Digital Marketing

Analytics & Attribution

Most analytics setups produce dashboards and arguments. We build them as decision infrastructure: clean data, defensible models and one version of the truth.

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The problem

Marketing decisions are routinely made on broken data

iOS changes, server-side tagging, consent mode, AI-driven attribution. The technical complexity is real, and most analytics setups have quietly fallen behind it.

GA4 set up the wrong way

Default events, missing parameters and incomplete revenue tracking distort every report.

No server-side layer

Browser tracking alone leaves significant traffic and conversions invisible.

Attribution by feel

Last-click metrics in the platforms, no defensible model behind them.

CRM data sitting outside the picture

The numbers that matter most, qualified leads, customers and revenue, are not in the marketing reports.

How we build the layer

Clean tracking, defensible attribution, decision-ready reporting

A single decision layer across paid, organic, content and CRM.

GA4 and server-side rebuild

Tag manager, GA4 and server-side tagging implemented properly, with consent handled correctly.

Attribution modelling

A defensible mix of platform, MMM and incrementality, sized to your business.

CRM and revenue integration

Qualified leads, customers and revenue stitched back into the marketing view.

Reporting humans actually read

A small number of dashboards, owned by named people, designed to drive decisions.

AI-assisted insight

Pattern detection, anomaly alerts and narrative summaries layered on top of clean data.

Audit trail

Every change to the tagging or attribution layer documented. No mystery breakages.

Outcomes

What changes once analytics actually works

Faster

shifts in spend

Confident budget decisions

Reliable data shortens the loop between insight and reallocation.

Visible

cost per customer, by channel

Real ROI on every channel

No more relying on platform self-reporting.

Better

inputs into Smart Bidding and Advantage+

Cleaner data to feed AI

When the platform sees the right signal, performance compounds.

Owned

in your accounts, not theirs

Lower agency and tool risk

Tracking and reporting belong to you, not the agency.

How we work

A pragmatic, opinionated rebuild

No 200-page audits. No frameworks for their own sake.

Audit the current stack

Week 1

Tag manager, GA4, ad platform pixels, server-side endpoint, CRM and BI tooling, reviewed as one system.

Rebuild the data layer

Weeks 2-3

Events, parameters, consent and server-side endpoint specified once and implemented properly.

Wire in CRM and revenue

Week 3

Qualified leads, customers and revenue connected back into the marketing view.

Design the reporting

Week 4

A small number of decision-ready dashboards, owned by named people on the team.

Iterate and govern

Ongoing

Quarterly reviews, change logs and AI-assisted anomaly detection keep the system clean.

Frequently asked questions

Do you replace our existing analytics tools?

Usually no. We rebuild the data layer underneath your existing tools. New platforms are introduced only where a measurable gap exists.

Which attribution model do you use?

A mix sized to the business. Platform attribution for tactical decisions, marketing mix modelling for budget allocation, incrementality testing where it earns its keep.

How does this work with privacy and consent?

Consent mode, server-side tagging and consent-aware events are part of the build. The layer is designed to remain compliant as regulation evolves.

How quickly do we see useful reports?

First reliable dashboards typically land in week four. Full attribution model is normally settled within the first quarter.

Next step

Build the decision layer your growth deserves

Most growth issues are visible in the data long before they appear in the numbers, but only if the analytics layer is sound. Book a consultation and we will assess where yours stands.

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