We engineer the commerce platforms the automotive aftermarket runs on
Parts commerce platforms for US, UK and European distributors and retailers, built and modernized
for confirmed fitment, live stock, and same-day dispatch
Your platform loses orders in five specific places
None of them is on the storefront. Each sits below it, in the catalog data, the stock layer, or the search index.
| What is broken | What causes it | What it costs you |
|---|---|---|
| No fitment validation before checkout | Catalog and vehicle data are not cross-referenced at the platform level | Wrong-part returns and abandoned baskets |
| Stock updated in batches, hours apart | Inventory and order systems are not connected in real time | Orders confirmed against stock that is already gone |
| Search that demands a part number | The index answers to exact SKUs, not to how buyers describe parts | Buyers without a part number purchase elsewhere |
| A taxonomy that cannot hold EV and ADAS parts | The category structure predates the categories now growing fastest | Locked out of the fastest-growing segment |
| The site slows or fails under peak load | The architecture was never tested against real trading conditions | Failure lands during your highest-revenue hours |
The same five gaps, closed on three
live aftermarket platforms
GSF Car Parts, Euro Car Parts, and Wemoto. One engagement each, a verified number attached to every claim, and every
figure measured on a running store, not modeled on a slide.
Revenue up 140 percent after the replatforming, on traffic it already had
GSF Car Parts runs a 400,000 SKU catalog across a national branch network. The platform was taking orders and suppressing more: checkout took 15 seconds, 2.16 percent of searches returned nothing at all, and product data refreshed on a 16-hour overnight cycle. Every one of those was a revenue leak hiding in plain sight.
We rebuilt the platform on Adobe Commerce, rebuilt parts search on Adobe Live Search, stabilized the Akeneo product data integration, and put fitment validation directly in the buying path, so the add to basket action stays closed until the part is confirmed compatible with the customer's vehicle.
140%
Revenue growth after the overhaul
3-4s
Checkout duration, down from 15 seconds
0.73%
Zero-result search rate, down from 2.16 percent
17min
Product data export cycle, down from 16 hours
40%
Home delivery revenue share, up from 20 percent
1200
Concurrent users at peak load periods
Euro Car Parts (LKQ)
A custom platform built from the ground up in 2009 and modernized continuously since, across 60 integration modules, click and collect, same-day delivery, and a later move to Adobe Commerce Cloud with the business trading throughout.
From roughly £100,000 in annual online revenue at the start of the engagement
to the IRUK Top 50 within two years, growing to three times the size of its nearest
online competitor over the partnership period.
Wemoto
One global platform for motorcycle parts replacing a 15-year-old stack: Solr-based search with custom aftermarket fitment rules, a custom point of sale, Stripe integration, and more than four million product associations migrated across six countries.
A 70 percent improvement in site performance and zero loss of SEO visibility,
measured through the multilingual migration, on a store now serving roughly
10,000 orders a month.
A storefront refresh cannot repair a
data-layer fault
When orders slip, most agencies reach for what they can see: a new theme, an off-the-shelf search tool, a faster checkout page. It looks like progress. It is redecoration.
Fix the symptom, keep the fault
A plugin cannot validate fitment, because fitment lives in how catalog and vehicle data are cross-referenced. A faster page cannot fix stock that was wrong when the page loaded. The returns keep coming, now behind a nicer interface.
Repair the system the fault lives in
We treat each of the five as a system failure and repair it where it lives: the catalog, the inventory feed, the search index, and the architecture underneath all of them.
Four engineering layers, applied in the order
the architecture demands
Commerce Engineering delivered through the Growth Engineering method. You cannot forecast demand from data you never captured. Each
layer ships into production before the next begins, and trading never pauses for the build.
1 Modernize the foundation
The work that makes everything above it possible.
- Monolith re-architected to a composable, headless build on Adobe Commerce Cloud, proven at UK aftermarket scale
- Supplier feeds cleaned and structured into one catalog source
- API-first integration, so any ERP, WMS, or distributor feed connects cleanly
- A release pipeline that ships updates with zero downtime
- Page loads and catalog processing brought to operational standard
2 Instrument the data
The platform becomes observable, then learnable.
- Real-time inventory sync across every warehouse, retiring the nightly batch for good
- One data layer running B2B and B2C together, with zero duplication
- Vehicle ownership tracked against the customer record, so service cycles become repeat revenue
- Catalog and stock connected directly to the marketplaces that matter
3 Orchestrate the buying path
The platform starts acting on what it knows.
- Fitment checked by VIN, registration, or make and model, with the basket held until the part is confirmed compatible
- Natural language search built around how buyers describe parts, with OEM to aftermarket numbers matched at query time
- A headless CMS that frees marketing from the development queue
- Vehicle details that persist across sessions, never re-entered or lost
4 Automate the commercial engine
The platform starts improving itself.
