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About
Growth Hacking Tactics
Overview
Growth hacking isn't "one weird trick to 10x your users." It's a systematic approach to finding and scaling the highest-leverage growth levers through rapid experimentation. The mistake: copying tactics without understanding the underlying growth model. A tactic that works for a consumer social app (viral invite loop) will fail for enterprise SaaS (sales motion). This skill covers growth loops, viral mechanics, referral flywheels, PLG hacks, and the experimentation framework to find what works for YOUR product.
When to Use
Trigger phrases: "growth hacking", "growth loops", "viral growth", "growth experiment", "referral flywheel", "growth tactics", "low-cost acquisition", "PLG growth hack", "how to grow faster", "growth model"
Authoritative Foundations
Brian Balfour — Growth Loops vs Funnels
Funnels are linear: acquire → activate → retain → revenue → refer. Loops are circular: the OUTPUT of one cycle becomes the INPUT of the next. Growth loops compound. Funnels don't. Every great growth company has a dominant growth loop.
Sean Ellis — Hacking Growth Process
- Analyze: Data. Find the biggest opportunity.
- Ideate: Brainstorm experiments. Score with ICE (Impact, Confidence, Ease).
- Prioritize: Run highest-ICE experiments first.
- Test: Run the experiment. Measure result.
- Scale: Kill what failed. Double down on what worked.
Andrew Chen — The Cold Start Problem
Networked products have a "cold start" problem: they're worthless until enough users join. The solution: build an "atomic network" — the smallest possible network where the product provides value. Tinder: one college campus. Slack: one team. Uber: one city.
Growth Models (Pick Your Dominant Loop)
| Model | How It Works | Best For | Example | |---|---|---|---| | Content Loop | Content → traffic → signups → more content | Content-driven SaaS, SEO-heavy | HubSpot, Ahrefs | | Viral Loop | User invites → new user → more invites | Consumer, social, collaboration tools | Slack, Notion, Loom | | Sales Loop | Outbound → demos → customers → revenue → more SDRs | B2B SaaS, enterprise | Salesforce, Gong | | Product-Led Loop | Free product → usage → upgrade → more usage | Developer tools, freemium | Miro, Figma, Notion | | Paid Loop | Ads → signups → revenue → reinvest in ads | High-margin, high-LTV | Any profitable paid channel | | Partner Loop | Partner → referral → customer → better partner program | Marketplace, integration-heavy | Shopify, Stripe | | Community Loop | Community → engagement → product adoption → community growth | Developer tools, creator economy | Figma, Webflow, Notion |
25 Growth Hacking Tactics
Content & SEO Tactics
- Programmatic SEO: Generate 1,000+ landing pages targeting long-tail
keywords. Pattern: "[City] [Service]" or "[Integration] + [Use Case]." Tool: AI content + Webflow/Next.js template.
- Competitor comparison pages: "X vs Y" pages for every competitor.
These rank quickly (buyers search for them) and convert at 5-10%.
- Template galleries: Free templates (Notion, Figma, Google Sheets)
that include your branding and product links. Notion's template gallery drives 5M+ monthly visits.
- "Best X tools" listicles: Get listed on every "best [category] tools"
roundup. Reach out to authors. Offer unique data or quotes.
- Free tools directory listings: Get listed on Product Hunt, G2,
Capterra, GetApp, AlternativeTo, SaaSWorthy, and niche directories.
Product-Led Growth Tactics
- Sidecar free tool: Build a free micro-tool that solves one small
problem for your ICP — and naturally leads to your paid product. Example: HubSpot's Website Grader → CRM. Ahrefs' free backlink checker → paid suite.
- Collaboration as acquisition: When a user shares a file/link/page
with a non-user, that non-user sees your product. Loom, Notion, Figma, and Miro all grew this way.
- Watermark / "Powered by" link: Free plan includes your branding.
Typeform, Hotjar, and Calendly all used this to drive B2B growth.
