Built for Brands That Sell.
From recovering your lost conversions to activating your best customers on every channel — the full stack that makes Shopify brands compound revenue without renting their data from a vendor cloud or trusting someone else's pixel.
CMS IMAGE — E-COMMERCE STACK ARCHITECTURE
Three Leaks Compounding Against You Right Now.
E-commerce growth ceilings rarely come from creative. They come from the data layer underneath — what your platforms see vs what is actually happening.
Your Tracking Lies to Meta
iOS14+, ad blockers, and the new privacy stack quietly remove 30% of your conversions from the pixel. Your ROAS report is fiction. Smart Bidding is optimizing on incomplete data — every euro spent on the wrong audience compounds.
30% of conversions invisibleYour Customer Is Fragmented
Same human is anon_id_1234 in Shopify, subscriber_5678 in Klaviyo, lead_9012 in your CRM, audience_ABC in Meta. None of them know about each other. Your "personalized" flows are sending the wrong message to the wrong person.
5+ disconnected user IDs per customerYou Pay to Retarget Refunders
No cross-channel suppression means you waste budget retargeting people who already bought — or worse, refunded. Lookalikes seeded on "all buyers" pull in low-LTV customers because that's what Meta sees. Your acquisition ceiling is the warehouse you never built.
Refunders, recent buyers — still in your ad audiencesThe E-commerce Stack — Five Layers, One System
Each layer can be deployed independently. Together they form a stack that compounds — and that you fully own, end to end.
Foundation — Server-Side Tracking
Server-side GTM, Meta CAPI, Google Ads Enhanced Conversions, LinkedIn CAPI, TikTok Events API. Conversions captured server-to-server, immune to ad blockers and ITP. First-party cookies persist 90+ days.
Data Layer — Warehouse + Modeling
BigQuery as the canonical source. Shopify orders, GA4 events, ads spend, CRM contacts ingested via Airbyte and native exports. dbt models build mart tables: RFM segments, cohort retention, LTV / CAC by channel.
Identity — RCU Across Every Tool
RudderStack collects events client + server side. dbt models stitch identity: Shopify customer_id ↔ Klaviyo email ↔ Meta pixel ID ↔ CRM contact. One canonical_user_id propagates to every downstream destination.
Activation — Audiences Back to Every Channel
RFM tiers, churn cohorts, LTV brackets, propensity scores synced daily from BigQuery to Meta Custom Audiences, Google Customer Match, Klaviyo lists, Brevo audiences, WhatsApp automation triggers. Suppression lists pushed in parallel — refunders, recent buyers, opt-outs.
Automation — Operations That Run Themselves
n8n self-hosted orchestrates the back-office: refund flows cross-system (Shopify → Klaviyo suppression → Meta exclusion → support ticket), inventory sync Shopify ↔ 3PL, loyalty point allocation from warehouse RFM, abandoned cart escalation tiered (1h email → 24h SMS → 48h WhatsApp → 72h human).
CMS IMAGE — STACK LAYERS DIAGRAM
What This Stack Actually Unlocks
Six concrete outcomes — not features. This is what changes about your business when the data layer is engineered properly.
Recover the Conversions You Already Earned
Server-side tracking and CAPI recover 13–20% of conversions blocked by ITP, ad blockers, and consent denials — without spending another euro on ads.
See Which 20% of Customers Drive 80% of LTV
Warehouse-driven RFM segmentation and cohort retention curves replace gut feel with the actual Pareto distribution of your customer base.
Stop Paying to Reach People Who Just Bought
Automated cross-channel suppression removes recent buyers, refunders, and opt-outs from Meta / Google / TikTok / Klaviyo in parallel — daily, no manual exports.
Lookalikes Seeded on Your Best Customers
Top 10% LTV cohort feeds Meta and Google lookalike audiences — the model finally learns from the right examples, not from "anyone who bought once".
