Skill: ivangdavila/growth-hacker (version 1.0.0)

--- name: Growth Hacker slug: growth-hacker version: 1.0.0 homepage: https://clawic.com/skills/growth-hacker description: Drive explosive user growth through rapid experimentation, viral loops, and data-driven tactics. metadata: {"clawdbot":{"emoji":"🚀","requires":{"bins":[]},"os":["linux","darwin","win32"]}} --- ## 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`

path: channels.md
content: # Channel Playbooks — Growth Hacker

## Channel Selection Framework

### Bullseye Method

1. **Outer ring:** Brainstorm all possible channels (19+)
2. **Middle ring:** Test top 6 with cheap experiments
3. **Inner ring:** Focus on 1-2 that work

### The 19 Traction Channels

| # | Channel | Best For |
|---|---------|----------|
| 1 | Viral Marketing | Products with network effects |
| 2 | PR | Newsworthy launches, funding |
| 3 | Unconventional PR | Stunts, guerrilla marketing |
| 4 | SEM (Search Ads) | High-intent keywords |
| 5 | Social Ads | B2C, visual products |
| 6 | SEO | Long-term, content-heavy |
| 7 | Content Marketing | Thought leadership, education |
| 8 | Email Marketing | Existing lists, retention |
| 9 | Engineering as Marketing | Tools, calculators |
| 10 | Business Development | Partnerships, integrations |
| 11 | Sales | Enterprise, high ACV |
| 12 | Affiliate Programs | Products with margins |
| 13 | Existing Platforms | Marketplaces, app stores |
| 14 | Trade Shows | Industry-specific B2B |
| 15 | Offline Events | Local, community |
| 16 | Speaking Engagements | Founder brand |
| 17 | Community Building | Niche audiences |
| 18 | Influencer Marketing | Consumer products |
| 19 | Offline Ads | Mass market awareness |

## Channel-Specific Playbooks

### Product Hunt Launch

**Preparation (2-4 weeks before):**
- Build hunter relationships
- Gather testimonials and social proof
- Prepare assets (video, images, copy)
- Line up supporters to upvote and comment

**Launch Day:**
- Launch at 12:01 AM PT
- Founder engages in comments ALL day
- Share to existing audience (email, social)
- Do NOT ask directly for upvotes (against rules)

**Success metrics:**
- Top 5 = significant traffic
- #1 = long-term SEO and credibility

### Reddit Growth

**Rules:**
- 90% value, 10% promotion
- Become genuine community member first
- Never spam or self-promote obviously
- Follow subreddit rules strictly

**Tactics:**
- Answer questions in relevant subreddits
- Create genuinely useful resources
- Do AMAs when you have credibility
- Participate in discussions authentically

### Twitter/X Growth

**Content strategy:**
- Threads perform 5-10x better than single tweets
- Hook in first line (curiosity, controversy, value)
- Visual content gets 2-3x engagement
- Reply to bigger accounts in your niche

**Growth tactics:**
- Tweet 3-5 times daily
- Engage for 30 min before and after posting
- Build relationships with similar-sized accounts
- Cross-promote threads to other platforms

### TikTok/Reels/Shorts

**What works:**
- First 3 seconds hook is everything
- Native, raw content over polished
- Trends + your niche angle
- Behind-the-scenes, tutorials, reactions

**Volume matters:**
- Post 1-3 times daily minimum
- Expect 1 in 20 to hit
- Double down on formats that work

### Cold Email Outreach

**Formula:**
1. Personalized first line (real research)
2. One clear value proposition
3. Social proof (one line)
4. Single clear CTA
5. Keep under 100 words

**Best practices:**
- Warm up new domains before sending
- Respect anti-spam regulations (CAN-SPAM, GDPR)
- Provide clear unsubscribe options
- Monitor deliverability and bounce rates

### SEO for Startups

**Quick wins:**
- Target long-tail keywords (lower competition)
- Create comparison pages (vs competitors)
- Build tool pages that earn backlinks
- Guest post on industry blogs

**Programmatic SEO:**
- Generate pages at scale (location, category)
- Template + unique data = unique pages
- Examples: Zapier integrations, Nomadlist cities

## Channel Economics

| Metric | Formula | Target |
|--------|---------|--------|
| CAC | Total spend / New customers | Lower than LTV/3 |
| LTV | ARPU * Lifetime months | Higher than 3x CAC |
| Payback | CAC / Monthly revenue per user | Under 12 months |
| ROAS | Revenue / Ad spend | Above 3x |

## Channel Maturity Curve

1. **Discovery:** Channel is new, early adopters dominate
2. **Growth:** Channel scales, costs are low
3. **Saturation:** Everyone piles in, costs rise
4. **Decline:** Returns diminish, move on

**Strategy:** Enter channels in Discovery/Growth phase. Exit at Saturation.

## Multi-Channel Attribution

**Models:**
- **Last touch:** Credit to final channel
- **First touch:** Credit to discovery channel
- **Linear:** Equal credit to all touchpoints
- **Time decay:** More credit to recent touches

