What this solves
Three problems we hear every week.
Your attribution model is wrong.
Last-click attribution is hiding where revenue actually comes from. You are optimizing spend based on a partial picture, and you know it.
You cannot forecast with confidence.
Revenue projections are still spreadsheet-based. Risk and growth teams are working from different numbers. No one trusts the model.
Your reporting is a week old.
By the time you see the numbers, the window to act has passed. Decisions are being made on stale data or gut instinct.
What we build
Specific deliverables. Measurable outcomes.
Attribution modeling
Full-path attribution using server-side tagging and BigQuery. See exactly which channels contribute to revenue across the full customer journey, not just the last click.
Predictive analytics
Statistical models for churn prediction, demand forecasting, and customer lifetime value. Built on your data, calibrated to your business context.
Custom dashboards
Looker Studio or Power BI dashboards built around the decisions they need to support — not around the data that happens to exist.
GA4 & event tracking
Complete analytics implementation — data layer architecture, custom event design, server-side collection, and ongoing QA. Data you can trust.
How it works
From audit to operating analytics in three steps.
Analytics audit
We review your current tracking setup, identify gaps and data quality issues, and map the analytics architecture needed to answer your actual business questions.
Implementation
We build the tracking layer, data pipelines, and dashboards. Everything is documented, tested with real data, and handed over with your team trained to use it.
Iteration
Analytics is not a one-time project. We remain available for questions, refinements, and new measurement requirements as your business evolves.
“We identified €180K in misallocated ad spend in the first month.”
A mid-size Irish eCommerce brand was running campaigns across four channels with last-click attribution only. We rebuilt their analytics stack with server-side tagging and a custom BigQuery attribution model.
The result: 3.4× improvement in attribution accuracy and a 23% reduction in customer acquisition cost over six months.