WhatsApp Automation Triggered by Real Signals
Abandoned high-AOV checkouts, churn risk cohorts, post-purchase confirmations — WhatsApp flows triggered by warehouse events, not by point-and-click rules.
Refund Automation Cross-System
A Shopify refund triggers Klaviyo suppression, Meta exclusion, support ticket, and accounting update in parallel — instantly, every time, no human in the loop.
The Six Services, in E-commerce Context
Each service stands on its own. Together, they form the stack. Click any service to go deep.
Data & Tracking
Server-side GTM, Meta CAPI, Google Ads Enhanced. Recover 13–20% of conversions blocked by ITP and ad blockers.
Data Engineering
BigQuery warehouse with dbt models on top of Shopify, GA4, and your ad accounts. RFM segments and cohort retention served daily.
CDP & Architecture
RudderStack RCU stitching Shopify ↔ Klaviyo ↔ Meta ↔ CRM. One canonical customer across every tool. 100% data ownership.
CRM Marketing
Klaviyo (or Brevo) flows engineered for revenue, not opens. WhatsApp automation triggered by warehouse signals. Deliverability as engineering.
How the Stack Deploys — Four Phases
Full stack typically deploys over 4–6 months end to end, but each phase ships independently — start where it hurts most, expand from there.
Phase 1 — Foundation
4–6 weeksServer-side tracking (sGTM + Meta CAPI + Google Ads Enhanced) deployed. BigQuery warehouse provisioned. Shopify, GA4, ad accounts, and CRM ingested via Airbyte. First dbt staging models — the data layer the rest of the stack sits on.
Phase 2 — Identity & Activation
4–6 weeksRudderStack deployed for client + server side event collection. dbt RCU models stitch identity across Shopify, Klaviyo, Meta, CRM. First reverse-ETL audiences live — RFM tiers and top-LTV lookalikes synced daily to Meta, Google, TikTok, LinkedIn. Suppression lists in parallel.
Phase 3 — Lifecycle & Automation
4–6 weeksKlaviyo (or Brevo) rebuilt around warehouse-driven segments. 8–12 lifecycle flows live with revenue attribution per flow. WhatsApp automation triggered by warehouse events. n8n self-hosted handling refund flows, inventory sync, loyalty allocation, abandoned cart escalation.
Phase 4 — Optimization
OngoingSmart Bidding adapts to the new signal quality over 30–60 days. Audience drift detection, AI-augmented routing where it pays, monthly review of what to optimize and what to retire. The stack stops being a project and becomes a system the team owns.
CMS IMAGE — ENGAGEMENT TIMELINE
What the Full Stack Compounds Into
+0–25%
ROAS lift from first-party audiences
0–20%
Conversions recovered via server-side
0–15%
Revenue lift from lifecycle flows
0–12 hrs
Per week reclaimed via automation
Built on the Tools You Already Use
Plus dbt, RudderStack, Klaviyo, MessageBird, and a long tail of niche tools we wire in where they pay. Tool choice per layer, not per vendor.
Who This Stack Is — and Isn't — For
Honesty up front saves everyone a discovery call. Here is who we work best with — and who we will refer elsewhere.
For You If
- DTC brand running on Shopify or Magento
- $500K–$50M annual revenue
- 4+ paid channels (Meta, Google, TikTok, LinkedIn, etc.)
- In-house marketing or growth team
- Frustration with conflicting reports across tools
- Ready to own your data layer end-to-end
Not For You If
- Pre-launch brands with under $500K ARR
- Single-channel acquisition (Meta only) — wait until you scale
- Teams with zero tech infrastructure ownership
- Brands looking for a "Klaviyo template pack" — not our shape
- Pure copy or creative engagements without architecture
Frequently Asked Questions
Ready to Build Your E-commerce Stack?
Get a free audit of your current tracking, identity, activation, and automation layers. We will map the gap and show you what a full stack would unlock for your brand.