Every platform reports accurately.
Ad platforms, analytics, CRM, each telling a slightly different story. We consolidate them into one reporting layer, reconciled, documented, and updated before anyone asks for it.
Most marketing teams don't have a reporting problem. They have a consolidation problem.
Every platform has its own dashboard. Each one is accurate on its own terms. None of them reconcile against the others, and none match the CRM. So someone on the team builds a spreadsheet that lines them up, flattens the discrepancies, and produces a version leadership can read.
That spreadsheet is fragile. It misses the cross-market view entirely. When the person goes on holiday, reporting slips. When the business asks a question the spreadsheet wasn't built for, the answer takes three days.
We replace the spreadsheet with infrastructure.
Marketing data pipelines and dashboards, reconciled into one view.
BigQuery data models, built around business questions.
In a warehouse like BigQuery, all your sources are consolidated into tables. We structure each table around one question: spend by campaign, spend by country, website behaviour, landing page health. The schema is designed backward from the question, not forward from whatever the platform happens to export. Readers know where to look. The dashboard doesn't collapse under the weight of every metric that was technically available.
Data joins: what connects, what doesn't.
Some data combines cleanly. Ad platforms to each other, campaigns to countries. Some doesn't. Website analytics rarely joins to ad campaigns with more than a fraction of sessions, and forcing it destroys the rest of the data. Where it should reconcile, we reconcile. Where it shouldn't, we keep it separate in the same dashboard and let the reader filter. The reporting doesn't pretend everything lines up when it doesn't.
Standardised metrics, one definition on every row.
Google counts interactions, Meta counts clicks, LinkedIn won't split conversions by country. Every platform ships its own definitions, and raw comparisons quietly misallocate budget. We standardise fields, metrics, and currencies before the data lands, so a metric means the same thing on every row. What can't be compared is named, not blended.
CRM integration, tied to revenue.
Where a CRM is in the stack, we connect it properly. Lead, opportunity, closed deal, matched back to the campaign that generated it. So marketing is judged on real revenue, not just leads. You see which campaigns opened pipeline and which closed deals.
Each platform tells the truth.
Nobody trusts the same one.
Once the numbers reconcile, the arguments stop.
Start where the numbers disagree.
Typically three weeks, scoped to your stack. The deliverable is yours whether we continue or not.
- 01Where each source lives and what it reports
- 02Where the numbers disagree across platforms and CRM
- 03What reconciles, what doesn't, and why
- 04The cross-market view that's currently missing
- 05Prioritised build to a single reporting layer