"Growth hacking isn't a bag of tricks. It's a discipline of systematic experimentation applied to the highest-leverage parts of your growth funnel. The tactics vary. The process doesn't."
Coined by Sean Ellis in 2010 — a discipline focused on finding scalable, repeatable growth through unconventional, low-cost tactics. The "hacker" is an experimental mindset, not a viral trick.
There is no universal growth hack. There is a process for finding the lever that works for your specific product and audience. That's what this post covers.
Before running experiments, understand how your product grows. Most products have growth loops — mechanisms that, when working, produce compounding growth:
Most important principle: fix the weakest loop before investing heavily in any other. Pouring acquisition spend into a product with broken activation is pouring water into a leaky bucket.
Biggest mistake: trying to improve everything simultaneously.
How to find the constraint:
Improving activation from 10% to 20% might have more impact than improving acquisition by 50%. You have to look at the numbers to know.
Step 1: Hypothesis. "If we change [X], [Y will happen] because [Z]." Be specific. "If we show users a progress bar during onboarding, activation will increase because progress indicators create completion motivation." Vague hypotheses produce uninterpretable results.
Step 2: ICE prioritization (Impact / Confidence / Ease). Run high-impact, high-confidence, easy experiments first.
Step 3: Define success metrics before running. What's a win? How long does the test run? What minimum effect size matters? Define before you see results.
Step 4: Run. Change one variable at a time. If you change three things, you won't know which caused the result.
Step 5: Measure honestly. A test that doesn't confirm your hypothesis is valuable data. Document what you learned.
Step 6: Implement wins immediately. An experiment that succeeds but doesn't get implemented is wasted.
Dropbox referral program (2008): Gave users free storage for every successful referral. Both parties got storage. The principle: align the incentive with the product (free storage was nearly costless for Dropbox, genuinely valuable to users) and make both parties benefit.
Airbnb and Craigslist (circa 2010): Airbnb reverse-engineered Craigslist's posting flow — without an official API — to let hosts cross-post listings to Craigslist's much larger audience. Craigslist eventually blocked it; the specific tactic is not replicable. The principle: find where your target audience already exists in large numbers and build a bridge to them. Distribution leverage beats building audience from scratch.
Hotmail email footer (1996): Every outbound Hotmail email included "P.S. I love you. Get your free email at Hotmail." Hotmail grew from 20,000 to 1 million users in months. The principle: build distribution into the product itself. When every user action creates an organic touchpoint with potential new users, growth compounds without spend.
The principle behind all three: each identified a specific leverage point — referral loop, distribution, product-embedded virality — and amplified it structurally. None were tricks.
Weekly: Run one active experiment. Review data from previous experiment. Document results.
Monthly: Review the full funnel — is the current experiment targeting the actual constraint?
Quarterly: Revisit the growth loop model. Has the highest-leverage lever changed as the product evolved?
Rolling: Maintain an experiment backlog prioritized by ICE score. When one experiment ends, the next starts immediately.
Growth loop health:
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