Visitor identification, outbound automation, and a full attribution stack — built in phases over 15 months. CVR went from 1.1% to 6.72%.
The Problem
The brand had consistent traffic and a working Shopify store, but no way to identify anonymous visitors or act on them. Conversion rate was stuck at 1.1% — meaning 98.9% of every session was lost with no recovery path.
There was no outbound motion, no attribution model to understand what was working, and no automation to close the gap between visit and purchase. The team knew they had a revenue leak. They didn't know where or how to fix it.
The Solution
We built the infrastructure in three sequential phases — each one unlocking the next. By the end, the brand had a complete loop: identify visitor, activate outbound, attribute revenue, optimize.
Phase 01
Visitor Identification
Anonymous site visitors became known contacts. We deployed a visitor-identification layer across the Shopify storefront to capture identity data at the session level.
Phase 02
Outbound Activation
Identified visitors entered automated sequences immediately. We built multi-channel follow-up flows in GHL, orchestrated by n8n, covering email and SMS.
Phase 03
Attribution & Optimization
We built the measurement layer so every revenue euro could be traced back to a touchpoint. CVR testing and open rate loops drove continuous improvement.
Timeline
Each milestone unlocked the next phase. We didn't start optimizing until we had enough data — and we didn't claim attribution until the model was validated.
Dec 2024
Infrastructure Audit & Stack Selection
Mapped existing tools, identified the identity gap, selected the stack (identity resolution + GHL + n8n). Established baseline CVR at 1.1%.
Baseline CVR: 1.1%Jan – Feb 2025
Phase 1 Deploy — Visitor Identification Live
Identity-resolution pixel deployed on Shopify. First identified contacts flowing into GHL. Initial contact pool built from existing traffic.
First 800 contacts identifiedMar – May 2025
Phase 2 Deploy — Outbound Sequences Active
GHL email + SMS sequences launched. Abandoned cart flows went live first, followed by browse abandonment and win-back campaigns. Open rates hit 40%+ in week one.
CVR climbing to 2.8%Jun – Sep 2025
Phase 3 Deploy — Attribution Model Built
Python attribution model validated against 6 months of data. Subject line testing framework introduced. Revenue per send metric established as primary KPI.
CVR at 4.3% · €180K attributedOct 2025 – Mar 2026
Scale & Optimize — Full Revenue Loop Running
All three phases running in parallel. Continuous offer and copy testing drove CVR from 4.3% to 6.72%. Peak open rate hit 71% in a win-back sequence.
CVR 6.72% · €500K attributed · 71% peak openResults
All metrics are verified against Shopify revenue data and GHL send logs. Attribution model validated against a 90-day holdout period to confirm lift.
Attributed Revenue
Total revenue attributed to the visitor identification and outbound automation system over 15 months, validated against Shopify data.
CVR Improvement
Conversion rate grew from a baseline of 1.1% to 6.72% — a 6.1× lift driven by identity resolution and automated follow-up sequences.
Peak Email Open Rate
Peak open rate achieved in a win-back sequence. Average open rate across all active flows sustained above 40% throughout the engagement.
Tech Stack
All tools are white-labeled and client-owned after handoff. No proprietary lock-in — the infrastructure runs independently after we're done building.
We'll audit your current setup and tell you exactly where you're losing revenue — no pitch, no fluff.