**Recommendation:** Use multi-touch for understanding, last-touch for optimization.


path: experiments.md
content: # Experiments Framework — Growth Hacker

## Experiment Document Template

```markdown
## Experiment: [Name]
**Date:** YYYY-MM-DD
**Owner:** [Name]
**Status:** Planning | Running | Analyzing | Completed

### Hypothesis
If we [action], then [metric] will [change] because [reason].

### Metrics
- Primary: [Metric to move]
- Secondary: [Guard rails]
- Sample size needed: [Number]

### Design
- Control: [Current state]
- Variant: [Change being tested]
- Duration: [Days/weeks]
- Audience: [Segment]

### Results
- Control: [Result]
- Variant: [Result]
- Lift: [Percentage]
- Confidence: [Statistical significance]

### Decision
[ ] Ship variant
[ ] Keep control
[ ] Iterate and retest

### Learnings
[What we learned regardless of outcome]
```

## Experiment Prioritization (ICE Score)

| Factor | Scale | Description |
|--------|-------|-------------|
| Impact | 1-10 | How much will this move the needle? |
| Confidence | 1-10 | How sure are we it will work? |
| Ease | 1-10 | How easy is it to implement? |

**ICE Score = (Impact + Confidence + Ease) / 3**

Run experiments with highest ICE first.

## Weekly Experiment Cadence

| Day | Activity |
|-----|----------|
| Monday | Review last week results, plan new experiments |
| Tuesday-Thursday | Run experiments, collect data |
| Friday | Analyze results, document learnings |

## Minimum Viable Experiments

### Landing Page Tests
- Headline variations (5 min to set up)
- CTA button text and color
- Social proof placement
- Pricing display

### Onboarding Tests
- Number of steps
- Required vs optional fields
- Tutorial vs immediate access
- Progress indicators

### Retention Tests
- Email timing and frequency
- Push notification copy
- Re-engagement triggers
- Feature discovery prompts

### Viral Tests
- Share button placement
- Referral incentives
- Social proof displays
- Invite flow friction

## Statistical Significance Quick Guide

| Sample Size | Minimum Lift Detectable |
|-------------|------------------------|
| 100 per variant | ~30% lift |
| 500 per variant | ~15% lift |
| 1,000 per variant | ~10% lift |
| 5,000 per variant | ~5% lift |

**Rule:** If you need to squint to see the difference, you need more data.

## Failed Experiment Value

Every failed experiment teaches you:
1. What your users do NOT want
2. Assumptions that were wrong
3. Segments that behave differently
4. Ideas for new experiments

**Document failures as rigorously as wins.**


path: viral-loops.md
content: # Viral Loops — Growth Hacker

## Viral Coefficient Formula

```
K = i * c

K = Viral coefficient
i = Invitations sent per user
c = Conversion rate of invitations
```

| K Value | Growth Pattern |
|---------|---------------|
| K < 1 | Declining (need paid/organic) |
| K = 1 | Stable (replacing churn) |
| K > 1 | Exponential growth |

**Goal:** Get K above 1, even temporarily, to create growth spurts.

## Types of Viral Loops

### 1. Inherent Virality
Product requires sharing to function.

**Examples:**
- Slack (team communication)
- Splitwise (expense sharing)
- Multiplayer games

**Implementation:**
- Core feature involves others
- Value increases with more users
- Impossible to use alone

### 2. Artificial Virality
Incentivized sharing.

**Examples:**
- Dropbox (+500MB for referrals)
- Uber ($20 credit for referrals)
- PayPal ($10 for signups)

**Implementation:**
- Two-sided rewards (giver AND receiver)
- Instant gratification
- Clear value proposition

### 3. Word-of-Mouth Virality
Users share because product is remarkable.

**Examples:**
- ChatGPT (mind-blowing experience)
- Superhuman (status symbol)
- Notion (template sharing)

**Implementation:**
- Create "wow" moments
- Build shareable outputs
- Make users look good

### 4. Collaborative Virality
Working together spreads the product.

**Examples:**
- Google Docs (shared editing)
- Figma (design collaboration)
- Miro (team whiteboarding)

**Implementation:**
- Easy invite flow
- Guest access without signup
- Visible "Powered by X" branding

## Viral Loop Optimization

### Reduce Friction at Every Step

| Step | Friction Killers |
|------|-----------------|
| Trigger to share | One-click sharing, pre-written copy |
| Invitation delivery | SMS > Email > In-app |
| Landing experience | Personalized, shows who invited |
| Signup | Social login, minimal fields |
| First value | Immediate, connected to invitation |

### Increase Invitation Volume

- Prompt at peak happiness moments
- Gamify referrals (leaderboards)
- Remind about unused invites
- Make sharing part of core flow

### Improve Conversion Rate

- Personal invitations over broadcast
- Clear value proposition for invitee
- Urgency and scarcity
- Social proof (X friends already use this)

## Viral Timing Windows

| Moment | Why It Works |
|--------|-------------|
| After first success | User is happy, wants to share |
| During onboarding | Fresh excitement |
| Achievement unlocked | Pride moment |
| Before paywall | Earn access through sharing |

**Anti-pattern:** Asking for shares when user is frustrated or confused.

## Measuring Viral Success

### Track These Metrics

- **Invites per user:** How many people does each user invite?
- **Invite acceptance rate:** What percentage accept?
- **Time to invite:** How long before users invite?
- **Viral cycle time:** Days from signup to invitee signup

### Viral Cycle Time Matters

```
Users after 30 days with different cycle times:

Starting: 100 users, K = 1.5

Cycle time 2 days:  100 → 14,000 users
Cycle time 7 days:  100 → 1,200 users
Cycle time 30 days: 100 → 150 users
```

**Faster cycles = exponentially more growth.**

## Dark Patterns to Avoid

- Spam invites without consent
- Misleading invitation messages
- Forced sharing to access features
- Address book harvesting

These destroy trust and trigger platform bans.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)