If you sell auto parts online, two acronyms quietly decide whether your catalog helps customers or frustrates them: ACES and PIES. These are the data standards published by the Auto Care Association, and together they form the backbone of nearly every serious auto parts ecommerce operation in North America. ACES tells shoppers what fits their vehicle. PIES tells them what the product actually is. Get both right and your store feels effortless. Get either wrong and you generate returns, chargebacks, and abandoned carts.
This guide breaks down what ACES and PIES do, how they differ, and how they work together to power fitment-driven ecommerce on platforms like Shopify.
What are ACES and PIES?
ACES (Aftermarket Catalog Exchange Standard) is the fitment standard. It maps a part to the specific vehicles it fits using a structured vocabulary of year, make, model, submodel, engine, and other qualifiers. When a customer selects “2018 Honda Accord EX 1.5L Turbo” and sees only the parts that match, ACES data is doing that work behind the scenes.
PIES (Product Information Exchange Standard) is the product content standard. It describes the part itself: descriptions, dimensions, weights, package quantities, UPC codes, hazardous material flags, digital asset links, pricing references, and hundreds of other attributes. PIES is what fills out your product page once ACES has confirmed the part belongs there.
A useful way to remember the split: ACES answers “does it fit?” and PIES answers “what is it?” Both are XML-based standards maintained by the Auto Care Association’s Technology Standards Committee, and both are versioned and updated regularly to keep pace with new vehicles and product categories.
Why auto parts ecommerce needs both standards
Selling auto parts is fundamentally different from selling apparel or general merchandise. A t-shirt fits based on size preference. A control arm fits based on hard engineering constraints, and installing the wrong one is dangerous, expensive, or both. That difference is why the industry built dedicated data standards decades ago and why modern ecommerce still depends on them.
Here is what each standard delivers for an online store:
- ACES powers vehicle filtering. It enables the year/make/model dropdown, “verify fitment” widgets, and compatibility checks at checkout. Without clean ACES data, a fitment filter either returns nothing or returns wrong results.
- PIES powers product pages and search. Rich attributes feed titles, specs tables, faceted navigation, and the structured data that search engines read. Complete PIES content is also what makes your listings syndicate cleanly to marketplaces.
Stores that treat these as optional tend to rely on manual spreadsheets, which drift out of date within months. Stores that treat ACES and PIES as their source of truth can scale to hundreds of thousands of SKUs without the catalog collapsing under its own weight.
ACES vs PIES: the practical differences
The two standards overlap in purpose but almost never in content. Here is how they compare across the dimensions that matter for an ecommerce team:
Scope
ACES covers the relationship between a part and a vehicle. A single part number can have thousands of ACES fitment rows if it fits many vehicles. PIES covers the part in isolation and typically has one record per part number, regardless of how many vehicles it fits.
Data volume
Because ACES describes every vehicle a part fits, ACES files are usually far larger and more repetitive than PIES files. A catalog of 5,000 parts might generate a PIES file with 5,000 records and an ACES file with several hundred thousand fitment rows.
Update cadence
ACES data changes as new model years arrive and as coverage expands. PIES data changes when packaging, pricing references, digital assets, or descriptions are updated. In practice, both need periodic refreshes, and syncing them on a schedule beats one-time imports.
Where it shows up
ACES lives in your fitment filter and compatibility messaging. PIES lives in your product title, description, specs, images, and search facets. A shopper interacts with ACES before they ever land on a product page and with PIES once they arrive.
How ACES and PIES flow into a Shopify store
Shopify was not originally designed for vehicle fitment, so bringing ACES and PIES into it takes a deliberate approach. The typical pipeline looks like this:
- Source the data. You receive ACES and PIES files from your suppliers, a data provider, or the manufacturer directly. These arrive as XML or as flattened CSV exports derived from the standards.
- Map PIES to products. Product-level attributes become Shopify product fields and metafields: title, body, vendor, part number, UPC, weight, and category-specific specs.
- Map ACES to fitment records. Vehicle fitment gets stored separately, usually in metafields or a dedicated fitment datastore, because a single product maps to many vehicles.
- Expose fitment through a filter. A vehicle fitment app reads the ACES relationships and renders the year/make/model search that customers actually use.
The tricky part is steps three and four. Native Shopify has no concept of a many-to-many vehicle relationship, so a purpose-built fitment layer is what turns raw ACES data into a working shopping experience. This is exactly the gap that a vehicle fitment app like Aculogi is built to fill, translating ACES fitment tables into a fast year/make/model filter without forcing you to rebuild your catalog by hand.
Common mistakes when working with ACES and PIES
Teams new to these standards tend to hit the same avoidable problems. Watching for them saves weeks of cleanup later.
- Treating flattened CSVs as complete. Many providers export a simplified CSV that drops qualifiers like engine or submodel. That simplification causes false fitment matches. Keep the granularity ACES provides.
- Mixing the two standards into one file. ACES and PIES describe different things and should stay in separate pipelines. Merging them prematurely tends to duplicate fitment rows across every product attribute.
- Ignoring version differences. A supplier on an older ACES version may use vehicle IDs that no longer match current data. Reconcile versions before importing or fitment will silently break.
- Skipping data validation. Both standards have validation rules. Importing unvalidated files leads to parts that fit “everything” or “nothing,” and customers notice fast.
Do you need the full standards, or a simplified version?
Not every store needs to ingest raw XML. Smaller catalogs often work fine with a well-structured subset of ACES fitment and a handful of key PIES attributes. Larger catalogs, or stores that syndicate to marketplaces, benefit from staying as close to the full standards as possible because that is what downstream partners expect.
The right answer depends on where your data comes from and where it needs to go. If your suppliers already provide clean ACES and PIES, preserving that structure protects you as you grow. If you are assembling fitment manually, a fitment app that accepts structured imports will keep you far more consistent than spreadsheets ever will.
Frequently asked questions
What is the difference between ACES and PIES?
ACES is the fitment standard that maps a part to the vehicles it fits using year, make, model, and engine data. PIES is the product content standard that describes the part itself, including dimensions, descriptions, UPCs, and digital assets. ACES answers “does it fit,” while PIES answers “what is it.”
Do I need both ACES and PIES for an auto parts store?
For most auto parts ecommerce operations, yes. ACES powers the vehicle fitment filter that helps customers find the right part, and PIES fills out accurate product pages and search. Using only one leaves either your filtering or your product content incomplete.
Can Shopify use ACES and PIES data directly?
Not natively. Shopify has no built-in vehicle fitment model, so ACES fitment relationships are usually stored in metafields or a dedicated datastore and surfaced through a fitment app. PIES attributes map more directly to Shopify product fields and metafields.
How often should ACES and PIES data be updated?
ACES should be refreshed as new model years and coverage arrive, and PIES whenever packaging, descriptions, pricing references, or assets change. Scheduling regular syncs is more reliable than one-time imports, since both datasets drift over time.
What happens if fitment data is wrong?
Incorrect ACES data causes parts to appear compatible with vehicles they do not fit, leading to returns, chargebacks, and lost trust. Clean, validated fitment data is what keeps the shopping experience accurate and reduces costly mistakes.