Maison de luxe · Tri-geo
Luxury house: 280 stores, MACH, follow-the-sun, ROI in 18 months.
Silos across stock/orders/CRM. MACH architecture, composable commerce, unified CDP, global team on 3 hubs.
KPI
+24%
conversion cross-canal
Duration
22 mois
Team
11 engineers
Hub(s)
Tri-geo
280 boutiques across 4 continents, inventory invisible from one channel to the next, and 9 months to ship a feature. A luxury brand cannot afford that time-to-market in 2026.
The context
European luxury house, 6,200 employees, physical presence in 38 countries. Three regional e-commerce platforms (EMEA, Americas, APAC), three CRMs, two inventory management tools, no single source of customer truth.
The problem
- Inventory/customers/orders siloed by region
- Time-to-market of a feature: 9 months on average
- No 360 customer view (same customer counted 3 to 5 times across systems)
- Cross-channel conversion under-measured, estimated 3x too low
- Dependency on a legacy vendor losing momentum
The approach
MACH architecture (Microservices, API-first, Cloud-native, Headless) built around commercetools as commerce engine. Global follow-the-sun team with Paris-Montreal-Tokyo rotation, shared governance.
The workstreams
- commercetools as single multi-region commerce engine
- CDP (Segment + Snowflake) as source of customer truth
- Next.js front per market with shared components
- Federated Algolia search with per-segment personalization
- Global follow-the-sun squad, handoff daily at 9 AM Paris/9 AM Tokyo
The stack
- commercetools (commerce engine), Algolia (search)
- Snowflake (CDP), Segment (collection), dbt (modeling)
- Next.js 16 (front), Vercel multi-region
- AWS multi-region (us-east-1, eu-west-1, ap-northeast-1)
- Contentful (headless CMS)
The results
- Feature time-to-market: 9 months to less than 2 weeks
- Cross-channel conversion: +24%
- 360 customer view: 100% of customers deduplicated within 6 months
- ROI reached at 18 months (vs 36 in initial business case)
- VIP customer NPS: +14 points in 12 months
« Abbeal delivered what three previous vendors had promised without holding up. The difference: they owned the hard trade-offs instead of leaving us to arbitrate. »
What we learned
MACH is powerful but explodes the number of integrations to maintain: you need a real platform team from the start. Follow-the-sun works with 3 hubs maximum, beyond that handoffs become unmanageable. Mistake: we underestimated in-store change management (training sales reps on new tools). To redo: embed 10 sales reps from month 1 in design, not month 18.
// Read next
Mobilité urbaine · Paris + Montréal
Mobility scale-up: −30% cloud bill, same SLOs.
AWS bill doubled in 18 months without matching traffic growth. GreenOps audit, refactor, Karpenter, ARM64. Measured outcome.
−30%
facture cloud
E-commerce sport · Paris
Sports leader: PWA, +18% mobile conversion, Lighthouse 92.
Mobile Lighthouse at 38, conversion falling. Next.js App Router, edge, images, splitting. Delivered in 6 months.
+18%
conversion mobile
Robotique industrielle · Tokyo
Japanese industrial: 80 AGVs, ROS 2, +40% warehouse throughput.
Slow fleet, collisions, downtime. Nav2 refactor, perception fusion, multi-agent planning. Zero collisions in 6 months.
+40%
throughput entrepôt
