Reporting only changes decisions when people believe it. We fix the measurement layer first — tracking, identity and definitions — and then build the dashboards.
Marketing analytics fails quietly. The dashboards still load, the reports still send, but the ad platforms claim more conversions than the CRM has records, GA4 disagrees with both, and finance uses a fourth number. Once the numbers are disputed, every budget conversation becomes a negotiation about methodology instead of a decision about spend. Fixing it means rebuilding measurement on a foundation that can be reconciled and tested.
We rebuild measurement from collection to decision: a tracking plan you can audit, warehouse-backed models with tests, attribution matched to your actual sales cycle, and reporting that reconciles with finance.
Reliable, consent-aware collection across web, product, CRM, billing and advertising, landing in one place that can be queried.
Dashboards built around the decisions they support, with a defined owner and a defined action for each metric shown.
An attribution approach chosen to fit your sales cycle and channel mix, and validated with tests rather than asserted.
Analysis that goes past channel totals into which audiences, creatives and offers actually move the business.
Recurring reporting produced by pipelines instead of people, delivered where the team already works.
Models applied where they extend analyst capacity: spotting anomalies, explaining shifts and forecasting.
Dashboards built on a broken tracking layer create arguments, not decisions. We start with a documented tracking plan and a single definition of each metric.
We combine platform-reported data, a warehouse-based multi-touch model, and periodic holdout or geo tests, and present the range rather than a single false-precision number.
Typical situations where teams bring us in for this work.
One revenue definition, modelled in the warehouse, that both teams sign off on and report from.
Geo holdout tests that show which channels drive incremental revenue and which are claiming credit for it.
Server-side collection, consent handling and modelling that keeps measurement viable as identifiers disappear.
The weekly pack assembled and delivered automatically, with narrative commentary generated from the data.
Product usage joined to acquisition and billing data so activation and expansion can be measured by source.
The same delivery method every engagement follows — see our full process for more detail.
We test what is currently collected, where it breaks and how far the numbers diverge across systems.
A documented event taxonomy and data contract agreed with engineering before implementation begins.
Server-side and client-side collection deployed with consent handling and validation.
Transformations with tests and documentation, so every metric has traceable, reviewable logic.
Dashboards built against real decisions, plus incrementality testing on the channels that carry the budget.
Ownership, monitoring and change control so the measurement layer stays trustworthy as the stack changes.
We are vendor-neutral. These are the platforms we work with most often on this service.
Ad platform numbers, GA4 and the finance report disagreed by a wide margin each month, so channel budget decisions were being argued rather than decided.
Read the case study SaaSInbound demo requests were triaged by hand in a shared inbox. Follow-up took over a day on average and sales had no consistent definition of a qualified lead.
Read the case studyGA4, server-side GTM, Segment, RudderStack, BigQuery, Snowflake, dbt, Looker Studio, Metabase and Power BI, among others.
We implement consent-mode-aware collection and work with your legal counsel on retention and lawful basis; we do not provide legal advice ourselves.
Performance, SEO, security and AI-readiness scoring in one run.
Challenge, architecture, stack and measured results from real engagements.
Articles on AI marketing, automation, analytics and AI search visibility.
Fixed-scope automation, AI agent and analytics engagements.
Stack strategy, vendor selection and architecture
ServiceAutomated lifecycle, lead flow and CRM operations
ServicePerformance campaigns with clean measurement
SolutionA warehouse-backed measurement layer
SolutionClean data, automated handoffs, trustworthy pipeline
Start with a measurement audit: what is collected, where it breaks, how far the systems diverge, and what it takes to reconcile them.
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