Run Fast, Scale Only What Actually Holds Up
Growth marketing built on structured experimentation across acquisition, activation, and retention.
Growth marketing is structured experimentation - testing specific hypotheses against a defined North Star metric across acquisition, activation, and retention, then scaling only what a real sample size actually supports.
What is Growth Marketing?
Growth marketing is a repeatable testing cycle: form a specific hypothesis, run the smallest test that can validate or kill it, and only scale what holds up against a real sample size. Acquisition, activation, and retention get tested as connected stages, because a win in acquisition that damages activation isn't a win.
Skipping the discipline is expensive in a specific way: someone tries a tactic that worked for a different business with no clear hypothesis, and a mild uplift on a small sample gets rolled out to the whole funnel before anyone checks whether it actually holds.
It's different from ad-hoc "growth hacking," which tries tactics because they worked somewhere else, and from revenue growth strategy, which measures success in pipeline and closed revenue rather than funnel-stage metrics.
Common problems we solve
Tactics copied without a hypothesis
A tactic that worked for a different business gets tried here with no clear reason it should transfer.
Small samples treated as proof
A mild uplift on a small sample gets rolled out to the whole funnel before anyone checks if it holds.
No shared definition of "working"
Different people would give different answers about what success actually means for the growth programme.
Wins in one funnel stage hide losses in another
An acquisition win that quietly damages activation still gets reported as a win.
Failed tests get repeated
A hypothesis that already failed gets tried again later because nobody documented the result.
Everything covered in this service
Experiment Design & Prioritisation
Every idea gets a hypothesis-driven brief and an effort-versus-impact score before it enters the queue.
Full-Funnel Testing
Acquisition, activation, and retention are all tested as connected stages, not separate silos.
North Star Metric Definition
A single top-line metric the whole growth programme is judged against, with supporting inputs mapped beneath it.
Rapid Test-and-Learn Cycles
Short experiment cycles with a defined end date and agreed kill criteria before launch.
Scaling Discipline
Statistical significance and sample-size checks happen before anything scales, with phased rollout rather than a full switch.
Our optimization framework
North Star Definition
We agree the single metric the growth programme is actually accountable to before any test gets designed.
Backlog Build
Hypotheses are collected and scored by likely effort versus impact, so the queue reflects what is worth testing first.
Test Design
Each experiment gets a stated hypothesis, a success metric, and a kill criterion agreed before launch.
Rapid Testing
Tests run in short cycles across acquisition, activation, and retention, with a defined end date rather than running indefinitely.
Result Review
Results are checked against sample size and significance, not just whether the top-line number moved.
Scale or Kill
What holds up gets rolled out in phases; what doesn't gets documented and retired rather than quietly repeated.
What actually changes
| Before | After |
|---|---|
| Tactics tried because they worked elsewhere | Every test starts from a specific, stated hypothesis |
| A small-sample uplift rolled out immediately | Results checked against sample size before scaling |
| Wins reported per channel in isolation | Acquisition, activation, and retention tested as connected stages |
| Failed tests quietly forgotten | Every result documented, win or loss |
| No shared metric for "working" | One North Star metric the whole programme is judged against |
What we report on
Experiment velocity
How many hypotheses get tested per cycle, tracked against the prioritised backlog.
Win rate against sample size
The share of tests that clear statistical significance before being scaled, not just direction of movement.
North Star metric movement
Change in the agreed top-line metric, tied to the specific experiments that moved it.
Funnel-stage impact
Whether a win in one stage - acquisition, activation, retention - holds up or costs ground elsewhere.
Tools & platforms
Industries we optimize for
Built for teams like yours
Why choose EASI7
We fix tracking before we touch results
Every engagement starts with the same audit we'd run on our own accounts, so the numbers you're optimizing against are actually true.
One accountable team, not siloed vendors
The same team that does this also owns the rest of your stack - no handoff, no blame-shifting between vendors.
Built for how AI search actually works
Everything we build is structured to be extractable by AI answer engines, not just ranked in a list of blue links.
Reporting tied to your own dashboard
Every number we report ties back to GA4/GTM events you can see directly - not a screenshot from a tool you can't independently verify.
Related Growth Strategy services
Design The Whole Funnel, Not Just One Stage
We map the full path from awareness to retention as one connected system, so a fix upstream never breaks something downstream.
Growth StrategyGrowth that doesn't outpace your ability to serve it
Customer acquisition strategy balanced against retention capacity and unit economics.
Measure Growth in Revenue, Not Just Traffic and Leads
Revenue growth strategy connecting marketing activity directly to pipeline and revenue outcomes.
How to engage us for this
Project-based
A defined outcome with a start and end date - an audit, a migration, a campaign build, a tracking overhaul. Fixed scope, fixed price, agreed upfront.
Ongoing retainer
Continuous management and optimization once the initial build is live - campaigns, SEO, reporting, and iteration run every month under one accountable team.
Advisory
Strategy and oversight without full delivery - we review what's already running, unblock decisions, and point an in-house or existing team in the right direction.
Common questions
Faster than a full rebrand or a content programme, but not overnight - a proper test needs enough volume to reach a real sample size, which can take anywhere from a couple of weeks to a couple of months depending on your traffic. We'd rather report a slower, trustworthy result than a fast one that doesn't hold up.
No - growth rate depends on market conditions, your product, and your existing baseline, none of which a testing process controls outright. What we can guarantee is a disciplined process that finds real wins and avoids scaling false ones, which compounds over time even without a guaranteed number attached.
They get documented, not discarded. A failed hypothesis is still information - it rules something out and often points toward what to test next, so retesting the same dead end gets avoided.
You need enough to reach statistical confidence in a reasonable timeframe. Very low-traffic sites can still run growth marketing, but tests take longer to reach a trustworthy read, so we usually prioritise fewer, higher-impact tests rather than a high volume of small ones.
Running ads is a channel; growth marketing is the discipline that decides which channel, message, and funnel stage is actually worth testing next, and whether a result is real before more budget goes toward it.
The experiment backlog is scored jointly, weighing likely impact against effort, but the North Star metric set at the start is what keeps the priority list honest rather than driven by whichever idea is most exciting that week.
Testing tactics with no way to tell if they worked?
We'll help you define the metric that actually matters and build a testing process that scales only what holds up.
Ready to get started?
We usually reply within 24 hours.
Growth Marketing, in detail
Scope, area by area
| Area | What we deliver |
|---|---|
| Experiment Backlog | A prioritised, scored list of hypotheses ready to test |
| North Star Metric | A defined top-line metric with supporting input metrics mapped underneath it |
| Test Reports | A documented result for every experiment, including the ones that didn't work |
| Scaling Plan | A phased rollout plan for anything that clears the bar to scale |
How this compares
| Structured Growth Marketing | "Growth Hacking" Tactics |
|---|---|
| Every test starts with a hypothesis and success metric | Tactics get tried because they worked somewhere else |
| Results are checked against sample size before scaling | A small uplift gets rolled out immediately |
| Learnings are documented whether a test wins or loses | Failed tests are forgotten and get tried again later |
Both approaches involve testing - the difference is whether a result is trusted before it's acted on.