A product with users, no growth
There's a base of active customers or users, but the business's key number has been flat for months.
GROWTH MARKETING / TEST, MEASURE, SCALE
Growth marketing in Malta. Test, measure,
scale what wins.
We test growth hypotheses in short cycles, measure their effect on one concrete business metric, and scale what works — cutting what doesn't — instead of betting everything on a single channel.
FROM HYPOTHESIS TO RESULTIllustrated process
01 / 04
We choose what to test.
We start from a concrete business metric — sign-up, purchase, activation — and choose which lever to test first.
02 / 04
We launch it small.
We set up the minimum version of the experiment, with just enough traffic for a reliable reading.
03 / 04
The data decides.
We analyse whether the experiment moved the business metric, or whether the change wasn't significant.
04 / 04
What wins, grows.
What works gets scaled to more traffic or budget; what doesn't gets closed and isn't tested the same way again.
- Short test cycles
- Measured on your metric
- What loses gets cut
- What wins gets scaled
WHAT WE DELIVER
Experiments with
a clear verdict.
Every experiment arrives with its hypothesis, the result against your business metric, and a decision: scale it, adjust it or close it.
- 01Growth hypotheses prioritised by expected impact
- 02Experiments in short cycles, with controlled traffic
- 03Results read against your business metric, not vanity numbers
- 04A decision to scale, adjust or close each experiment
PHX / GROWTH LOOP Measured
Your test cycle
What happens to each experiment
- Hypothesis
- Prioritised by business impact
- Cycle
- Short, with controlled traffic
- Metric
- The one that defines your business
- Verdict
- Scale, adjust or close
01
02
03
04
Does your case fit? We will tell you what can be done, at no cost and no commitment.
I want my first experimentWHEN IT MAKES SENSE
When acquisition
is no longer the problem.
Lots of ideas, zero priority
The team has ten ideas to improve conversion and activation, and no way to know which one to test first.
A SaaS or subscription losing users
New customers come in but leave at almost the same rate, and no one has measured exactly where they drop off.
Budget that doesn't perform like it used to
Acquisition costs more than before, and you need to get more out of every visit or customer that already comes in.
WHAT CHANGES IN PRACTICE
Growth marketing is about experimenting against a business metric and scaling what works, not managing one more channel.
A growth experiment starts from one concrete business metric — sign-up, activation, repeat purchase — and tests a hypothesis about what would move it, with just enough traffic for a reliable reading in a short cycle. The result is measured against that metric, not against clicks or reach, and always ends in a decision: scale the change, adjust it or close it. Without that discipline of measuring and deciding, what you have are just loose ideas.
At Phoenix Hub Solutions, we prioritise hypotheses by their expected impact on your business metric, set up each experiment in a short cycle, and present the result with its verdict: scale, adjust or close. We don't keep an experiment running because it "sounds good," nor do we multiply simultaneous tests beyond our capacity to measure them all. What we don't do is promise how many experiments will win before running them: the data decides that.
PeopleWhoever runs the business needs to see which experiment moved the number that matters to them, not a report of impressions and reach with no connection to sales.
SEO and GEOWe explain what's being tested and against which metric, in sentences quotable by people or an AI assistant. It doesn't guarantee what percentage of experiments will win.
QUESTIONS BEFORE YOU START
The important part,
explained well.
Before you start experimenting, it's worth knowing what gets measured, how long each cycle takes, and what happens if an experiment goes wrong.
What exactly is a growth marketing experiment?
It's a concrete hypothesis about what would move one of your business metrics — for example, the percentage of sign-ups that convert into customers — put to the test with real traffic, with a result measured against that metric, never against clicks or reach. It doesn't include the ongoing management of a channel as if it were an ad campaign: here, every piece being tested has a start date, a reading date and a decision at the end.
What if none of the experiments work?
It's a real possibility and part of the method: not every hypothesis wins, and one that doesn't is still information, because it rules out a path without spending on scaling it first. What we're after isn't every single experiment winning, but the whole cycle — several hypotheses tested in parallel or in sequence — moving the business metric over the quarter. If an entire cycle moves nothing, we review the starting hypothesis before testing further minor variations.
How long before you see a result?
Each experiment cycle lasts between 2 and 4 weeks, depending on available traffic: with low traffic, it takes longer for the result to be statistically reliable. The first cycles tend to be slower because the business metric needs to be properly instrumented before measuring anything; from the second or third cycle onward, the pace picks up. That minimum timeline doesn't get shortened just to get an answer sooner.
What happens if an experiment goes wrong and affects real sales?
Experiments launch with the minimum traffic needed to read a result, never with a hundred percent of the business's traffic, precisely to limit the cost of a hypothesis that doesn't work out. If an experiment shows a clear drop in the metric that matters, it gets stopped before completing the planned cycle. We don't risk the business's main traffic or revenue to validate an idea.
What data do you need to measure the experiments?
Access to the product or website analytics where the business metric is defined — sign-ups, purchases, activations — and, if it exists, to the CRM to follow the result beyond the first click. We don't need your users' personal data or password access: we work with aggregated metrics and anonymous events whenever possible. Any personal data that is genuinely needed is handled in line with GDPR, within the EU.
Do I need to already have a metric defined before starting?
It's not essential, but it does help to know which number genuinely matters to you: sales, activations, retention. If it isn't defined yet, the first block of work is exactly that: agreeing what the business metric is and how it's measured today, before proposing any experiment. Without that prior agreement, the result of any experiment can be read in different ways.
NEXT STEP
Tell us which number matters to you.
We start testing.
We define the business metric with you and the first hypothesis worth testing this very week.
I want my first experiment No guarantee that the first experiment will win.