What is Growth Hacker?

Growth Hacker is a growth-oriented role that drives explosive user growth through rapid experiments, viral loops, and data-driven tactics.

How many experiments should I run per week?

Aim for 3-5 experiments per week with clear hypotheses, metrics, and results documented for learning and scaling winners.

Are external tools or access required?

This skill is instruction-only and does not access analytics, ad accounts, or credentials; if external access is needed, the user must grant it explicitly and review each integration.

Growth Hacker

Verified

@ivangdavila

npx machina-cli add skill @ivangdavila/growth-hacker --openclaw

Files (1)

SKILL.md

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When to Use

User needs rapid user acquisition, viral growth, or unconventional marketing tactics. Agent runs experiments, builds growth loops, and optimizes funnels for startups and products seeking exponential growth.

Quick Reference

Topic	File
Experiment framework	`experiments.md`
Viral mechanics	`viral-loops.md`
Channel playbooks	`channels.md`

Core Rules

1. Experiment Everything

Never assume what works. Test with real users
Run 3-5 experiments per week minimum
Kill losers fast, double down on winners
Document every experiment: hypothesis, metric, result

2. Build for Virality

Every feature should ask: "How does this spread?"
Viral coefficient (K) > 1 = exponential growth
Types: inherent (product requires sharing), artificial (incentivized), word-of-mouth
Reduce friction in sharing to zero

3. Optimize the Pirate Metrics (AARRR)

Stage	Metric	Focus
Acquisition	Traffic sources	Where users come from
Activation	First value moment	Time to aha moment
Retention	DAU/MAU, cohorts	Users who stay
Revenue	LTV, ARPU	Money per user
Referral	K-factor, NPS	Users who invite

4. Channel Saturation Strategy

Find ONE channel that works before diversifying
Ride channels before they saturate (early TikTok, early Product Hunt)
When CAC rises, move to next channel
Own your audience (email list, community)

5. Speed Over Perfection

Ship in days, not months
Ugly but working beats beautiful and delayed
Learn from market, not from planning
"If you're not embarrassed by v1, you shipped too late"

6. Data-Driven Decisions

Track everything from day 1
Cohort analysis over vanity metrics
A/B test with statistical significance
Attribution matters: know what actually converts

7. Leverage Unconventional Tactics

Guerrilla marketing, stunts, PR hacks
Piggyback on existing platforms and audiences
Create artificial scarcity and FOMO
Make users feel like insiders

Growth Traps

Scaling paid ads before product-market fit → burning cash
Optimizing for signups instead of activation → leaky bucket
Copying competitor tactics without understanding context → wasted effort
Ignoring retention for acquisition → hamster wheel growth
Viral features that annoy users → brand damage
Vanity metrics (downloads, pageviews) over real metrics (LTV, retention)

Security & Privacy

This skill is instruction-only:

Does NOT access analytics, ad accounts, or email systems
Does NOT require API keys or credentials
Does NOT send data to external services
All tactics are guidance for the user to implement manually

If implementing tactics requires external access:

User must explicitly grant access to specific tools
Each integration should be reviewed separately

Related Skills

Install with clawhub install <slug> if user confirms:

cro — Conversion rate optimization
analytics — Track and analyze metrics
seo — Organic search growth
cmo — Brand and marketing strategy

Feedback

If useful: clawhub star growth-hacker
Stay updated: clawhub sync

Source

git clone https://clawhub.ai/ivangdavila/growth-hackerView on GitHub

Overview

Growth Hacker uses rapid experimentation, viral loops, and data-driven tactics to drive explosive user growth. It emphasizes testing, optimizing funnels using AARRR, and embedding viral mechanics into products for startups seeking exponential scale.

How This Skill Works

The skill runs 3-5 experiments per week, documenting every hypothesis, metric, and result to kill losers fast and scale winners. It builds growth loops and focuses on one-channel saturation before diversifying, leveraging AARRR metrics and cohort analysis to guide decisions, and engineering features that reduce sharing friction for virality.

When to Use It

Need rapid user acquisition and exponential growth.
Pursuing viral growth through loops and referrals.
Testing unconventional marketing tactics or guerrilla campaigns.
Optimizing funnels across Acquisition, Activation, Retention, Revenue, and Referral for startups.
Seeking a data-driven approach to fast, testable growth decisions.

Quick Start

Step 1: Define a growth objective and draft 3-5 quick experiments with hypotheses and success metrics.
Step 2: Run the experiments, collect data, and decide which variants to kill or scale.
Step 3: Review AARRR metrics, adjust the funnel, and plan the next iteration.

Best Practices

Run 3-5 experiments per week and document hypothesis, metric, and result.
Design features for inherent or incentivized virality with minimal sharing friction.
Track AARRR metrics and perform cohort analyses instead of vanity metrics.
Validate one channel at a time; scale only when CAC is sustainable.
Ship quickly and iterate; prefer learning fast over perfection.

Example Use Cases

Launch a viral referral program to boost SaaS signups.
Use guerrilla marketing or PR stunts to drive rapid awareness and early adoption.
Run onboarding experiments to shorten the time-to-activation moment.
Piggyback on platforms like Product Hunt or early TikTok campaigns to accelerate user growth.
Create scarcity and limited-time offers to ignite early demand while monitoring retention.

Frequently Asked Questions

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