MarketingBeginnerPreview
Growth Hacking
A practical, evidence-driven course that teaches you to find your real growth lever, pick a North Star metric, and run a high-tempo experiment loop across the full AARRR funnel so you can scale a product on a small budget without guessing.
Beginners, founders, marketers, and product people who own a product or funnel and want sustainable growth without a large team or budget.
Course content
Workbook & downloads
Put the course into practice — a printable workbook plus editable templates you can fill in and reuse.
Preview the workbook
This workbook turns the course into reps you can run on a real product. Each section mirrors one course module with hands-on exercises, fill-in worksheets, and checklists you apply to your own product or funnel. Pick one product, app, or offer you own and carry it through every section, and you will finish with a mapped AARRR funnel, a chosen North Star metric, a prioritised experiment backlog, a quantified aha moment, and your first compounding growth loop sketched out.
What Growth Hacking Really Is
Build an accurate model of growth as a process — the AARRR funnel and the metric hierarchy — before you change anything.
Worksheet: Map Your AARRR Funnel
Pull real numbers for a recent period (e.g. last 30 days) and fill in each stage. Use whatever analytics you have; estimates beat blanks, but mark which numbers are guesses so you know what to instrument.
- Acquisition: visitors or installs in the period, and the top channel they came from
- Activation: number and percentage who reached a first valuable experience
- Retention: number and percentage still active after one full cadence (day 7 / week 4 / month 1)
- Referral: number who invited or recommended someone, and the resulting new users
- Revenue: number who paid or upgraded, and revenue per active user
Exercise: Find Your Constraint Stage
Calculate the conversion rate between each consecutive AARRR stage. The single steepest relative drop is your constraint and the focus for the rest of this workbook.
- Write the conversion rate from Acquisition to Activation, Activation to Retention, and so on down the funnel.
- Circle the stage transition with the largest percentage drop-off — this is your constraint.
- In one sentence, why do you think users leak out at that stage (evidence, not a guess)?
- Confirm you are not just defaulting to acquisition because it feels like growth.
Worksheet: Choose a North Star and Input Metrics
Name the core value moment your product delivers, pick the one metric that counts it, then break it into the three to five levers your team can directly move.
- Core value moment in plain words (a ride taken, a file saved, a message sent)
- North Star metric that counts that moment
- Input metric 1 (and which AARRR stage it maps to)
- Input metric 2 (and which AARRR stage it maps to)
- Input metric 3 (and which AARRR stage it maps to)
Checklist: Vanity vs Actionable Metric Gut Check
- My North Star can go down, which means it tells me the truth rather than just rising forever.
- I am not steering by total signups, total downloads, or cumulative views (vanity metrics).
- Each input metric ties to a specific repeatable user action.
- Every input metric maps to a stage of AARRR so each experiment has a clear home.
- I have identified my single constraint stage with funnel math, not opinion.
The Experiment Engine
Stand up a high-tempo loop — a steady backlog, ICE prioritisation, falsifiable hypotheses, and honest result reading.
Worksheet: Set Up Your Weekly Growth Meeting
Design the recurring meeting that will drive your tempo. A fixed cadence is the real growth hack; commit to it before you have any wins to show.
- Day, time, and length of your weekly growth meeting
- Who owns the North Star and runs the meeting (even if it is just you wearing the hat)
- Target number of experiments to ship per week
- Where the backlog lives (Notion, Trello, a sheet) and where the learning log lives
- The fixed agenda order: review metrics, review results, pull from backlog, assign owners, log learnings
Exercise: Write Three If-Then-Because Hypotheses
Take your constraint stage and write three falsifiable hypotheses to relieve it. Each must commit to a change, a metric and direction, and an evidence-based reason that could turn out wrong.
- Hypothesis 1 — If [change], then [metric + direction], because [evidence].
- Hypothesis 2 — If [change], then [metric + direction], because [evidence].
- Hypothesis 3 — If [change], then [metric + direction], because [evidence].
- For each, state the failure case: what result would prove it wrong?
Exercise: Score Your Backlog With ICE
Score at least five test ideas on Impact, Confidence, and Ease (1-10 each) and sort by total. Anchor confidence to real evidence: a 9 needs data, a hunch caps at 4.
- List five test ideas and give each an Impact, Confidence, and Ease score from 1 to 10.
- Total or average the three scores and sort the list so the highest rises to the top.
- For your top idea, name the specific evidence behind its Confidence score.
- Name the single highest-priority experiment you will run first.
Checklist: Valid-Test Readiness and Result-Reading Check
- I set a minimum sample size and end date with a calculator BEFORE launch (no peeking).
- I am aiming for roughly 95% significance, not just a nice-looking percentage.
- The test will run at least one to two full weeks to cover a complete behavioural cycle.
- I will segment the result by device, source, and user type before declaring a winner.
