Data, Analytics & Insights

We audit and configure tag management containers across Google Tag Manager, Adobe Launch and Tealium, and test sites against applicable data protection legislation including GDPR, CCPA and DUAA. Automated tooling built by our own data scientists identifies where tags set storage before consent, where consent platforms aren’t properly connected, and where non-essential storage sits outside consent controls entirely. Fixing those issues improves compliance and reporting accuracy in the same move.

Once the data is reliable, the questions get more interesting. Where is revenue coming from across a complex sales funnel? Which paid channels are performing, and by what measure? What’s genuinely driving organic traffic, as opposed to what appears to be?

We configure and validate analytics platforms including Google Analytics and Adobe Analytics, then build reporting layers that pull data warehouses, analytics platforms and paid media channels into a single view. Periodic reports give context over time; real-time dashboards give teams the ability to respond to what’s happening now. Both are designed around what different teams need to see, not around what’s easy to visualise.

Tighter consent controls are often assumed to mean less attribution data, and less attribution data means softer commercial decisions. It doesn’t have to. We treat consent as an engineering problem, not a binary gate. Systems collect the richest data the current consent state allows and degrade gracefully as it becomes more restricted. Consent state is monitored throughout the session, not just at page load, so a user who grants consent mid-session doesn’t go unattributed. Attribution holds up across the full range of consent states, and marketing investment stays grounded in real evidence as privacy controls tighten.

For organisations whose needs go beyond standard analytics, our data scientists and engineers build the underlying systems that make more advanced work possible. Custom data pipelines that bring together sources which don’t connect natively. Warehousing solutions that make data available quickly and at reasonable cost. Predictive models that draw on historical behaviour to forecast future outcomes. Large language model integrations that automate work currently taking hours by hand.

We turn insight into action by building audiences, scoring and routing leads, and syncing segments into CRM and ad platforms so journeys feel more relevant and conversion improves.

Most organisations can measure the journey as far as the form submission. What happened after sits in the CRM, and the two datasets don’t talk to each other - marketing gets optimised against lead volume, while revenue quietly decouples from the decisions that should be driving it. We solve this. Marketing performance becomes measurable against actual revenue, acquisition channels can be ranked by commercial value rather than lead volume, and budget decisions sit on real commercial evidence.

Once the foundations are trusted, data science answers the questions the business actually needs answered. Which customers are most likely to churn, and which are worth retaining? Which leads should sales prioritise? What content, product or offer is most likely to move a given segment forward? We build predictive models and expose their outputs through applications and APIs, so the commercial teams who need them don’t have to understand the models to use them.

We structure content for GEO and AEO, use AI-assisted analysis to speed up research and production, and introduce practical copilots that remove repetitive work across marketing and operations.

We define roles, create playbooks and deliver training so your teams can run the day-to-day with confidence, defend numbers to the board without external support, and keep commercial decisions moving when we’re not in the room.