WEBSITE MIGRATION

Your Parts Store Ships Wrong Fitments. We Fix Your ACES/PIES Stack.

If you're an auto parts operator watching chargebacks pile up from bad fitment data, you've hit the ceiling of spreadsheet-based catalogs.

Book a 30-min call Get Your Fitment Audit
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WEBSITE MIGRATION AT A GLANCE
  • Next.js
  • Supabase
  • Vercel
  • Algolia
  • Shopify Hydrogen
  • PostgreSQL
  • 95+LIGHTHOUSE AVG
  • 12+ yrsSENIOR-LED
  • Fixed feeNO SCOPE CREEP
  • 200+PROJECTS SHIPPED
CLUTCH 5.0 VERIFIED

Overview — 01

We build auto parts eCommerce stores with native ACES/PIES data integration, Year/Make/Model search, and VIN lookup -- so every customer finds the exact part that fits.

ACES/PIES Fitment Integration

ACES (Aftermarket Catalog Exchange Standard) defines which parts fit which vehicles. PIES (Product Information Exchange Standard) carries the product attributes, pricing, and digital assets that surround those parts. A correctly implemented ACES/PIES stack connects your supplier data feed to your storefront's Year/Make/Model and VIN lookup so fitment validation happens at search time, not after a return label is printed.

The gap — 02

What is holding your current website back?

Common gaps we find in nearly every audit.

Customers order the wrong part because your Year/Make/Model filter is driven by a manually maintained spreadsheet that lags behind supplier catalog updates.
Risk: Each wrong-fitment order costs you the return shipping, a restocking fee that suppliers rarely waive in full, and a customer who will not return.
Your current platform stores fitment data as tag strings or custom fields, so there is no structured vehicle database to query against and no VIN decode path.
Risk: Without a validated vehicle database, even a small catalog update silently introduces fitment gaps that only surface when a chargeback arrives.
Supplier ACES data arrives as flat files on irregular cycles and your team manually imports them into a system that was not designed to handle vehicle application records at scale.
Risk: Manual import cycles mean your live catalog is always behind the supplier's current fitment truth, creating legal exposure if a safety-critical part ships to the wrong application.

Safeguards — 03

How we build this right

Every safeguard, built in from Day 1.

ACES Schema Validation

Every ACES file ingested by your store is validated against the current ACES XSD schema before it touches your live catalog, preventing malformed vehicle application records from reaching customers.

PIES Attribute Completeness Checks

We enforce required PIES segments — pricing, package dimensions, hazmat flags — at import time so your product records satisfy marketplace channel requirements and carrier rating rules.

VIN Decode Audit Trail

Each VIN lookup is logged with the decoded year, make, model, engine, and trim so you have a timestamped record of what fitment data was served to a customer at the moment of purchase.

Scope — 04

What we build

Purpose-built features for your industry.

Structured Year/Make/Model Search

A vehicle selector backed by a normalized vehicle database, not tag fields, so drill-down filtering returns only parts with confirmed fitment records for the selected application.

VIN Decode at Add-to-Cart

Customers enter a VIN and the store decodes it against a live vehicle database, confirms fitment before the item enters the cart, and stores the decoded vehicle against the order record.

Automated ACES/PIES Feed Ingestion

Supplier flat files or API feeds are ingested on a scheduled cycle, diffed against your current catalog, and published only after schema validation passes, keeping your live fitment data current without manual intervention.

Fitment Conflict Reporting

A back-office dashboard surfaces vehicle application conflicts, orphaned part numbers, and PIES attribute gaps before they reach customers, giving your catalog team a prioritized work queue rather than a reactive inbox.

Stack — 05

Built on a modern, secure stack

Next.jsSupabaseVercelAlgoliaShopify HydrogenPostgreSQLACES XMLPIES XML

Process — 06

Our development process

From discovery to launch. Quality at every step.

01

Catalog and Feed Audit

1 week

We ingest your current supplier ACES files, map your existing fitment data structure, and produce a gap report showing schema errors, missing vehicle applications, and PIES attribute deficiencies before a line of code is written.

02

Vehicle Database and Fitment Engine Setup

2 weeks

We deploy a structured vehicle database normalized to ACES standards, wire it to your Year/Make/Model selector and VIN decode endpoint, and validate fitment lookup accuracy against a sample of your top-selling SKUs.

03

Feed Pipeline and Storefront Integration

2 weeks

Automated ingestion pipelines are configured for each supplier feed format, schema validation rules are enforced at the pipeline boundary, and the fitment engine is connected to your product display, search, and cart layers.

04

Fitment QA and Catalog Team Handoff

1 week

We run fitment accuracy testing across vehicle application edge cases, document the conflict reporting dashboard for your catalog team, and deliver runbooks for onboarding new supplier feeds without engineering involvement.

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Related resources — 07

Solution Magento to Nextjs Auto Parts Ecommerce Solution Auto Parts Ecommerce Platform Solution Auto Parts Ecommerce Development Solution Auto Parts Ecommerce Website Development Solution Bicycle Ebike Parts Ecommerce Development Solution Marine Boat Parts Ecommerce

Questions — 08

Frequently asked questions

ACES (Aftermarket Catalog Exchange Standard) defines which parts fit which vehicles -- year, make, model, engine, trim. PIES (Product Information Exchange Standard) handles the product side: dimensions, images, pricing, attributes. Together they're the backbone of automotive aftermarket data exchange in North America, maintained by the Auto Care Association. If you're selling auto parts seriously, you're working with these standards whether you know it or not.
Cascading dropdown filters query your ACES-mapped fitment database directly. Pick a year, and only valid makes show up. Pick a make, and it narrows to matching models, then engine and trim. The result is a list of parts with confirmed fitment for that exact vehicle configuration -- typically in under 200 milliseconds, even across large catalogs.
Yes. We integrate VIN decoding APIs that pull year, make, model, trim, engine, and transmission from a 17-character VIN. That data maps to your ACES vehicle applications, auto-fills the fitment filter, and surfaces only compatible parts. It's genuinely useful on model years where the same vehicle shipped with multiple engine or transmission options -- which is more common than most people realize.
We use a headless architecture with PostgreSQL handling the fitment database and a dedicated search index -- Algolia or Meilisearch -- for real-time faceted filtering. The Next.js frontend serves static product shells and loads fitment data dynamically. Page loads stay under 2 seconds regardless of catalog depth.
Yes. We build automated feed pipelines that export your catalog in the exact format Amazon's Automotive Part Finder and eBay Motors' fitment structure require. When you add SKUs or vehicle applications, updates push to your marketplace listings automatically -- no manual exports.
A full build -- ACES/PIES integration, YMM search, VIN lookup, and marketplace syndication -- typically runs 10 to 11 weeks from data audit to launch. Simpler builds without marketplace feeds can ship in 7 to 8 weeks. The biggest variable is catalog size and how clean your existing fitment data is when we get started.

More solutions — 09

Explore related industries

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If you're running a multi-million SKU auto parts catalog, you've watched mobile sessions die at the filter step -- Magento can't keep up.

Your Auto Shop Loses $4,800 Every Month You Can't Book Online

If you're a shop owner still answering the phone at 7pm to schedule oil changes, you're bleeding revenue to the dealer down the street with instant booking.
Need enterprise scale?

200+ employee company? Complex multi-tenant, auction, or multi-location requirement? We have a dedicated enterprise capability track.

View Enterprise Hub

Get started — 10

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