OVERVIEW
What Are Automotive Catalog Data Standards?
In the automotive aftermarket, data accuracy determines sales accuracy. ACES and PIES serve as the industry's structured language for communicating vehicle fitment and product information.
ACES handles vehicle-to-part mapping, ensuring every part correctly aligns with the vehicles it fits.
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PIES manages product details — attributes, pricing, packaging, and digital assets that enrich your listings.
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Together they keep catalogs consistent, interoperable, and up-to-date across every channel.
INDUSTRY ADOPTION
Catalogs built on ACES and PIES are recognized across suppliers, warehouses, distributors, retailers, and digital storefronts.
ACES 5.0
Current fitment schema
PIES 8.0
Current product schema
AUDIENCE
Who Needs Automotive Catalog Data Standards?
These standards are essential for manufacturers, private brands, distributors, and suppliers that want their products accurately represented across lookup platforms and eCommerce channels.
Fewer Returns
Accurate fitment data means the right part reaches the right customer, reducing costly returns and disputes.
Stronger Partnerships
Distributors trust suppliers whose data arrives clean, validated, and standards-compliant every time.
Search Visibility
Enriched product data improves how parts appear in search-driven lookup tools and eCommerce platforms.
FITMENT STANDARD
ACES Explained: The Foundation of Vehicle Fitment
ACES (Aftermarket Catalog Exchange Standard) defines how vehicle application data is structured and shared across the supply chain. When your data aligns with ACES, you eliminate mismatches, avoid costly returns, and make your catalog universally compatible.
BaseVehicleID — the unique vehicle identifier tied to VCdb
VCdb & Qdb — databases defining makes, models, years, engines, and qualifiers
XML Schema — a consistent structure for exchanging application data
FITMENT STANDARD
PIES Explained: Structuring Product Data for Distribution
While ACES defines what a part fits, PIES describes the part itself. PIES structures product-level data so it can be distributed, enriched, and maintained consistently across channels.
Product attributes — material, size, performance specs
Pricing and packaging data
Digital assets — images, videos, PDFs
Regulatory and compliance information
COMPARISON
ACES vs PIES: What's the Difference?
Although they work together, ACES and PIES solve different problems. ACES makes sure the part fits. PIES makes sure it sells.
STRATEGIC VALUE
Why ACES and PIES Matter More Than Ever
Catalog data has evolved from a back-office requirement into a competitive advantage. In an increasingly digital aftermarket, buyers depend on search-driven lookup tools to identify the right part quickly.
Channel Relationships
Standardized data strengthens distributor trust and makes onboarding with new partners faster.
Product Visibility
Consistent, enriched data ensures your products appear in searches — even when competitors' don't.
Faster Time-to-Market
Automated standards compliance means new applications reach buyers sooner with fewer errors.
IMPLEMENTATION
How to Implement Modern Catalog Data Standards
Managing catalog standards effectively requires more than exporting XML files. Here's the process — and where most companies struggle.
01
Import & Validate
Import data from manufacturers and standards bodies, then validate structure against the latest schemas.
02
Align & Enrich
Align fitment and product data to prevent coverage gaps. Enrich listings with assets and attributes.
03
Distribute & Maintain
Distribute validated updates reliably to partners and marketplaces. Keep everything in sync.
Common Struggles
Out-of-sync ACES and PIES files
Manual updates that introduce errors
Missed schema updates causing validation failures
How DataPoint Solves This
Automated validation against latest schemas
Centralized ACES & PIES management
Intelligent gap analysis for coverage
Scalable tools that grow with your catalog
LATEST VERSIONS
ACES 5.0 & PIES 8.0 Schema Updates
The introduction of ACES 5.0 and PIES 8.0 brought major improvements to structure, validation, and data enrichment capabilities.
Enhanced XML schema structures
Expanded VCdb support for new vehicle types
Additional digital asset handling in PIES
Improved positional data accuracy
FAQ
Frequently Asked Questions
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