Overview
Most analytics setups were configured once, extended under pressure, and never audited. The data looks complete and is quietly wrong: duplicate events, internal traffic counted, conversions firing on page load. Everything built on top of it inherits the fault.
The work here is unglamorous and decisive. Design events around the decisions you actually make, validate the numbers against something you know is true, recover what browser restrictions have taken away, and then analyse rather than merely report.
Who this is for
- Companies whose analytics disagrees with their own sales figures
- Advertisers whose reported conversions fell without sales falling
- Teams with several dashboards and no number anyone trusts
Everything we cover in Analytics & Data
Each one links through to scope, typical deliverables and how the work runs.
Digital Analytics
Analytics implemented so the numbers can be trusted: events designed deliberately, consent handled correctly, and reporting that answers a question someone actually asked.
Performance Tracking
Knowing what each channel and campaign actually produced: consistent tagging, conversions defined once, and reporting that survives someone changing a URL.
Attribution Modelling
Working out what each touchpoint contributed, choosing a model that fits your sales cycle, and being clear about what attribution can and cannot tell you.
Privacy-Compliant Tracking
Measurement that works within consent rules rather than around them: consent handled properly, data minimised, and modelling used for what consent removes.
Server-Side Tracking
Moving measurement off the browser: a server-side container, platform conversion APIs, and control over what data leaves your infrastructure.
Data Visualisation
Dashboards and reports people actually read: built around a decision, honest about uncertainty, and readable at a glance without a legend of caveats.
CRM & CDP Integration
Joining marketing data to what happened afterwards: identity resolved, records synchronised both ways, and closed-won data fed back where it changes decisions.
Marketing Performance Analysis
Reading the data rather than collecting it: finding what actually changed, what caused it, and what to do differently next quarter.
Common questions about Analytics & Data
The things people ask before they get in touch. If yours is not here, ask us directly.
Why does our analytics not match our sales figures?
Usually a combination of consent rejection, ad blockers, cross-device journeys and attribution windows, plus implementation faults. A gap is normal; a large or unstable one indicates something fixable, and we quantify each cause rather than accepting it.
Can attribution tell us what caused a sale?
No. Attribution allocates credit among touchpoints you can observe, which is useful for steering. Causation needs a holdout test, and arguing about attribution models is usually a substitute for running one.
Do we need a customer data platform?
Less often than they are sold. For most mid-sized companies a well-integrated CRM plus a warehouse does the same job for considerably less.
Multi-market delivery
Teams that have shipped across regions, languages and regulatory regimes.
Built for review
Security, accessibility and privacy handled during the build, not bolted on at audit.
Measured, not assumed
Every engagement agrees its success metric before work starts.