Commerce engineering for fashion brands

Shopify, Magento and Adobe Commerce, WooCommerce, and headless storefronts on Next.js, chosen by catalogue size, scale and roadmap rather than preference. Fashion has a specific pressure most categories do not: variant counts multiply quickly once every product carries sizes and colourways, and platforms differ considerably in how gracefully they handle that. We check your realistic variant count early, because a range that looks modest as a product list can become tens of thousands of variants once fully expanded, and that materially affects which platform is sensible.

Yes. We build styling assistants, size and fit guidance, recommendation engines and visual search on current model stacks including Claude. Size guidance is usually the highest value application in fashion because fit uncertainty is the main cause of both abandoned baskets and returns, and reducing returns improves margin directly rather than only revenue. The honest caveat is that fit prediction improves substantially once the system has your own returns and exchange data to learn from, so the first version is a guide rather than a promise.

Yes. We connect payment providers, shipping carriers, marketplaces and tax systems so orders, fulfilment and settlements stay in step without manual work. The engineering that matters is in the failure paths rather than the connection itself: operations are made idempotent so a retried webhook cannot duplicate an order, failed syncs can be replayed instead of being lost, and discrepancies surface in a report rather than being discovered by a customer. Marketplace listings in particular need careful stock handling, since overselling across channels is the usual consequence of naive syncing.

Yes, and in fashion they are closely linked because the category is image heavy and mobile dominated. We build against the Core Web Vitals thresholds, Largest Contentful Paint under 2.5 seconds, Interaction to Next Paint under 200 milliseconds and Cumulative Layout Shift under 0.1 at the 75th percentile. Google and Deloitte measured a 0.1 second improvement lifting retail conversion by 8.4 percent and average order value by 9.2 percent. Most of the practical gain comes from image handling and reducing JavaScript rather than from redesigning buttons. We test the real purchase journey on mid range phones rather than only in a desktop browser at a narrow width, because the friction that actually costs orders tends to appear in checkout on a modest device over mobile data.

You do, completely. You receive clean, documented, well structured code and full ownership of everything we build, held in your own repositories from the first commit rather than transferred at the end. There is no proprietary framework you can only maintain through us and no arrangement where you keep paying to use what you commissioned. If you later bring the work in house or move to another agency you should be able to do so without asking our permission or unpicking a dependency on us.

Most fashion stores go live in six to fourteen weeks depending on range size, custom features and integrations. A focused theme build or straightforward replatform can be faster, while a headless or heavily customised store takes longer, and we share a clear timeline before starting. Product data preparation is the task most often underestimated: photographing, categorising and attributing a large range with full variant coverage frequently takes longer than the build, and it is usually your team’s time rather than ours, so we plan it explicitly.

Cost depends on scope, platform and the integrations and AI features involved. We scope every project to your goals and budget, then give a fixed proposal with no surprises, usually within 24 hours of your enquiry. In fashion the variables that move the number most are variant complexity and the number of systems to integrate, rather than the number of page templates. We will say when a requirement is disproportionately expensive relative to the revenue it can realistically produce, because deciding what to leave out is often the more valuable conversation.

That is the goal every time, and method decides the outcome. We map every existing URL to its destination as a one to one redirect plan rather than pointing old pages at the homepage, preserve titles, descriptions and structured data, and migrate product, customer and order data with reconciliation instead of a raw dump. Then we monitor Search Console daily for the first thirty days. A brief dip is normal around any migration; lasting damage comes from unmapped URLs, redirect chains and product pages quietly dropped in the rebuild.

Yes. We build iOS and Android shopping applications with personalised feeds, push notifications for drops and restocks, loyalty and fast checkout, connected to the same backend as your store so stock, orders and customers stay consistent across channels. The honest question we ask first is whether you have the repeat purchase frequency to justify one, because an application only earns its cost when customers return often enough to keep it installed. For many brands a fast mobile site plus email and messaging achieves more for less.

Yes, and it needs designing for rather than hoping. We architect for peak load with edge caching, queueing for checkout, and infrastructure that scales horizontally, then load test against realistic drop volumes rather than average traffic. Equally important is inventory logic that prevents overselling when hundreds of people add the last units simultaneously, because cancelling confirmed orders damages a brand more than the sale was worth. We also rehearse the drop beforehand, since discovering the ceiling during the event is the expensive way to find it.

Yes. Every build includes thirty days of post launch support, and beyond that we continue with monitoring, security patching, updates, new features and ongoing conversion and SEO work, so the store improves season after season. You get one senior team for the build and the growth rather than a handover into silence. For Magento and Adobe Commerce stores, scheduled patching matters more than teams assume: Sansec found roughly 75 percent of stores still unpatched a week after the CosmicSting fix, CVE-2024-34102, was published.

As a single connected problem, because they are one. We model size and colour variants properly at the data layer so stock, pricing and imagery stay correct per combination, present size guidance based on your actual garment measurements rather than a generic chart, and build a returns and exchange flow that captures the reason. That reason data is the valuable part: knowing that a particular style runs small lets you fix the guidance and the description, which reduces future returns rather than simply processing them more efficiently.