Systems

The infrastructure behind modern revenue.

Three interconnected systems. Each one solves a distinct failure mode in how brands convert traffic into revenue. Together they form a complete operational layer.

A — Revenue Intelligence B — AI Growth Systems C — Competitor Intelligence

Pillar A · Revenue Intelligence

Understand what actually drives growth.

Most brands optimize what they can measure. We build the measurement layer so you can measure what matters.

GA4 out of the box tells you sessions and bounce rate. It doesn't tell you which channel drives customers who actually come back. It doesn't tell you which SKU has a 6-month LTV 3× the average. It doesn't tell you where your attribution model is lying. We build the stack that does — from raw event data through to executive dashboards and AI-generated insight summaries.

What you get

1

Full attribution visibility

Know exactly which ad → which click → which revenue, down to SKU and cohort level

2

LTV and cohort intelligence

Understand which acquisition channels produce customers worth keeping, not just converting

3

AI reporting copilot

Weekly automated insight summaries — trends, anomalies, and recommended actions in plain English

4

One source of truth

Every team sees the same numbers. No more "the spreadsheet says" vs "the dashboard says"

Architecture

Data Collection Event Tracking GA4 · Meta CAPI · Shopify webhooks · server-side GTM
Storage Data Warehouse BigQuery · Airtable · raw event logs
Attribution Revenue Model Python · custom attribution logic · holdout validation
Visualization Dashboards Vercel · Looker Studio · Airtable views
Intelligence AI Copilot Claude API · weekly summaries · anomaly alerts

Stack

GA4 BigQuery Meta CAPI Python Vercel Airtable Claude API Looker Studio n8n

Build Timeline

Week 1 Audit existing tracking, map gaps, define measurement plan
Week 2 Deploy server-side tracking, fix attribution gaps, connect BigQuery
Week 3 Build LTV model, cohort analysis, custom dashboard layer
Week 4 AI reporting copilot live, team walkthrough, SOPs handed off

Pillar B · AI Growth Systems

Automate execution at operator scale.

Manual processes cap your growth at headcount. We remove the ceiling.

Every visitor who leaves your store without buying is a lost revenue event. Every lead who doesn't hear from you for 72 hours is a cooled-off deal. Every manual report your team builds is time not spent on strategy. We build the AI agents and automation workflows that close all three gaps — visitor identification, outbound activation, and reporting — running without human intervention at scale.

What you get

1

Visitor identification at scale

Anonymous traffic becomes known contacts — identity resolution at the session level

2

Automated outbound activation

Multi-channel sequences (email, SMS) triggered instantly on identified visitor behaviour

3

AI research pipelines

Prospect discovery, enrichment, and personalisation — fully automated from ICP definition to booked call

4

Lifecycle automation

Cart abandonment, win-back, upsell — every sequence running 24/7 without manual intervention

Architecture

Identification Visitor ID Identity resolution · Shopify pixel · session resolution
Orchestration Automation Engine n8n · trigger logic · branching conditions
CRM Contact & Pipeline GoHighLevel · contact enrichment · pipeline stages
Activation Multi-Channel Sequences Email · SMS · follow-up cadences · offer triggers
Intelligence AI Agents Claude API · prospect research · copy personalisation

Stack

Identity Resolution GoHighLevel n8n Shopify Claude API Python Instantly Apollo Exa.ai

Build Timeline

Week 1 Deploy visitor ID pixel, connect GHL, map customer journey stages
Week 2 Build n8n trigger logic, launch cart abandonment + browse sequences
Week 3 Win-back campaigns live, outbound AI pipeline configured
Week 4 All sequences live, reporting dashboard built, handoff + SOPs

Pillar C · Competitor Intelligence · Differentiator

See what competitors are doing before the market catches up.

Most brands react to competitors. We build the systems that let you anticipate them.

Your competitors are changing their ads, landing pages, pricing, and offers constantly. Most brands find out after the fact — when their ROAS drops or a competitor's angle starts showing up in their customer interviews. We build automated intelligence systems that track those changes in real time: ad creative, landing page copy, offer structure, pricing shifts, and keyword positioning — scraped, analysed, and surfaced to you before the market reacts.

What you get

1

Live competitor ad monitoring

Track which ads competitors are running, how long they've been live, and what's performing

2

Landing page change tracking

Get notified when a competitor changes their headline, offer, pricing, or CTA

3

AI creative teardowns

Automated analysis of competitor creative strategy — hooks, formats, angles, and trends

4

Weekly intelligence brief

AI-generated summary of what changed in your competitive landscape and what it means

Architecture

Data Collection Scraping Layer Apify · Firecrawl · Meta Ad Library API
Monitoring Change Detection n8n · page diff logic · structured extraction
Analysis AI Teardown Engine Claude API · creative analysis · pattern detection
Storage Intelligence Database Airtable · versioned snapshots · trend history
Output Weekly Brief AI-written · Slack / email · actionable insights

Stack

Apify Firecrawl Meta Ad Library API Claude API n8n Airtable Python Exa.ai

Build Timeline

Week 1 Define competitor set, configure Apify scrapers, connect Meta Ad Library
Week 2 Landing page change detection live, structured data flowing to Airtable
Week 3 AI teardown engine trained on your competitive context, weekly brief templated
Week 4 First intelligence brief delivered, alerts live, full system handed off

Which system does your business need first?

Book a strategy call. We'll audit your current setup and tell you exactly which pillar has the highest leverage for your stage.