Case Study · Luxury Fashion
Palisade
AI-assisted product discovery for a high-SKU luxury fashion storefront, on desktop and mobile.
Palisade's catalogue was both its strength and its problem: search for dresses and you got more than twelve thousand results and twenty-seven filters. We redesigned discovery around what shoppers actually ask for, in plain language, and made sure a missing size never ends the visit.
Client / Product Overview
A luxury fashion retailer with a large, multi-designer catalogue, selling online on desktop and mobile.
- Industry
- Luxury Fashion
- Services Provided
- Project Scope
- UX audit of the existing shopping experience, AI-assisted product discovery, a redesigned product detail page and cart, and a mobile-first shopping flow from discovery to checkout.
Before
The Challenge
Too many filters, too many products and no guidance. Sizing was inconsistent, out-of-stock sizes were dead ends, and shoppers spent their time narrowing a list instead of finding something to buy.
Approach
From the problem to a direction
Strategy first, then the experience, then how it looks.
- 01
Discovery / Strategy
The audit showed that shoppers already knew what they wanted; they just couldn't express it through filters. So the strategy was to let them say it, and have the store translate that into the right filters and results.
- 02
UX Approach
A shopping assistant turns a request like “black evening dresses under $250, size M” into applied filters, a focused set of matches and smart refinements. On the product page, an unavailable size prompts curated alternatives instead of a dead end, and the cart slides in without leaving the page.
- 03
UI / Visual Direction
Ivory grounds, plum and burgundy accents, serif display type and editorial photography — the restraint of a luxury boutique, with the assistant styled as a quiet part of the page rather than a chatbot bolted on.
The Build
Development
A storefront with AI-assisted discovery built into its listing pages, size-aware alternatives on product detail, a slide-in cart, and a mobile flow covering discovery, filters, product detail and checkout.
Key Features
- 01AI shopping assistant that turns plain-language requests into filters
- 02Smart refinements and top matching styles
- 03Curated alternatives when a size is out of stock
- 04“You might also like” recommendations on product detail
- 05Slide-in cart
- 06Mobile flow from discovery and filters to product detail, cart and checkout
The Result
Final Product
A storefront where a shopper can describe what they want and see it, recover from a missing size without leaving, and do the whole thing comfortably on a phone.
01 / 03Before: a high-SKU listing page with 27 filters 
02 / 03Product detail with size alternatives and a slide-in cart 
03 / 03The mobile shopping experience, with results
Outcome
Results
Shoppers engage with more products and find what they want faster. Add-to-cart rose 21%, size-related exits fell 28%, and more mobile shoppers progress through checkout.
- 32%More product engagement
- 26%Faster discovery
- +21%Add-to-cart
- 28%Fewer size-related exits
- +19%Mobile checkout progression
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