- Pricing that moves with demand, cost, and competitors
- Demand forecasting built from order history, fleet trends, and market shifts
- Fitment-based bundles that lift order value on high-value parts
- Image lookup for damaged or unidentified parts
- One commercial view, from the warehouse floor to the boardroom
The capabilities that close each of the five gaps
Fitment accuracy and catalog structure
- Parts verified by VIN, registration, or make and model before checkout
- Supplier data cleaned and structured into one searchable catalog
- Every vehicle iteration cross-referenced, so nothing slips through
- A taxonomy built to hold EV and ADAS parts alongside the traditional range
- AI-matched OEM numbers, mapped to their aftermarket equivalents
Inventory and order management
- Real-time sync across every warehouse, with stock figures updated the moment they change
- Full multi-location visibility, with orders routed and allocated by rule
- Same-day dispatch and click and collect built into fulfillment
- Channel-level stock accuracy held everywhere it is shown, including your busiest hours
Search and parts discovery
- Natural language queries matched to how buyers describe parts
- Vehicle details carried across sessions automatically
- OEM to aftermarket part numbers resolved at query time
- Image lookup for damaged or unidentified parts
- Relevance that sharpens the more your catalog is used
Platform modernization and re-architecture
- Monolith to composable, headless architecture
- API-first design, so any ERP, WMS, or supplier feed connects cleanly
- Performance engineering measured against page load and catalog processing targets
- Updates shipped continuously, with zero disruption to live trading
- Adobe Commerce Cloud, delivered by a Recognized Adobe Solution Partner
Pricing, data, and commercial intelligence
- Pricing adjusted automatically to demand, cost, and competitor movement
- Forecasting built from order history, fleet trends, and market shifts
- Bundles matched to the vehicle on the order to lift average order value
- One commercial view across every channel and warehouse
Multi-channel commerce and content operations
- B2B and B2C served from one data layer, with zero duplication
- Catalog and stock connected directly to the marketplaces that matter
- A headless CMS that lets marketing publish without a development ticket
- Built to hold catalogs above one million SKUs without degradation
- Vehicle ownership data turned into service-cycle repeat revenue
Built for the automotive
aftermarket
The standards, natively
ACES, PIES, TecDoc, MAM, VIN and VRM lookup, and OEM to aftermarket cross-referencing ship inside every build we deliver, live across the UK and US today.
Proven at catalog scale
We have run catalogs above one million SKUs through national branch networks and seasonal demand spikes without performance degradation.
One team, start to finish
Platform engineering, AI and Data Engineering, ERP integration, CMS, and ongoing support, delivered without handoffs. Recognized Adobe Solution Partner, Akeneo Partner, and AWS Select Tier Services Partner.
The questions skeptical buyers ask
before they commit
How does fitment validation work before checkout?
We build VIN, registration, and year, make, and model lookup into the catalog layer itself, not into a plugin sitting on top of it. Every part is checked against the buyer's specific vehicle, including cross-referenced iterations, before the order is placed. The add to basket action stays held until compatibility is confirmed.
Can real-time inventory connect multiple warehouses and distributor feeds?
Yes. We connect every warehouse and distributor feed into one event-driven stock layer, so the availability shown at checkout reflects the shelf as it stands now, not an overnight refresh from hours earlier. The same layer holds accuracy across marketplaces and branch networks through peak trading, when stale stock costs the most.
How long does an aftermarket re-platform take, and does trading stop during the build?
Trading never stops. Delivery is layered, and each layer ships into production before the next begins, so there is no single cutover date and no downtime window. Euro Car Parts moved to Adobe Commerce Cloud with the store live the entire time. A distributor cannot go dark while its platform is replaced, so we do not ask yours to.
Can our existing ACES, PIES, TecDoc, or MAM data be migrated without a manual rebuild?
Yes. We work with the catalog data you already hold and structure it into one clean, unified source, rather than demanding it all be re-keyed by hand first. Search, fitment logic, and OEM cross-referencing are then built on top of that source, so the investment in your existing data carries forward instead of being written off.
What if our problem is search or catalog data rather than the platform?
Then we will say so, in writing, before you commit to anything larger. Every engagement opens with an assessment of the platform, the catalog, and the integrations, and that review sometimes concludes that a search rebuild and a catalog cleanup on your existing platform gets you there faster and cheaper than a migration. You keep the findings either way.
Tell us where the orders
are going
Search that returns nothing, stock that was gone before checkout, or fitment
discovered at the returns desk. Tell us which one it is, or let the assessment find
out, and we will tell you honestly whether it needs a re-platform or something
smaller.
