Norrelle
AI-personalized styling and a live shopping assistant lifted Norrelle's average order value by 34%.
Project Snapshot
- Client
- Norrelle
- Industry
- E-Commerce / Fashion Retail
- Platform
- Web App
- Timeline
- 4 months
- Our Role
- Full-stack web development, AI integration, and UI/UX design
The Challenge
Norrelle launched three years ago as a small capsule-collection label and had grown into a full multi-category fashion and lifestyle store — women's, men's, and accessories — almost entirely on word of mouth. The problem was that their storefront hadn't grown with them. Every visitor saw the same generic homepage and the same static category grids, regardless of what they'd browsed before, what they'd bought last season, or what size and style they actually wore.
Customer support was buried in repetitive questions that had nothing to do with growing the brand: "does this run small?", "where's my order?", "what goes with this?" Norrelle's two-person support team was fielding hundreds of these a week over email, with response times stretching past 24 hours during sale periods — long enough that most shoppers had already abandoned their cart.
Every unanswered sizing question was a lost sale, and every generic homepage was a missed chance to show a returning customer something they'd actually want. Norrelle's leadership estimated that sizing uncertainty alone was responsible for a return rate nearly double the category average, eating directly into margin.
The existing site ran on a heavily customized, years-old theme with no real product data layer to build on — no browsing history, no purchase graph, nothing that could power real personalization without a rebuild.
Our Solution
iMobdev proposed a full storefront rebuild centered on one idea: the site should feel different for every visitor, and shoppers should never have to leave the page to get a real answer. That meant building a genuine customer data and recommendation layer underneath a fashion-forward front end, not just a fresh coat of paint.
On the architecture side, we rebuilt Norrelle on Next.js with a headless commerce backend, syncing catalog, inventory, and order data through a Node.js service layer. Every product view, wishlist add, and past purchase feeds an event stream that powers the recommendation engine, so personalization improves with every session instead of staying static.
The centerpiece AI feature is the "AI Styled For You" engine: a collaborative-filtering and embeddings-based similarity model (built on product attribute vectors — category, fabric, color, silhouette — blended with real-time behavioral signals) that resurfaces a fresh, ranked product grid on the homepage and product pages, each item tagged with a plain-language "why we picked this" reason so the logic feels transparent rather than creepy. Alongside it, we built the Norrelle AI Stylist, an LLM-powered chat assistant (OpenAI API + a retrieval layer over Norrelle's size charts, fabric guides, and live order data) that handles sizing questions, styling advice, and order tracking in natural conversation, with quick-reply chips for the most common asks.
On the design side, we leaned into a warm, editorial look — cream and terracotta, generous photography space, soft rounded cards — so the AI features feel like styling help from the brand, not bolted-on tech. Checkout was rebuilt around a "Complete the Look" upsell row driven by the same recommendation model, and the whole build shipped in three phases: storefront and catalog first, recommendation engine second, AI stylist and checkout upsells last.
The Impact
Within the first full quarter live, Norrelle saw average order value climb 34% and sizing-related returns drop by nearly a third, as shoppers got confident sizing answers before they ever reached checkout. The AI Stylist now resolves the majority of sizing and order-status questions without a human touching a ticket, freeing Norrelle's small support team to focus on the conversations that actually need a person.
Working with iMobdev, Norrelle turned its storefront into something closer to a personal shopper than a static catalog. The roadmap ahead includes extending the recommendation engine into email and SMS re-engagement, and a wishlist-aware "restock me" alert system — all building on the same behavioral data layer laid down in this first release.
Key Features
What We Built
AI Styled For You
A live, personalized product feed driven by browsing and purchase history, updated every visit.
AI Shopping Assistant
A floating stylist chatbot that handles sizing, styling questions, and order tracking in real time.
Complete the Look Upsell
AI-curated add-on picks surfaced right in the cart, matched to what's already in the bag.
Headless Commerce Rebuild
A fast, flexible Next.js storefront on a headless backend built to support real-time personalization.
Conversational Order Tracking
Shoppers can ask the AI stylist for order status instead of digging through account pages or email.
Editorial Fashion UI
A warm, gallery-like storefront design that puts photography and product storytelling first.
Tech Stack
- Next.js
- Node.js
- OPOpenAI API
- RERecommendation Engine (collaborative filtering + embeddings)
- SHShopify Plus
- Stripe
- PostgreSQL
Screenshots
App in Action
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“Our AI stylist answers the questions that used to sit in our inbox for a day, and it answers them instantly, in our brand voice. It's the closest thing to having a stylist on staff around the clock.”
Norrelle
Illustrative Example, Concept project — not an actual client engagement
Why 200+ Companies Choose iMOBDEV Over the Rest
AI-Native Approach
We don't retrofit AI; we design for it from day one — architecture, data, and UX.
On-Time, Every Time
Agile sprints with clear milestones, transparent reporting, and zero deadline surprises.
Transparent Pricing
No hidden costs. Fixed-price or dedicated team models — you choose what fits.
Global Team, Local Focus
India-based delivery excellence with US and UAE client engagement offices.
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ISO 27001-compliant, NDA-ready, GDPR-aware — secure by design at every layer.
Ongoing Partnership
We're a long-term partner, not a one-and-done vendor. We grow as you grow.
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