- Invite-to-unlock: "Invite 3 teammates to unlock [feature/premium
trial]." Dropbox's famous referral program gave 500MB per invite.
- Public-by-default: User-generated content is public and indexed.
Canva designs, Notion pages, Substack posts — all discoverable.
Viral & Referral Tactics
- Double-sided referral rewards: "You get $10, they get $10."
PayPal, Dropbox, and Uber all used this. Works best when the reward is core product value, not cash.
- Referral leaderboard: Public leaderboard of top referrers with
prizes. Harry's razors got 100K emails pre-launch via referral contest.
- Waitlist referral priority: "Jump the line by referring friends."
Robinhood's waitlist hit 1M users before launch. Position in line improved with each referral.
- Milestone unlocks: "Unlock [premium template/tool] when 3 friends
sign up." Lower friction than "refer for cash."
- Social share for bonus: "Share on LinkedIn for [bonus features/
extended trial]." Low-cost, high-reach.
Community & Distribution Tactics
- Community as moat: Build a community (Slack, Discord, WhatsApp)
where your ICP hangs out. Figma's community, Notion's ambassador program, Webflow's forum — all drive product adoption.
- Integration marketplaces: List in your partners' marketplaces.
Every Slack app, every Notion integration, every HubSpot integration is a distribution channel.
- Newsletter swaps: Trade newsletter recommendations with 5
complementary newsletters. Each swap = 50-500 new subscribers.
- Podcast guesting flywheel: 1 podcast → 1K listeners → 100
newsletter subs → 10 demos. Do 2 podcasts/month = 2,400 subs/year.
- Launch aggregators: Launch on Product Hunt, Hacker News, BetaList,
Uneed, SaaSHub. Each launch = 500-5,000 new users.
Low-Cost Paid Tactics
- LinkedIn "Boosted" posts: Boost organic posts that already perform
well. 5-10x cheaper than LinkedIn Ads proper. $100/post can reach 10-20K ICP.
- Retargeting: 2% of visitors convert on first visit. Retargeting
captures the other 98%. $5-10/day on retargeting can 2x conversion.
- Newsletter sponsorships: Sponsor 3 newsletters reaching your ICP.
$200-1,000 per sponsorship. 1-5% clickthrough. Track with UTM.
- Reddit Ads: Target specific subreddits where your ICP hangs out.
r/SaaS, r/startups, r/Entrepreneur. $5 CPM. High intent but very anti-marketing — be genuine.
- Affiliate/referral for customers: Existing customers refer you
for 10-15% of first-year revenue. Lower CAC than paid ads. Higher close rates (warm intro > cold).
The Growth Experimentation Process
1. Identify Your North Star Metric
One metric that captures the core value your product delivers:
- Airbnb: Nights booked
- Spotify: Time spent listening
- Slack: Messages sent
- Stripe: Payment volume processed
- LeadMagic: Emails verified
2. Build Your Growth Model
Map the equation:
[North Star Metric] = [Acquisition] × [Activation] × [Retention] × [Referral] × [Revenue]
Example (SaaS):
ARR = Traffic × Signup Rate × Activation Rate × Paying Rate × ACV × Retention Rate
3. Find the Biggest Lever
Which variable has the most room for improvement?
- If Activation is 15% (industry avg 20-30%): biggest lever.
- If Retention is 95%: not the lever. Move on.
- Focus on ONE lever at a time.
4. Run Experiments (ICE Framework)
EXPERIMENT NAME: [descriptive]
HYPOTHESIS: We believe [change] will increase [metric] by [X%] because [reason].
ICE SCORE:
- Impact (1-10): [how big if it works?]
- Confidence (1-10): [how sure are we?]
- Ease (1-10): [how easy to implement?]
TOTAL: [I × C × E = score. Sort descending. Run highest first.]
RESULT: [metric before → after]
LEARNING: [what did we learn?]
