Background
Tech Leads IT sells IT training to a global audience through paid search, paid social, organic and email. Leads were arriving with no source data attached, so every channel could claim the same conversion and nobody could prove which spend produced revenue.
Before any media optimisation was worth doing, the business needed a measurement layer it could defend — and one KPI that connected marketing activity to sales-qualified outcomes.
The challenge
Leads arrived with no source data. Paid, organic and social all claimed the same conversions, form submissions were counted inconsistently, and budget was being defended with platform-reported numbers that never matched the CRM.
What I did
- 1
Implemented GA4 with a clean event and conversion schema mapped to real business actions, not vanity clicks.
- 2
Deployed Google Tag Manager as the single tagging layer — one container, versioned, with documented triggers and no hardcoded pixels.
- 3
Enforced a strict UTM taxonomy across every campaign, email and partner link so channels stopped stealing each other's credit.
- 4
Built Looker Studio dashboards blending ad spend with CRM outcomes, reporting cost per qualified lead by campaign and creative.
- 5
Introduced CPL-Q (qualified cost per lead) as the optimisation target, replacing raw lead volume in every review.
How it was measured
- GA4 configured with a deliberate event and conversion schema mapped to real business actions: qualified form submissions, booked consultations and enrolments — not clicks and scrolls.
- Google Tag Manager as the single tagging layer: one versioned container, documented triggers, no stray hardcoded pixels on the site.
- A strict UTM taxonomy applied to every campaign, email and partner link, enforced at launch QA rather than cleaned up afterwards.
- Looker Studio dashboards blending ad spend with CRM outcomes to report cost per qualified lead (CPL-Q) by campaign, ad set and creative.
The outcome
- Every lead traceable to its campaign, creative and keyword.
- Budget reallocated toward campaigns producing qualified pipeline rather than the cheapest raw leads.
- Reporting reduced from manual spreadsheet pulls to a live dashboard the whole team reads.
What I'd carry into a similar project
- Attribution is a naming-discipline problem as much as a tooling one. The UTM taxonomy is what makes the dashboard honest.
- Choosing the KPI is the intervention. The moment CPL-Q replaced raw lead volume in reviews, budget moved on its own toward campaigns producing pipeline.
- Platform-reported conversions and CRM outcomes will never match exactly. Pick the CRM as the source of truth and report the gap openly.
Stack used
Questions I get about this work
What is CPL-Q and why use it?
CPL-Q is qualified cost per lead — spend divided by the leads sales actually accepts. It stops campaigns from being rewarded for cheap, unusable volume, which raw CPL always does.
What does an attribution stack built from scratch include?
GA4 with a clean event and conversion schema, Google Tag Manager as the single tagging layer, an enforced UTM taxonomy, and Looker Studio dashboards blending ad spend with CRM outcomes.
Want results like this on your account?
Tell me where growth is stalling and I'll tell you what I'd do first.
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