Club21 — AI-Powered E-Commerce Analytics
Client: Club21 (COMO Group) | Industry: Luxury Fashion E-Commerce | Platform: Shopify Plus | Region: Singapore, Malaysia, and 20+ shipping destinations
A complex, multi-channel operation
Club21's e-commerce operation is not small. The online store carries 40,000-50,000 active SKUs across 250+ luxury brands, ships to 20+ countries, and runs paid advertising through 400+ campaigns across Google Ads and Meta — managed through five regional ad accounts spanning Singapore, Malaysia, and several other markets. Klaviyo sends 100,000-150,000 emails per month through 40+ campaigns and 70+ automated flows. Combined paid media generates 15-20 million ad impressions monthly.
For a lean e-commerce team, keeping analytical eyes on all of this — across every channel, every market, every product category — is the core challenge.
Data in silos, insights out of reach
Like many mid-size e-commerce teams, Club21's analysts faced a recurring problem: data lived in silos. Orders data sat in Shopify. Email and SMS performance lived in Klaviyo. Paid media metrics were split across Google Ads and Meta. Website behaviour was in its own analytics stack. Market-level trends required manual cross-referencing.
Every reporting cycle meant hours of pulling exports, switching between dashboards, and manually connecting the dots — often under time pressure, and often missing the cross-channel patterns that matter most.
An 11-agent AI system across 7 channels
We designed and built a multi-agent AI system powered by Anthropic's Claude that analyzes e-commerce data across seven channels — orders, Klaviyo, SKU performance, website analytics, market intelligence, Google Ads, and Meta — then synthesizes cross-channel insights automatically.
How it works — two phases
Phase 1: Channel Analysis
Seven independent channel agents each analyze a single data domain. Each agent ingests standardized data exports, applies its domain-specific analytical framework, and writes 20 structured insights. Individual agents complete in 25-45 minutes each.
Phase 2: Synthesis
A synthesis agent reads all 140+ channel-level insights and identifies cross-channel patterns. A full cycle completes in under 3 hours.
Three support agents complete the system: data standardization, feedback processing, and instruction improvement. Eleven agents total.
Key design decisions
No custom infrastructure
Runs on Claude and Notion. No servers, no databases.
Simple data pipeline
Standardized CSV exports processed locally with Python.
Self-improving
Analyst feedback flows into a persistent knowledge base that sharpens each agent.
Built-in validation
Automated audits scan all 13 instruction pages after every change, catching 5-10 issues per scan.
The system at a glance
What the system delivered
Unlocking Hidden Revenue in Paid Media
The system’s first analysis surfaced that approximately 10-12% of combined paid media budget was flowing to campaigns that had not yet converted. At the same time, nine highest-performing Google Ads campaigns were running at 12x+ ROAS but hitting budget caps. By reallocating, the system identified SGD 1-2 million per year in additional attributed revenue potential — with no increase in spend.
Operational Efficiency
Full cross-channel analysis in under 3 hours. More than 2x increase in analytical depth — from 60 insights per run to 140+.
Data Quality Safeguards
The system caught a data processing issue affecting approximately 50% of transaction line items — a Shopify multi-item order export nuance. It identified the root cause, corrected its processing logic, and updated instructions to prevent recurrence — within the same cycle.
Cross-Channel Intelligence
In its first full-cycle run, the synthesis agent identified seven cross-channel connections spanning ad spend, SKU sell-through, email engagement, and operational disruptions.
Compounding Value
The system’s instruction set has been refined over 12 iterations in its first three months, with automated audits scanning all 13 instruction pages after every change.
Stack overview
Have a similar operation?
If your e-commerce team is managing multiple channels, markets, or brands — we should talk.