Fashion Commerce Built
For The Drop And The Return

Apparel breaks generic e-commerce in two specific places: one product becomes forty sellable items, and a third of what ships comes back. Build without planning for both and the platform fights you every season.

Fashion & Lifestyle work in progress
The Sector

Size, Colour, Season, Return

A single style in eight sizes and five colours is forty SKUs, each with its own stock, its own photography and its own return rate. Multiply that by a seasonal catalogue and the data model stops being an implementation detail.

Then the returns arrive. In apparel that is normal, not a failure — but it has to be a designed flow with restocking, condition checks and refunds that reconcile, rather than an email address and a spreadsheet.

  • Variants, options and stock modelled the way your buying team thinks
  • Returns and exchanges built as a first-class flow, not an afterthought
  • Drop days load-tested, because a launch that falls over is the whole campaign

What We Build For Fashion

The systems behind a season, from lookbook to restock.

D2C Storefronts

Brand-led stores where the imagery, the editorial and the product pages are yours to art-direct, not a theme's.

PIM & Catalogue

One source for products, variants, attributes, imagery and copy, syndicated to every channel you sell on.

Drop & Launch Platforms

Timed releases, queues, raffles and stock reservation that hold up when the whole mailing list arrives at once.

Size & Fit Tools

Size guides, fit recommendation and review-based sizing signals, aimed squarely at the biggest cause of returns.

Omnichannel & Store

Ship-from-store, click and collect, endless aisle and one stock position shared by the store and the site.

Loyalty & Community

Tiers, early access, referrals and member drops — the mechanics repeat customers actually respond to.

What Decides Whether It Holds

Apparel platforms are tested twice a year, hard, on a date you announced in advance.

Variant & SKU modelling

Options, variants and bundles structured so a new season is data entry rather than a development ticket.

Returns & exchanges

Self-serve returns, condition handling, restocking and refunds that reconcile against the original order.

Drop-day capacity

Queueing, caching and stock reservation rehearsed at launch scale, so the first minute does not decide the season.

Imagery & content

Fast, art-directable product and editorial pages with a media pipeline that does not punish large photography.

Omnichannel inventory

One stock position across warehouse, stores and marketplaces, with allocation rules that prevent overselling.

Traceability & disclosure

Material, origin and care data carried through the catalogue, which regulation and customers increasingly both expect.

What We Connect To

A fashion brand sells in more places than it manages. Keeping stock, price and content consistent across all of them is most of the engineering.

Talk to our team
PIM & DAM
ERP & merchandising
Retail POS
Payments & BNPL
3PL & warehouse
Marketplaces
Social commerce
Email & SMS lifecycle
Size & fit providers

How We Deliver

Planned around your season. We launch between drops, never into one.

Model the catalogue

Styles, variants, attributes and the way your buying and merchandising team actually works, documented first.

Commerce core

Catalogue, cart, checkout and returns built and tested against a real season of products, not sample data.

Omnichannel and content

Store, marketplace and content integrations connected, with stock reconciled across all of them.

Rehearse the drop

Launch-scale load test on staging, then go live on a quiet week ahead of the drop you care about.

What Does Your Next Drop Need?

The size of the catalogue, the return rate you live with, the traffic you expect in minute one. Those three answers shape the whole build.

Talk to our team
FAQs

Fashion & Lifestyle Questions

What apparel and lifestyle brands ask us before starting.

Three things: the variant explosion, the return rate, and the traffic shape. Apparel has far more SKUs per product, returns are a routine flow rather than an exception, and demand arrives in spikes on announced dates. Each of those changes the data model and the infrastructure plan.

Some of it. Better size guidance, honest fit signals from reviews, accurate colour and fabric photography and clear measurements all help, and they are measurable. It will not eliminate returns — in this category a healthy return rate is a sign people are buying with confidence.

One inventory position with reservations and allocation rules, updated from POS and warehouse events rather than a nightly file. Ship-from-store and click and collect then work off the same numbers instead of a second, slightly wrong copy.

If it is tested for one. We rehearse launch-minute traffic on staging with queueing and stock reservation in place, then fix what breaks. Drop capacity is a test result on our projects, not an assumption.