Growth Hacking Is a Process, Not a Trick
Growth hacking is not a quick fix. It's a repeatable process of testing, learning, and improving over time.
Fall in love with the process, and the results will come. — Eric Thomas
A quick look into the process
Find product-market fit
Set the five prerequisites
Implement rapid experimentation (G.R.O.W.S)
Develop playbooks to iterate and scale
Growth marketing is a system
There is no single tactic that makes companies successful. The teams that scale run an organized, data-driven process.
If you do not have a plan for researching, prioritizing, designing, testing, and analyzing experiments, you will not get consistent paying customers.
There is no universal formula. Growth hacking is a simple step-by-step process.
Scraping, automation, virality loops, and other tactics can be powerful, but without a system they rarely create durable growth.
A quick look into the process
Hacky tactics only work with a system
Shortcuts can create spikes, but only a disciplined process turns them into lasting growth.
Find Product-Market Fit
A product that grows fast is worthless if people do not truly need it. If users would not notice it disappearing, growth will not save you.
Growth before PMF is a weak foundation
Scaling before demand is real is like building a house on sand. Focus on the right customers, understand their needs, and build a product they want to talk about.
Signals you are close to PMF
- Users would be disappointed if the product disappeared.
- People talk about the product and recommend it.
- Retention is strong and usage is meaningful.
- Customers are willing to pay and revenue is repeatable.
Structured PMF tests
Sean Ellis "Very Disappointed" method
- -Ask active users: "How would you feel if you could no longer use our product tomorrow?"
- -Options: extremely upset, somewhat upset, not upset at all, or I no longer use this.
- -If 40%+ answer "very disappointed," you have a strong PMF signal.
Brian Balfour Trifecta
- -Strong organic growth and referrals.
- -High retention and low churn for the category.
- -Meaningful, frequent usage that reflects the core value.
When can growth hacking start?
There is overlap between Problem-Solution Fit and PMF. At this stage, use growth to explore data and behavior patterns. Use tools like the Bullseye Template from Traction to focus on promising channels, but never use growth tactics to mask weak demand.
Timing matters
Once product validation is clear, growth processes start paying off. The right strategy at the right time turns a good product into a fast-growing business.
Set the five prerequisites
After PMF, growth still needs a foundation. Align the team on these prerequisites before rapid experimentation.
Growth is a team sport. Everyone needs to understand the system so experiments stay focused and measurable.
Business Model Canvas
A one-page map of your value proposition, customers, channels, operations, and economics. It aligns teams and speeds onboarding.
Value Proposition Canvas
Clarifies how your product solves real customer pains and creates gains. It should reflect real behavior, not assumptions.
Personas
Define 2 to 3 key personas deeply: goals, behaviors, pain points, alternatives, and decision criteria. Validate with feedback.
Pirate Funnel (AAARRR)
Map the user journey (Awareness, Acquisition, Activation, Retention, Referral, Revenue) and define the key actions and metrics.
OMTM + North Star
Choose the One Metric That Matters right now. It changes over time but should always move you toward the North Star.
Persona guidelines
- -Focus on the 2 to 3 most important personas first.
- -Define deeper traits: goals, behaviors, day-in-the-life, and current alternatives.
- -Validate and refine personas through real tests and feedback.
OMTM vs North Star
The OMTM is a short-term focus that changes as you hit milestones. The North Star is the long-term direction. Example: this month you focus on trial conversion while the North Star is total hours delivered or recurring revenue.
Implement Rapid Experimentation (G.R.O.W.S)
The growth loop makes experimentation predictable, fast, and measurable. It helps teams find the few experiments that unlock outsized growth.
Whether you follow the Sean Ellis or Growth Tribe flavor, the structure is what creates speed and learning.
Gather Ideas
Collect hypotheses that could improve your OMTM.
- -Observe your market: best practices, trends, articles, and competitor patterns.
- -Quantitative data shows what happens; qualitative data explains why.
- -Use a clear format: concept title, 5Ws + H, theory, success metric, minimum benchmark.
- -Use a shared system to capture ideas, rank them, and track outcomes.
Rank Ideas
Prioritize with a scoring model like ICE, BRASS, or PIES.
- -Ask the team to nominate a few top ideas before the sprint meeting.
- -Decide and ship the best-scoring experiments each cycle.
- -Include low-hanging fruit to keep momentum high.
Outline Experiments
Design fast experiments that validate potential before heavy investment.
- -Define roles: Growth Lead, Developer, Designer, Analyst.
- -Use agile rituals to keep velocity high.
- -Done is better than perfect when the goal is speed and learning.
Work the Plan
Execute the 20% of work that yields 80% of results.
- -Optimize for speed and learning, not perfection.
- -Agile Scrum principles keep the team aligned and shipping.
Study the Data
Analyze carefully and classify outcomes: inconclusive, failed (learned), failed (tweak), success (explore), success (scale).
- -Expect failures; they are part of the path to a breakthrough.
- -Segment results by device, audience, geography, or product cohort.
- -Document learnings so the next tests are smarter.
How to analyze experiments
- -End the experiment after 1 to 3 weeks to reduce seasonality.
- -The growth lead reviews results using a consistent evaluation template.
- -Classify outcomes: inconclusive, failure (no tweak), failure (tweak), success (explore), success (scale).
A/B testing prerequisites
- -You need enough volume. Aim for 1,000 conversions on the target action.
- -Early-stage teams should test bigger changes, not tiny tweaks.
- -Choose a statistical approach that matches your speed, risk tolerance, and team communication.
A/B testing notes
Frequentist approach
- -Lower risk of false positives, but requires higher significance (95%+).
- -Slower velocity because you need more data before calling a winner.
- -Harder to communicate to non-technical teams.
Bayesian approach
- -Higher velocity with probability thresholds (ex: 80% = winner).
- -Better for fast-moving teams where speed matters.
- -Easier to communicate: "Variant B has an 84% chance to win."
Develop playbooks to iterate and scale
Document every experiment with its hypothesis, setup, results, and learnings.
- Avoid repeating failed tests and accelerate new team onboarding.
- Turn wins into repeatable playbooks.
- Keep stakeholders aligned with a single source of truth.
Keep communication open. Many top teams share weekly updates or maintain a dedicated channel for results and learnings.