Case studies
These placeholder case studies show the type of work typically delivered across measurement, infrastructure and AI workflow assessment.
Context
A growth team was relying on fragmented platform reporting, agency-owned dashboards and inconsistent attribution logic across paid media channels.
Work
We reviewed tagging, conversion APIs, GA4 configuration, CRM handoff, reporting ownership and decision workflows.
Outcome
The audit identified duplicated reporting spend, unreliable conversion signals and a practical route to consolidate measurement into a cleaner cloud reporting layer.
Context
A leadership team needed better visibility across commercial performance, but core datasets were spread across SaaS platforms, exports and manually maintained spreadsheets.
Work
We mapped data sources, pipeline dependencies, transformation logic and reporting usage across finance, marketing and operations.
Outcome
The review produced a phased modernisation plan for cloud-native pipelines, governed metrics and lower reliance on manual spreadsheet reconciliation.
Context
A department wanted to use AI but had no clear view of which workflows would create measurable value rather than isolated experimentation.
Work
We assessed recurring reporting, analysis, QA, documentation and internal coordination processes against feasibility, risk and commercial impact.
Outcome
The assessment prioritised AI agents and automation candidates with clear owners, expected time savings and implementation sequencing.
A short discovery process can identify the business case, technical constraints and highest-value first move.