Reporting beyond the GA4 interface
Bright Analytics turns your GA4 BigQuery export into a reporting model built around your business. Define your own KPIs, inspect the events behind the numbers and connect website activity to customer outcomes where the data supports it.
For marketing and analytics teams who need more than standard website reports.
Your questions go further than the dashboard
You need to explain a change in revenue, understand the effect of consent choices or show which leads became customers. A standard GA4 report rarely answers all of that on its own.
The totals differ, but the reason is unclear
GA4 reports, explorations and exported data can use different processing and definitions. Sampling, reporting identity and modelling can all affect comparisons. Your team needs to explain the difference before acting on it.
Consent changes what you can measure
Cookie choices affect the events and identifiers available. You need to know which activity is observed, which figures are modelled and which questions the collected data cannot answer.
Website activity stops short of customer outcomes
A form submission is not a qualified lead, and a purchase event does not tell you whether a customer returned. Those answers require web activity to be connected to CRM and order data.
How do we solve it?
Our marketing analytics platform brings GA4 event data, business definitions and customer outcomes together. We build the reporting model around the questions your team needs to answer, with explicit rules for consent signals, identity and the limits of the data.
Collect data
Get your GA4 event export flowing into BigQuery
We work with your team to configure the export and connect it to Bright Analytics. We check event coverage, consent signals and the fields available for reporting, so the model starts with a clear understanding of what has actually been collected.
Model data
Define your metrics and consent-aware reporting
We build transparent KPI definitions, page groupings and filtering rules from the exported events. Where cookieless events are available, we analyse the supported activity separately, without treating event counts as known users or inventing missing customer journeys.
Connect web activity to customer and order records
Where suitable first-party identifiers and permissions exist, we join events to CRM, order or loyalty data. We define the matching rules and make unmatched records visible, creating a basis for lead quality, repeat purchase and customer cohort reporting.
Report and analyse
Give your teams reporting they can investigate
We build dashboards around your business questions, with clear definitions and the ability to investigate the underlying detail. Your team can compare periods, explore customer outcomes and understand measurement gaps without rebuilding an exploration for every question.
What changes for your team
Numbers you can explain
Your KPIs, exclusions and reporting rules are defined in one model. Analysts can trace a result back to the collected events and explain why it differs from a GA4 report.
A clearer view of consent-related activity
Where collected, cookieless events can support aggregate analysis of pages, purchases and other activity. You can inspect consent signals and changes in measurement coverage without presenting that activity as a complete record of individual visitors.
A foundation for customer-level analytics
Connect identifiable web activity to qualified leads, orders and repeat purchases. With suitable customer identifiers and history, analyse retention and customer value across visits and devices, while keeping unmatched activity separate.
Questions
What if we do not have BigQuery set up?
We work with your administrators to configure the GA4 export and the access needed for reporting. We agree the export configuration, storage and query requirements before building the model.
Will BigQuery contain our historical GA4 data?
The standard GA4 BigQuery export does not backfill the period before the link was established. If you already have exported data, we can assess that history. Otherwise, the event-level dataset starts building once the export is active.
Can we analyse activity from people who decline analytics cookies?
Where your implementation collects cookieless events and exports them, we can assess the available event activity and consent signals. That may support aggregate reporting on pages, events and recorded purchases. It does not guarantee a complete user, session or cross-device history, and cannot recover events that were never collected.
Does GA4 leave all of this activity out of its reports?
No. Eligible properties can include behavioural modelling in GA4 reporting. BigQuery provides the collected events rather than that modelled behavioural dataset. We make this distinction explicit instead of assuming the export and the interface should show identical totals.
Can you join GA4 data to our CRM and link devices?
Where suitable identifiers exist, yes. For example, a consistently implemented first-party User-ID can link signed-in activity across devices, and an appropriate lead or order identifier can support a join to business records. We assess tagging, permissions and match coverage; anonymous activity does not automatically become identifiable.
Is raw GA4 data complete and automatically clean?
No. The export avoids reporting-surface sampling, but collection gaps, export limits, duplicate events and tagging errors still matter. We check the data and define appropriate quality and filtering rules before using it for business reporting.
Can we use the resulting model in other tools?
Yes. Our Reporting API and MCP connections let teams work with the model through their BI tools and AI assistants, using the same agreed definitions as the dashboards.
Your GA4 data, connected to the rest of your business
Managed data pipelines, a fully customised data model and reporting built around your business. API and MCP connections let your teams use the same model in their BI tools and AI assistants.