Intelligence Layer
Intelligence & Analytics.
The data layer everything else depends on.
Server-side tracking, attribution chains, dashboards, experimentation, and quality assurance — instrumented so leadership decisions are measurable, not instinctive. Every other layer of the revenue operating system depends on this one being right.
→DIRECT ANSWER
Intelligence & Analytics is the data infrastructure layer of a revenue operating system: server-side tracking, attribution, joined CRM + ad-platform + finance reporting, experimentation, and quality assurance. It is the layer every other layer reads from. Get it right and every other system makes better decisions; get it wrong and every other system makes confidently wrong decisions.
Specific outcome
Decisions on math, not vibes.
CAC + payback + cohort + channel mix instrumented and joined to CRM closed-won. Leadership reviews real numbers; vendors review attributed numbers.
Operational credibility
How we run.
Source-of-truth, not vanity
We measure what closes; we ignore what platforms self-report. ROAS in the ad platform is a marketing input, not a business metric.
GA4 · GTM · server-side · CRM · BI
Five layers of the data stack, designed together so they reconcile.
Joined to RevOps + Marketing
Intelligence is the substrate the other layers run on. We design them together; the reporting always reconciles.
The system
Six modules of operational intelligence.
Server-side tracking
GTM Server-Side, Stape.io, or custom endpoints. Meta CAPI, Google Enhanced Conversions, LinkedIn CAPI. Survives ATT, ad-blockers, cookie restrictions.
Attribution chain
Click → lead → opportunity → closed-won, instrumented end-to-end. CRM is the source of truth for closed-won; ad platforms train on CRM signals via CAPI.
Dashboards + reporting
Looker Studio (or Hex / Tableau / Mode) joining spend, sessions, leads, opps, closed-won. One number across marketing, sales, and finance.
Experimentation framework
Test design, sample sizing, instrumentation, results review. Lightweight where the team can absorb it; rigorous where the decision matters.
Observability + QA
Conversion fires monitored, schema breaks alerted, ETL drift caught. Reporting integrity reviewed monthly so dashboards stay trustworthy over time.
CAC + payback model
Channel-by-channel CAC, payback period, cohort LTV, contribution margin. The model that drives budget allocation, not the model that justifies last quarter.
What we do
Every engagement, in writing.
- 01Audit existing tracking, attribution, reporting, and ETL — find every drop point and reconciliation gap.
- 02Deploy server-side tracking + Conversion APIs across Meta, Google, LinkedIn, TikTok as relevant.
- 03Build the attribution chain: click → lead → opportunity → closed-won, joined and reconciled.
- 04Stand up the joined dashboard (Looker Studio or BI tool of choice) showing spend → revenue per channel.
- 05Install the experimentation framework calibrated to your team's decision velocity.
- 06Hand off the CAC + payback model and the cadence to maintain it (weekly + monthly + quarterly).
WHEN IT FITS
- +Marketing reports ROAS that does not match CRM closed-won — and you cannot tell which number is right.
- +You spend $50K+/month and decisions are made on platform-self-reported numbers.
- +You want CAC + payback + LTV instrumented and reviewed at the leadership cadence, not assembled in spreadsheets.
WHEN IT DOES NOT
- −You need a one-time GA4 setup — that is the Tracking Setup playbook, smaller scope.
- −You need a staff data analyst — we ship the system; the analyst operates it.
Architecture
Reporting is the closing layer of the revenue OS.
Implementation
How a typical run sequences out.
10-day audit: tracking config, attribution chain, reporting reconciliation, ETL integrity, dashboard architecture review. Output: gap list and target architecture.
4–8 weeks. Server-side tagging deployed, attribution wired, dashboards built, experimentation framework installed, CAC model handed off.
2-week training. Cadence established (weekly, monthly, quarterly). Optional ongoing QA via Embedded Retainer.
FAQ
Questions we get asked.
01Is this just GA4 + GTM consulting?+
Tracking Setup is one piece. Intelligence & Analytics is the broader layer: tracking + attribution + reporting + experimentation + QA, designed as one system. Tracking Setup is a sprint; Intelligence is the discipline.
02Why server-side tracking?+
Browser-side tracking dies with ATT, cookie restrictions, and ad-blockers. Server-side conversion APIs (Meta CAPI, Google Enhanced Conversions, LinkedIn CAPI) survive all three. It is now the default; not an upgrade.
03Can you measure offline conversions?+
Yes. Offline Conversion Import (OCI) feeds CRM closed-won back into Google Ads + Meta to train bidding algorithms. We deploy it as part of the attribution chain.
04How do you handle cross-domain / cross-device?+
GA4 cross-domain config, user-ID propagation, server-side stitching across booking portals, account subdomains, and content surfaces. Users moving between sites count as one session with one acquisition source.
05What about iOS 14 / ATT impact?+
Server-side tracking + Enhanced Conversions + Conversion APIs is how attribution survives ATT. We deploy the full stack; recovered conversions typically 30–60% within 30 days.
06Will this work with our existing data warehouse?+
Yes — we tie out CRM closed-won + ad spend + finance into your warehouse (BigQuery, Snowflake, Redshift, Postgres) where applicable. Dashboards read from warehouse for high-volume + reconcile-heavy clients.
07How is this priced?+
Audit: fixed fee. Implementation: scoped per engagement, typical range $25K–$80K. Retainer: monthly, scaled to data surface area.
08How is this different from your Tracking Setup playbook?+
The playbook is the 7-day sprint version of the tracking module specifically. The Intelligence service is broader (5 modules) and longer (10 days audit + 4–8 weeks build). Many engagements start with the playbook and expand.
Related
Adjacent services and playbooks.
Get started
Build the data layer everything else depends on.
A strategy call gets you a tracking + attribution audit summary and a 90-day implementation plan within 48 hours.