Eight checks you can run yourself, how to rank what they find by what it actually costs you, and the questions to ask anyone who tells you their data is verified. Including us.
There are only two ways fitment data fails
Everything below is a way of measuring one of these two, and they are not the same problem.
Over application. The part claims vehicles it does not fit. This is the returns driver. It costs you freight, refunds, and the buyer's trust, and it is invisible until the parts come back.
Under application. The part is missing vehicles it does fit. This is the visibility driver. It costs you sales you never knew you were eligible for, and it is invisible forever unless you go looking.
Most catalogues have both, in different parts of the range. Any audit that produces a single quality percentage has averaged away the only distinction that matters, because the fixes are opposite: over application means removing applications, under application means adding them.
The eight checks
In the order worth running them. The first six need nothing but your own data and a spreadsheet.
1. Base vehicle coverage. What share of your applications resolve to a valid Base Vehicle ID in the Vehicle Configuration Database? Anything that does not resolve is not fitment, it is a note. Count it.
2. Configuration depth. Of the applications that do resolve, how many stop at year, make and model, and how many carry submodel and engine? A brake pad that varies by engine and is published without an engine base is over applied by construction.
3. Applications per part, distribution not average. Sort your parts by application count and look at both tails. Parts with one or two applications are usually under applied. Parts near the top of the range are usually over applied. The average tells you nothing; the shape tells you where to look.
4. Part type integrity. Does every part carry a valid Part Terminology ID from the Product Classification Database, or are there free text descriptions sitting where a coded value belongs? Free text does not travel to a receiver.
5. Qualifier misuse. Search your notes fields for the words "except", "with", "without", "up to", "from" and any date. Every hit is a qualifier that should be coded against the Qualifier Database and is currently invisible to every system downstream.
6. Duplicate and overlapping applications. The same part against the same vehicle twice, or a broad application that already contains a narrower one. Both inflate your coverage number without adding a single sale.
7. Supersession integrity. Are you publishing against numbers that have been replaced? A superseded number usually drags its old vehicle list with it, which is a quiet and common source of wrong fitment.
8. Receiver validation. Run a real file at a real receiver before you believe any of the above. A file can be valid ACES and still be rejected, and the receivers tell you why in detail.
How do I turn a wall of errors into a list I can act on?
Rank by vehicles in operation, not by error count.
A missing application on a platform with four million vehicles on the road is worth more than two hundred missing applications across vehicles nobody drives any more. Sorting your gaps by the size of the parc turns an unusable error log into a commercial priority list, and it is the single most useful thing you can do with an audit result.
The same logic applies in reverse for over application. An over applied part on a high volume platform is generating returns right now. An over applied part on a rare vehicle is a rounding error. Fix the first, schedule the second.
What does a receiver check that the standard does not?
Its own rules, on top of a valid file. Walmart Marketplace, for instance, states that "the Part Terminology ID, AAIA Brand ID and Manufacturer Part number tagged to the item must match the ACES file exactly for fitment to be enabled", including spaces, hyphens and underscores. It rejects files for a missing Part Type ID, a missing base vehicle ID or part number, or invalid vehicle information.
So a hyphen in your item attributes and not in your ACES file is enough to disable fitment on an otherwise perfect record. Every additional channel adds a reconciliation of this kind, and the errors it surfaces are usually not the errors your internal audit found.
What should "verified" mean when a vendor says it?
It is the most overused word in this market and it is almost never defined. Ask these five questions of anyone quoting a large number, and ask them of us too.
Verified against what? A manufacturer feed, a reference database, a competitor's catalogue, or an internal rule? These are very different claims.
At what depth? A relationship verified to year, make and model is not the same object as one verified to an engine configuration, even though both count as one in a headline.
How is a relationship counted? One part against one base vehicle, or one part against every submodel and engine combination underneath it? The second inflates the number by an order of magnitude without adding information.
How old is it? The vehicle database changes with every model year. A number with no as of date is a number from an unknown year.
What happens when sources disagree? A provider who has never had two sources conflict has not checked.
We publish a figure of 1.17 billion verified vehicle to part relationships, and those questions apply to it exactly as they apply to anyone else's. Larger competitors publish larger numbers. Counting rules differ enough between vendors that comparing headline totals tells you almost nothing, which is why the questions above are more useful than the figure they are asked about.
How do I audit a provider before I buy?
Do not ask for their coverage number. Give them a coverage test.
Take fifty part numbers from your own catalogue, chosen deliberately rather than at random: ten common wear items, ten from your worst selling range, ten European or diesel where fitment turns on engine code, ten private label or house brand parts with no manufacturer number to match on, and ten you already know are wrong. Ask what they return for each.
The last two groups are the whole test. Any provider handles the easy forty. What separates them is what happens where there is no part number to look up, and whether they surface the ten you know are broken or quietly repeat them back to you.
Which of these can I do this week?
Export your catalogue with one row per application, not one per part. Then, in order: count the rows that do not resolve to a base vehicle, count the ones with no engine where the part varies by engine, sort by applications per part and look at both tails, and grep your notes fields for qualifier words.
Four numbers, one afternoon, no vendor. They will tell you whether you have a small problem or a large one, and that is enough to decide what to do next.
Or send an extract and we will run it
A catalogue export with one row per application is enough. We return the eight checks scored, your gaps ranked by vehicles in operation rather than by error count, and the over applied and under applied lists kept separate, because they are different jobs.
No charge, and the report is yours whether or not you do anything with us. If the answer is that your data is fine, we would rather tell you that than sell you a project.
Auto Care Association, for the reference databases these checks run against: the Vehicle Configuration Database, the Product Classification Database, the Product Attribute Database, the Qualifier Database and the Brand Table.
Walmart Marketplace, quoted on exact field matching and on the reasons an ACES file is rejected.