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Contents

1. Revenue systems

2. Builds

3. The operator

4. Writing

5. Journal

6. Resume

7. Appendix

206 wordsby CONNOR J. LAUGHLIN

Marketing analytics architecture.

Web analytics and CRM joined into one performance ledger that reconciles itself.

Outcome

Reduced manual reconciliation through an automated performance ledger.

Performance ledger joinThe performance ledger join path: session and source capture on the web side, the lead record, opportunity, and closed revenue on the CRM side, and the single ledger row the join writes.SESSION CAPTURESOURCE CAPTURELEAD RECORDOPPORTUNITYCLOSED REVENUELEDGER ROW
FIG_014 [ Performance ledger join ]The join writes one ledger row from both systems. The reconciliation then runs on its own.

Two systems, two versions of the truth, and a monthly argument about which one to believe. I joined web analytics to the CRM record so spend, source, and outcome land in one ledger row. The reconciliation that used to eat days now runs on its own.

The case

  1. 01The problem

    Reporting was polluted by mixed consumer and B2B traffic. UTM and GCLID capture was inconsistent. Attribution numbers led to bad decisions.

  2. 02What I built

    I rebuilt measurement from first principles: B2B audience segmentation, content groupings by solution line, conversion event taxonomy, UTM and GCLID governance, hidden-field capture, and cross-domain tracking requirements.

  3. 03What changed

    Analytics became reliable enough to run RevOps off it. Lead source integrity held up to scrutiny.

  4. 04Why it mattered

    Attribution errors do not stay in the report. They move into budget and headcount decisions, which is why this got rebuilt from first principles.

  5. 05What it proves

    Analytics is revenue infrastructure here, sitting upstream of budget decisions.

Proof

Chapter figures

B2B content groupings
By solution line. B2B content groupings. Attribution grouped by solution line rather than by page. Grouping counts are not published..
UTM and GCLID capture in CRM
Enforced. UTM and GCLID capture in CRM. Hidden-field requirements enforced at the form layer. A process rule, not a measured rate..

Systems built

  1. B2B audience segmentation in GA4
  2. Conversion event taxonomy (generate_lead, file_download, click_to_call, click_to_email)
  3. UTM and GCLID hidden-field capture
  4. Cross-domain and subdomain tracking requirements

Chapter details

Scope
  • Audience segmentation
  • content groupings
  • event taxonomy
  • UTM/GCLID governance
  • cross-domain tracking requirements.
Stack
  • GA4
  • GTM
  • WordPress
  • CRM (Zoho/Salesforce concepts)
Governance
  • Event and naming standards
  • hidden-field requirements
  • QA checklist
  • change control

Governance notes

  • Event and naming standards versioned
  • Measurement QA built into release steps

In the interview

Attribution sits upstream of budget, so I treat analytics as infrastructure and rebuild it when it lies.
Email Connor

Open to VP of Marketing & GTM, Head of GTM, VP Revenue Operations, and GTM engineering roles at AI-native B2B SaaS and PE-backed growth companies that build the tools of change. Chicago, hybrid or remote.