02 The problem — in their words
If you've said any of these out loud,
the answer isn't another consultant.
Four lines we hear on almost every first call. Different companies, same missing piece.
01
"We're spending on growth but we can't actually tell what's working."
Series B SaaSHead of Growth
02
"Our activation numbers are bad and nobody can give me a straight answer why."
Series A SaaSCEO
03
"We have data in eight tools and nobody's connecting it to decisions."
Bootstrapped SaaSFounder
04
"We had the data and the team but no system connecting them. Every sprint we'd say 'we should run a proper experiment' — and never did."
Scale-upHead of Product
the pattern
The pattern is the same every time: the data exists, the team is capable, but the
function connecting them doesn't. That's what we install.
03 How it works — 6 weeks to install your growth function
Six weeks to install the function.
Then it runs — with or without us.
We need roughly 3 hours per week from a PM or Growth lead, plus stakeholder access in
weeks one and four. Everything else is on us.
01
Stakeholder interviews, tooling audit, and a structured read of every funnel you have. Goal: understand what you already know — and map exactly where the blind spots are.
02
Rebuild the activation-to-revenue funnel from raw events. Quantify every drop-off in revenue, not just percentages. End of week: one source of truth for where growth is leaking, sized by revenue impact per step.
03
Galangal Flow gets configured to your stack — dashboard, AI skills, connectors, and automation calibrated to your metrics. Your team runs their first full diagnostic cycle before the week ends. The function is live early.
04
Share findings with the stakeholders and define the highest-leverage problems. Prioritize and surface any internal disagreements now — before the backlog is already built.
05
Translate the agreed priorities into a scored experiment backlog. This is where the growth function starts producing output — structured briefs and AI-assisted read-outs your team acts on, running through Flow.
06
The growth function is running. This week we document it, stress-test it, and make sure the team owns it — not just uses it. Final session: you run a full cycle without us.
One person runs Galangal Flow day-to-day after week six — it's built to plug into your existing workflows, not to sit beside them.
01
Growth diagnostic
A written read-out naming the three to five leaks worth fixing first — sized in revenue, ranked by effort. The first output of your growth function.
02
Experiment backlog
An RICE-scored backlog. Each one is structured for your flagging tool — hypothesis, metric, sample size, definition of done. Nothing is theoretical.
03
Galangal Flow
Your growth function, installed. Dashboard, AI skills, connectors, and automated workflow — calibrated to your stack, owned by your team, runs without a specialist.
04
Operating manual
How to run the next cycle, how to use the AI layer, how to read a result. The growth function keeps running when the team changes.
where AI fits
The growth function runs on an AI layer — configured skills that surface anomalies, draft experiment briefs, and read results. Your team decides. The function processes. Experiment deployment happens in your existing tools. Galangal Flow is the thinking layer above them.
04 Galangal Flow — the system you keep
One person running a growth function.
That's what Galangal Flow is built for.
Galangal Flow is the operating layer of your growth function. It connects your data,
automates the routine analysis, and gives your team a structured, repeatable way to find
what's breaking, propose what to test, and report on what moved — without needing a
specialist to make it work.
Live dashboard
Your funnel, instrumented against the metrics that move the P&L. Owned by your team.
AI skills & agents
The intelligence layer — surfaces anomalies, drafts experiment briefs, reads results. Your team decides; the function does the processing.
Connectors
Pre-built integrations that pull data from your existing stack into a single working view.
Automated workflow
Diagnostic → brief → read-out, automated. One person, full growth function, no specialist required.
a normal week
Monday morning, the system surfaces the week's top anomaly. Your PM reviews it, picks one thread, and has a drafted experiment brief by midday — without touching any database.
Experiment deployment lives in your existing tools — Amplitude, GA4, PostHog, your flagging system. Galangal Flow covers the thinking layer: structured briefs, AI-assisted analysis, and read-outs your team can act on. Design and development of variants are out of scope. The engagement adapts to where you are.
05 Proof — anonymised, specific, honest
One honest, specific metric
beats three vague ones.
B2B SaaS scale-upActivation
+18%trial → paid
Redesigned activation flow after surfacing a €35k/month drop-off.
Identified a single onboarding step where 40% of qualifying trials silently abandoned. Rewrote the flow, instrumented it properly, and shipped in week four.
Series B · earlier engagementRetention
+22%90-day retention
Led the experimentation program that grew retention over two quarters.
Built the system from scratch — hypothesis intake, prioritisation, instrumentation, post-mortems. Fourteen experiments shipped, four hits, none obvious. The system it produced is what Galangal Flow now installs in six weeks.
Scale-up · ProcessVelocity
3w→6dcycle time
Cut experiment cycle time from three weeks to six days.
Rewrote the experiment brief, automated the read-out, and put the analyst on the team instead of in a queue. The compounding effect is what matters here.
Companies anonymised by request. Detailed references available on a call.
06 Why us
Most analytics consultants tell you what's broken.
Most strategists tell you what to build.
We install the function that does both — continuously, without a consultant in the room.