Google Analytics 4 - implemented properly.

GA4 is only as good as the implementation behind it. A misconfigured GA4 property produces data that looks plausible but cannot be trusted - and decisions made on bad data are worse than decisions made on no data at all.

Google Analytics 4 Event Taxonomy BigQuery Attribution Custom Dimensions

Why It Matters

Signs your GA4 implementation needs attention.

These are the most common GA4 problems we find during audits. Most of them are invisible until someone looks closely at the data.

Duplicate events inflating your data

GA4 firing twice on the same interaction - from both GTM and the gtag snippet, or from misconfigured triggers - produces event counts that look high but are meaningless. Decisions made on inflated data are unreliable.

✓ Full audit identifies and eliminates all duplicate firing

Generic event names with no business context

Using GA4 recommended events without custom parameters means your reports show that something happened - but not what it means for the business. A "purchase" event with no product, revenue, or category data is almost useless.

✓ Custom event taxonomy aligned to your business metrics

Conversions not aligned to business goals

Marking every button click as a conversion dilutes conversion data and makes campaign attribution meaningless. Conversions should represent actual business outcomes - leads, purchases, sign-ups - not page views or scroll depth.

✓ Conversion events mapped to real business outcomes

BigQuery export not set up or poorly structured

Without BigQuery export, you are limited to GA4's sampled, aggregated reports. With a poorly structured export, your BI team cannot use the data reliably. Raw event-level data in BigQuery is the foundation of enterprise analytics.

✓ BigQuery export configured and schema documented

What We Do

Everything we cover in a GA4 implementation.

A proper GA4 implementation starts with understanding what business questions the data needs to answer - then designing the event taxonomy, custom dimensions, and property configuration to answer them. We do not apply generic templates; every GA4 setup we build is designed around the specific business it serves.

GA4 property setup and configuration from scratch or audit and rebuild of existing property
Custom event taxonomy designed around your business goals and conversion journeys
Custom dimensions and metrics for business-specific data points
Conversion event configuration mapped to real business outcomes
Cross-domain tracking for businesses with multiple properties or subdomains
User-ID implementation for authenticated user tracking across devices
BigQuery export setup with documented schema
Funnel and path exploration configuration for key user journeys
Full QA validation with GA4 DebugView and Chrome DevTools

What You Get

Fully configured GA4 property
Custom event taxonomy documentation
Custom dimensions and conversion setup
BigQuery export configured
QA report with full event validation
Handover documentation for your team
30-day post-launch support

Our Process

How we approach every GA4 engagement.

Requirements & Taxonomy Design

We start by understanding what business questions your data needs to answer - then design the event taxonomy and custom dimensions to answer them before writing any configuration.

Property Configuration

GA4 property set up with correct data streams, custom dimensions, conversion events, and BigQuery linkage - all aligned to the taxonomy agreed in phase one.

QA & Validation

Every event validated in GA4 DebugView and Chrome DevTools. Duplicate firing checked. Conversion events verified. Full QA report produced before handover.

FAQ

Common questions about GA4.

We already have GA4 set up - do we need a rebuild?

Not necessarily. We start with an audit to understand what is already in place. In many cases the existing property can be improved rather than rebuilt - cleaning up duplicate events, adding missing custom dimensions, fixing conversion configuration. We will tell you honestly what needs to change and what does not.

Do we need BigQuery export?

If you have a BI team or use data warehouse tools like Snowflake, yes - BigQuery export gives you raw, unsampled, event-level data that GA4's interface cannot provide. Even without a BI team, BigQuery export is worth setting up as a data safety net. GA4 only retains data for 14 months by default; BigQuery keeps it indefinitely.

How do you handle cross-domain tracking in GA4?

Cross-domain tracking in GA4 requires configuring the correct domains in the data stream settings and ensuring the linker parameter passes correctly between domains. For SPA platforms where the subdomain changes during a user journey - like onboarding or consultation flows - this requires additional configuration to maintain session continuity and prevent artificial session fragmentation.

What is the difference between events and conversions in GA4?

In GA4, every interaction is an event - page views, clicks, form submissions. Conversions are simply events that you mark as important business outcomes. The key is choosing the right events to mark as conversions - not every interaction, but the ones that genuinely represent business value. This directly affects how Google Ads optimises your campaigns.

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