Challenge. UGG Direct needed a from-scratch e-commerce build that could handle seasonal surges, frequent product drops, and complex size/colour variants—without ballooning headcount. The brief: launch a premium, high-converting storefront, implement an AI-assisted inventory & fulfilment layer to cut stockouts and errors, and run multi-channel digital marketing to drive profitable traffic at scale.

Solution. We launched a Shopify stack with a conversion-first theme, headless-ready architecture, and WCAG-conscious UX. An AI engine ingests sales velocity, returns, supplier lead times, and seasonal demand to forecast re-orders, auto-bundle slow movers, and prioritise pick paths in the warehouse. On the front end, AI product recommendations, search autocomplete, and dynamic merchandising lift AOV. For growth, we ran a full-funnel mix across Google (Search/PMAX), Meta, TikTok, and email/SMS—backed by server-side tracking and a clean UTM scheme.

Implementation. Go-live in 6 weeks: week 1–2 data model & SKU strategy; week 3 theme/dev & PDP testing; week 4 payments, tax, shipping, and WMS hooks; week 5 AI inventory rules (forecasting, safety stock, auto-POs), barcoded pick/pack, and returns portal; week 6 analytics, feed ops, and launch campaigns. Core Web Vitals improved to LCP 1.8s, CLS 0.02, INP 180ms. The AI layer forecast accuracy reached 94.6% at the style level; pick/pack scanners cut mis-picks by 68%; and automated purchase orders reduced stockout minutes per SKU by -57%.

Results (first 90 days). Sessions +112%, with paid contributing 62% of incremental traffic; overall conversion rate +36% (2.1% → 2.86%); AOV +14% from AI recommendations; revenue per session +57%. Blended CPA fell -24%; MER improved from 2.6× → 3.3×; email/SMS drove 22% of revenue at 18× program ROAS. Operationally, order cycle time dropped -41% (23.5h → 13.9h), WISMO tickets -38%, return-to-restock time -33%, and inventory holding cost -11%. Net effect: a premium brand experience, leaner operations, and durable, profitable growth.