DECISION: [scale / iterate / kill]
5. Scale What Works, Kill What Doesn't
| Result | Decision | |---|---| | Beat target by 20%+ | Scale. Invest more resources. | | Hit target ±20% | Iterate. Try a variant. | | Missed by 20%+ | Kill. Document learning. Move on. | | Broke something | Kill immediately. Post-mortem. |
Output Format
GROWTH EXPERIMENT PLAN — [Company]
NORTH STAR METRIC: [metric]
CURRENT: [value]. TARGET: [value]
GROWTH MODEL:
[Equation showing how North Star is built]
BIGGEST LEVER: [variable] — currently at X%. Industry benchmark: Y%.
THIS WEEK'S EXPERIMENTS:
| # | Experiment | ICE | Owner | Due | Result |
|---|---|---|---|---|
| 1 | [name] | 270 | [name] | [date] | — |
| 2 | [name] | 210 | [name] | [date] | — |
| 3 | [name] | 160 | [name] | [date] | — |
SCALED (last week's winners):
- [Experiment]: increased [metric] by X%. Scaling by [action].
KILLED (last week's losers):
- [Experiment]: no significant impact. Learnings: [insight].
Implementation Checklist
- [ ] North Star Metric defined (ONE metric, not a dashboard)
- [ ] Growth model mapped (equation linking inputs to North Star)
- [ ] Biggest lever identified (data-driven, not gut feel)
- [ ] Experiments scored with ICE before running
- [ ] Every experiment has a hypothesis (not "let's try X and see")
- [ ] Results documented: metric before → after, learning, decision
- [ ] Kill decisions are fast (underperforming experiments die within 1 week)
- [ ] Scale decisions are data-backed (statistical significance, not randomness)
Quality Check
Before delivering, verify:
- [ ] Output matches the user's stated request
- [ ] Named frameworks or sources are reflected in the recommendation
- [ ] The deliverable is specific enough for an agent to execute
- [ ] Any assumptions, risks, or dependencies are explicit
- [ ] No unsupported claims, invented facts, or private/internal references are included
Common Pitfalls
- Tactic copying without model understanding. "Dropbox did a referral
program. We should too!" But you're an enterprise SaaS company where referrals come from relationships, not viral loops. Fix: Build your growth model first. THEN pick tactics that fit your model.
- Running too many experiments. 10 simultaneous experiments = can't
isolate what worked. Fix: 2-3 experiments per week max. One variable changed per experiment. Everything else held constant.
- Over-optimizing the wrong metric. Growing signups 50% while
activation stays at 10% = growing a leaky bucket. Fix: Find the bottleneck. Fix activation BEFORE scaling acquisition.
- Declaring victory too early. "Our experiment increased conversion
by 15%!" With n=20. Statistical noise. Fix: Minimum 100 conversions per variant before calling a winner. Use a significance calculator.
- Scaling unscalable tactics. "We got 100 users from manually DMing
people on LinkedIn." Great. Now automate it or find a scalable channel. Don't do 1,000 manual DMs. Fix: Scalable > manual. Find channels that compound.
- Killing too slow. "Let's give it another week." 3 weeks later: same
result. 3 months of momentum lost. Fix: Kill threshold: if confidence interval suggests it won't hit target, kill immediately. Move on.
Execution Artifacts
references/framework-notes.md— Named frameworks and reference tablestemplates/output-template.md— Deliverable shell for agent outputscripts/check-output.py— Lightweight deliverable validator
Related Skills
growth-experimentation— ICE scoring, growth sprints, experiment designvibe-marketing— AI-powered marketing at scaleai-content-creation— AI content workflowscontent-led-growth— Founder content engineplg-strategy— Product-led growth strategyreferral-programs— Referral program designfreemium-optimization— Freemium conversion optimization
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: LeadMagic
- Source: LeadMagic/gtm-skills
- License: MIT
- Homepage: https://github.com/LeadMagic/gtm-skills
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.