users who love it
• •Metric: Qualitative feedback, NPS
• •Don't worry about: Scale

Stage 2: Early Traction (100-1000 users)

• •Focus: Retention and activation
• •Metric: Day 1/7/30 retention
• •Don't worry about: Growth rate

Stage 3: Growth (1000+ users)

• •Focus: Scalable acquisition
• •Metric: CAC, LTV, growth rate
• •Now optimize: Everything

Process Detail

Phase 1: BASELINE

Establish current state:

If no tracking:

• •Set up analytics first
• •Use analytics-tracking skill
• •Minimum: Sign-ups, activation, retention

Phase 2: MODEL

Map your growth mechanics:

ACQUISITION
How do users find you?
├── Organic search
├── Social/content
├── Referrals
├── Paid (if any)
└── Direct

ACTIVATION
What's the "aha moment"?
├── First action completed
├── Value received
└── Setup finished

RETENTION
Why do they come back?
├── Core value loop
├── Notifications
├── Habit formation
└── New content/features

REVENUE
How do you monetize?
├── Subscription
├── Usage-based
├── One-time
└── Freemium conversion

REFERRAL
How do they spread it?
├── Word of mouth
├── Built-in sharing
├── Incentivized referral
└── Social proof

Phase 3: DIAGNOSE

Find the bottleneck:

Diagnosis framework:

1. •Compare to benchmarks
2. •Identify biggest drop-off
3. •That's your focus

Phase 4: HYPOTHESIZE

Generate experiment ideas:

For each bottleneck, generate 3-5 hypotheses:

If we [change]
Then [metric] will [improve/increase/decrease]
Because [reasoning]

Example:

If we add an onboarding checklist
Then activation rate will increase by 20%
Because users will know what to do next

Phase 5: PRIORITIZE

ICE Scoring:

Definitions:

• •Impact: How much will this move the metric?
• •Confidence: How sure are we it will work?
• •Ease: How easy is it to implement?

Rule: Do highest ICE score first.

Phase 6: EXECUTE

For each experiment:

1. •Define hypothesis clearly
2. •Define success metric
3. •Define sample size needed
4. •Implement change
5. •Run for sufficient time
6. •Analyze results
7. •Document learnings

Minimum experiment duration:

• •High traffic: 1-2 weeks
• •Low traffic: 2-4 weeks
• •Statistical significance matters

Phase 7: LEARN

After each experiment:

Framework References

Growth Loops

frameworks/growth-loops.md - Viral, content, flywheel mechanics

Analytics

frameworks/analytics.md - Metrics, tracking, dashboards

Acquisition

frameworks/acquisition.md - Channels, CAC, scale

Retention

frameworks/retention.md - Engagement, churn, habit

Optimization

frameworks/optimization.md - A/B testing, CRO

Output Templates

Growth Model

templates/growth-model.md - Growth strategy document

Metrics Dashboard

templates/metrics-dashboard.md - KPI tracking structure

Tool Integration

MCPs

Supabase:

• •Query user data for analysis
• •Cohort analysis
• •Funnel tracking

Perplexity:

• •Research growth tactics
• •Find benchmarks
• •Competitor analysis

Skills

analytics-tracking:

• •Set up tracking
• •Define events
• •Create dashboards

Handoff

After completing growth analysis:

1. •

   Save outputs:

   • •Growth model → docs/GROWTH_MODEL.md
   • •Metrics → docs/METRICS.md
2. •

   Log to tracker:

   code

   /tracker log {project-slug} "GROWTH: Analysis complete. Focus: {bottleneck}. Top experiment: {experiment}."
   

3. •

   Update state:

   code

   /tracker update {project-slug} GROWING
   

4. •

   Next steps:

   • •Execute top-priority experiments
   • •Review results weekly
   • •When stable, transition to ops

Key Metrics Cheat Sheet

AARRR Funnel

Benchmarks

Anti-Patterns

Quality Checks

Before finalizing growth plan:

• • Baseline metrics established
• • Biggest bottleneck identified
• • Hypotheses are testable
• • Experiments are prioritized
• • Success metrics defined
• • Realistic timeline set
• • Learning process planned