Growth decisions were made on six conflicting dashboards. Nobody could answer which channel produced revenue, and the team spent more time assembling reports than acting on them.
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AIAutomationSaaSMarketing
TwinAI Growth OS
An end-to-end growth operating system: server-side tracking, automated reporting and a suite of AI agents running acquisition operations.
TwinAI · 2024 — 2025
3.4x
Pipeline
120
Hours saved / mo
-31%
CAC
Two weeks of instrumentation audit: every event, every tool, every handoff mapped. We interviewed sales on lead quality and reconciled CRM revenue against platform-reported conversions to size the attribution gap — it was 38%.
One source of truth first, automation second, AI third. Rebuild measurement, then remove manual operations, then layer intelligence on top of clean data — never the reverse.
Server-side GA4 + conversion APIs for Meta, Google and LinkedIn, deduplicated by event ID, reconciled nightly against CRM closed-won.
Weekly creative testing loop with a minimum-3-concepts rule, budget reallocation against payback windows rather than platform ROAS, and monthly agent prompt evaluations scored on human review.
AI amplifies whatever data discipline already exists. Deploying agents before fixing measurement would have automated the wrong conclusions faster.
- 01Deployed server-side GTM with a first-party data layer and consent-aware event forwarding.
- 02Modeled all channel, CRM and product data into a warehouse with a single revenue definition.
- 03Built an executive dashboard refreshed hourly with channel, cohort and payback views.
- 04Shipped AI agents for lead qualification, creative briefing and weekly performance narratives.
- 05Wrote the operating cadence: what gets reviewed daily, weekly, monthly, and by whom.
- 3.4x qualified pipeline in 9 months
- 31% lower blended CAC
- Reporting time cut from 14 hours per week to under 1
- Attribution gap closed from 38% to under 6%
Executive dashboard
Agent console
Event architecture
GTM ServerGA4BigQueryn8nOpenAILooker StudioHubSpot
Architect and operator. I designed the system, built the tracking and automation layers, and led the team running it.
Growth became forecastable. Budget decisions moved from opinion to payback math, and the company kept the infrastructure permanently.
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