- I will log a one-line insight whether the test wins, loses, or comes out flat.
Acquisition and Activation
Find a channel that fits the product and engineer the aha moment that turns a curious signup into an activated user.
Exercise: Run the Bullseye Framework
Work the three rings to find your one channel. Brainstorm broadly, test a promising few cheaply, then pick the bullseye where the economics work.
- Outer ring: jot one realistic, concrete test idea for as many of the nineteen traction channels as you can.
- Middle ring: pick the three to five most promising and define a cheap, time-boxed test for each.
- For each test, estimate the cost per acquisition you would accept for it to be worth scaling.
- Inner ring: based on results (or your best evidence), name the single channel to concentrate on.
Worksheet: CAC vs LTV by Channel
Do the unit-economics math for your top channels. A channel is only a growth channel if customers are worth more than they cost to acquire.
- Channel name
- Customer acquisition cost (CAC) for that channel
- Estimated customer lifetime value (LTV)
- LTV:CAC ratio (aim for at least 3:1) and months to recover CAC (aim within ~12)
- Verdict: double down, keep testing, or drop
Worksheet: Define Your Aha Moment
Use a retention analysis to find the action, magic number, and time window that separate retained users from churned ones — the way Facebook found 7 friends in 10 days.
- Candidate key action that predicts retention (e.g. files saved, messages sent, accounts followed)
- Magic number (the count of that action that correlates with staying)
- Time window (e.g. within the first session, first 24 hours, first 10 days)
- Current percentage of new users who reach this aha moment in the window
- One onboarding change you will test to raise that percentage
Checklist: Activation and Landing-Page Check
- My aha moment is a specific action + magic number + time window, found from data not a guess.
- Onboarding strips friction: minimal fields, no empty first screen, a clear first win.
- Paid traffic lands on a dedicated page whose headline and offer match the ad (message match).
- Each landing page has a value headline, one focused CTA, social proof, and objection handling.
- I have watched heatmaps or session recordings (e.g. Microsoft Clarity, free) on the key page.
Retention, Referral, and Growth Loops
Make growth compound — retain users to a plateau, build a measurable viral loop, and assemble a defensible growth model.
Worksheet: Plot Your Retention Curve
Build a cohort retention curve at the cadence that fits your product and read its shape. A flattening plateau is the signature of product-market fit.
- Cadence that matches real usage (daily / weekly / monthly active)
- Retention at day 1 (or period 1), day 7, day 30 — as percentages of the cohort
- Does the curve decline toward zero, or flatten into a plateau? At what percentage?
- Your current plateau level (the floor the curve settles to)
- One engagement experiment (lifecycle email, habit trigger, win-back) to raise the plateau
Exercise: Calculate Your K-Factor
Measure how viral your product actually is. K equals invitations sent per user multiplied by the conversion rate of those invitations.
- Average number of invitations or shares sent per user.
- Conversion rate of those invitations into new activated users.
- K-factor = invites per user x invite conversion rate. Is it above or below 1.0?
- Cycle time: how long does one full invite loop take, and how could you shorten it?
Worksheet: Design a Referral Incentive
Sketch a double-sided referral program prompted at a moment of delight, the way Dropbox offered storage rather than cash.
- Reward for the referrer (ideally more of the product itself)
- Reward for the invited new user (double-sided)
- The exact moment of delight at which you will prompt the share
- How close to one tap the sharing flow is (and what removes friction)
- Metrics you will track to judge it: K-factor and cycle time
Checklist: Growth-Loop and Model Assembly Check
- I can name at least one compounding loop my product could run (viral, content, paid, or product-led).
- The loop's output genuinely feeds back into its own input, rather than needing fresh top-of-funnel fuel.
- Any paid loop only runs where LTV comfortably exceeds CAC.
- My growth model connects North Star, input metrics, AARRR constraint, and at least one loop.
- I am working my single biggest constraint now, then moving to the next, not boiling the ocean.
Your Action Plan
- Choose one product, app, or offer you own to carry through the whole plan.
- Map your AARRR funnel with real numbers and calculate the conversion rate between each stage.
- Mark the single steepest drop-off as your constraint stage and focus there first.
- Pick a North Star metric tied to a real value moment, and break it into three to five input metrics.
- Stand up a fixed weekly growth meeting with a backlog and a learning log, and set a tests-per-week target.
- Write your constraint-relieving ideas as if-then-because hypotheses, then score and sort them with ICE.
- Size your first experiment with a sample-size calculator and commit to the end date before launch (no peeking).
- Run the Bullseye framework to find a channel, and confirm LTV beats CAC before doubling down.
- Define your aha moment from a retention analysis and test onboarding changes that raise activation rate.
- Plot your retention curve to find the plateau, measure your K-factor, and sketch at least one compounding growth loop, then repeat the loop on your next constraint.
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