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Analytics & Reporting

GA4 Setup & Tracking

GA4 and server-side tagging configured to a documented measurement plan — so the numbers mean the same thing in six months and in every report that quotes them.

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Documented measurement plan behind every property
1Documented measurement plan behind every property
What conversions are defined as
RevenueWhat conversions are defined as
Median signal recovered with server-side tagging
+22%Median signal recovered with server-side tagging

The problem

Most GA4 properties were migrated automatically and never configured. Events are auto-collected with meaningless names, "conversions" include newsletter signups next to purchases, and nobody trusts the numbers enough to make a decision with them.

How we do it

What the work actually involves

/01

A measurement plan before any tags

What business questions the data must answer, which events answer them, and how each is named. Tagging without this produces a property nobody can interpret two quarters later.

/02

Conversions that mean money

Qualified leads and revenue, not form views. Every downstream decision — including what the ad platforms optimise toward — inherits whatever you define here.

/03

Server-side tagging where it earns it

Recovers signal lost to blockers and browser restrictions, and gives you control over what leaves the page. It adds complexity, so we recommend it when the recovered data justifies the maintenance.

/04

Consent implemented, not simulated

Consent Mode wired so tags genuinely respect the choice. A banner that stores a preference and changes nothing is a compliance risk with a false sense of safety attached.

Included

What you actually receive

  • Measurement plan tied to business questions
  • GA4 property configuration and event taxonomy
  • Google Tag Manager container build
  • Conversion definitions at qualified-lead or revenue level
  • Server-side tagging where justified
  • Consent Mode implementation
  • Cross-domain and offline conversion import where needed
  • Documentation and team training

Tools we use

  • GA4
  • Google Tag Manager
  • BigQuery
  • Looker Studio
  • CallRail
Common failures

Where this usually goes wrong

The three we are called in to fix most often. If any of these describe your current setup, that is the first thing we would change.

  • Migrating automatically and never configuring

    Auto-collected events with meaningless names, and "conversions" that include newsletter signups next to purchases. Nobody trusts the numbers enough to decide anything with them.

  • Counting form views as conversions

    Every downstream decision inherits this definition, including what the ad platforms optimise toward. Getting it wrong is not a reporting problem, it is a bidding problem.

  • A consent banner that changes nothing

    Storing a preference and firing every tag regardless is a compliance risk with a false sense of safety attached. Consent Mode has to be wired to actual tag behaviour.

Measurement

How you will know it is working

Agreed before we start, so progress is visible in the months before it shows up in revenue.

Conversions matching the CRM
Analytics and reality within a tolerance you agree. If they never reconcile, one of them is not being used.
Month 1
Events following the plan
Share of tracked events with documented names and parameters. It is what makes the data readable in a year.
At delivery
Signal recovered server-side
Where server-side tagging is used, the conversions recovered versus the browser pixel alone.
Weeks 2–4
Questions

Any question in your mind?

The questions we get asked most, answered without the sales gloss. If yours is not here, ask us directly — you will get a straight answer either way.

Still have questions?

Book 30 minutes with a strategist. No deck, no pitch — just answers about your situation.

Book a call

They always will. Ad platforms count conversions on their own attribution windows and include view-through; GA4 uses last non-direct click. Neither is wrong, they answer different questions. Pick one as the source of truth for decisions and use the other for in-platform optimisation.

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