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Growth Hacking — Startup Growth Tactics & Viral Loops

by Gingiris · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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/install growth-hacking
Description
Battle-tested growth hacking playbook for B2B SaaS, AI products, and developer tools. Covers viral loop design, acquisition channel experiments, retention ho...
README (SKILL.md)

Growth Hacking — Startup Growth Tactics & Viral Loops

Gingiris Growth Series | Battle-tested playbooks from 150+ AI startup consultations

What Is Growth Hacking?

Growth hacking is systematic, data-driven experimentation across the full funnel to find the most efficient paths to growth. It's not tricks — it's a framework for finding leverage.

The Growth Experiment Framework

ICE Scoring Model

Every growth idea gets scored before building:

  • Impact (1-10): How much will this move the needle if it works?
  • Confidence (1-10): How sure are we this will work?
  • Ease (1-10): How easy/fast is it to implement?
  • ICE Score = (I + C + E) / 3 — prioritize highest scores first

2-Week Sprint Structure

  1. Day 1: Ideation session → 20+ growth ideas
  2. Day 2: ICE scoring → top 5 experiments
  3. Days 3-12: Build and run experiments (minimum 100 data points each)
  4. Day 13-14: Analyze results, kill losers fast, double down on winners

Viral Loop Design

The 4 Types of Viral Loops

Type Mechanic Example
Inherent virality Product creates content others see Canva "Made with Canva"
Referral loops User incentivized to invite others Dropbox storage bonus
Social proof Usage signals spread organically Twitter follower counts
Content virality Users share outputs HeyGen AI videos

Viral Loop Implementation Checklist

  • Identify natural sharing moment in product flow
  • Reduce friction: 1-click share to major platforms
  • Add value attribution: "Created with [Product]" watermark/badge
  • Track viral coefficient (K-factor): K = invites_sent × conversion_rate

Target K > 0.5 first, then > 1.0 for true virality

Acquisition Channel Stack

Channel Prioritization Matrix

Channel Cost Scale Speed Best For
SEO/Content Low High Slow SaaS, dev tools
Product Hunt Low Medium Fast Launch spike
Reddit/HN Low Medium Medium Developer tools
Referral Low High Slow Consumer + prosumer
LinkedIn Organic Low Medium Medium B2B SaaS
Cold outbound Medium Medium Fast B2B enterprise

The Channel Stacking Formula

  1. Foundation (months 1-3): SEO + 1 community channel
  2. Amplification (months 3-6): Add referral program + 1 paid channel test
  3. Scale (months 6-12): Double down on 2-3 proven channels

Activation Optimization

Finding Your Aha Moment

HeyGen case study: First AI video generated within 90 seconds of signup = 80% 30-day retention. Before optimizing to this, retention was 30%.

Framework:

  1. Identify top 20% of retained users
  2. Find the actions they took in first session that others didn't
  3. That's your Aha moment — build your onboarding to get there faster

Activation Funnel Template

Signup → [Aha Moment] within [X minutes/actions]
         ↓
         Activation rate = users who hit Aha / total signups

Industry benchmarks:

  • SaaS activation rate: 25-40% (good), 40%+ (excellent)
  • Time to Aha: \x3C 5 minutes (ideal), \x3C 15 minutes (acceptable)

Retention Engineering

The Habit Loop Framework

Trigger → Action → Reward → Investment

For SaaS:

  • Trigger: Daily digest email, notification, calendar event
  • Action: Core product use (create report, sync data, etc.)
  • Reward: Insight, saved time, accomplishment
  • Investment: More data stored = more valuable = harder to leave

Re-engagement Sequences

Day Action
Day 1 Welcome email with single next action
Day 3 "How to get value in 5 minutes" tutorial
Day 7 Case study from similar user
Day 14 Feature they haven't tried yet
Day 30 Direct outreach from founder (for B2B)

Growth Metrics Dashboard

AARRR Framework

  • Acquisition: CAC by channel, traffic by source
  • Activation: % hitting Aha moment, time to first value
  • Retention: D1/D7/D30 retention, cohort analysis, churn rate
  • Revenue: MRR, ARR, ARPU, LTV, LTV:CAC ratio
  • Referral: K-factor, viral coefficient, referral program conversion

North Star Metric Selection

Company Type North Star Metric
B2B SaaS Weekly Active Accounts
Consumer app Daily Active Users
Marketplace GMV or transactions
Developer tool API calls / integrations

Part of the Gingiris Growth Series — AI product growth playbooks for founders and PMs.

Usage Guidance
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How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install growth-hacking
  3. After installation, invoke the skill by name or use /growth-hacking
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: viral loop design, ICE scoring framework, channel stacking, activation optimization, and retention engineering playbook
Metadata
Slug growth-hacking
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Growth Hacking — Startup Growth Tactics & Viral Loops?

Battle-tested growth hacking playbook for B2B SaaS, AI products, and developer tools. Covers viral loop design, acquisition channel experiments, retention ho... It is an AI Agent Skill for Claude Code / OpenClaw, with 91 downloads so far.

How do I install Growth Hacking — Startup Growth Tactics & Viral Loops?

Run "/install growth-hacking" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Growth Hacking — Startup Growth Tactics & Viral Loops free?

Yes, Growth Hacking — Startup Growth Tactics & Viral Loops is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Growth Hacking — Startup Growth Tactics & Viral Loops support?

Growth Hacking — Startup Growth Tactics & Viral Loops is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Growth Hacking — Startup Growth Tactics & Viral Loops?

It is built and maintained by Gingiris (@gingiris); the current version is v1.0.0.

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