How it works
Make the machine understand.
A search engine doesn't browse your website. It tries to answer a question with it. Fitment data and structured data are how you hand it an answer instead of a page it has to guess at.
Layer one
Fitment:
what it fits.
Nobody walks in asking for part 51423-KZL-901. They ask whether it fits a 2021 PCX. Fitment data is the bridge between those two sentences, and in powersports that bridge is mostly missing.
The four-wheel aftermarket has ACES and PIES. Powersports fitment stayed fragmented, inconsistent and locked inside individual dealer systems — which is why a search for a specific bike and a specific job so often returns forum threads instead of parts.
- Normalised across the catalogueMake, model, year and trim reconciled across OEM and aftermarket part numbers.
- Supersessions resolvedWhen a part number is replaced, the fitment follows it instead of breaking.
- Current where it countsPriority on current-decade models, exactly where older datasets get thin.
- Maintained, not published onceAn update cadence and QA standard, because model years keep arriving.
Layer two
Structured data:
what it is.
Fitment tells a machine what a part fits. Structured data tells it what it's looking at in the first place — that this is a product, this is its price, this is whether you actually have one.
We run the two together. Markup on its own describes a listing that may be wrong; fitment on its own sits in a database nobody crawls. Paired, they make a page that answers a question correctly and can be trusted to keep answering it.
- Vehicle, Product, Offer, LocalBusinessThe markup types that let a crawler tell a unit, a part, a price and a store apart.
- Tied to live price and availabilitySo what a search engine shows matches what's on the floor when someone drives over.
- Templates by platformYour website vendor doesn't have to invent an implementation, and neither do you.
- Validated, not assumedTooling that checks the markup is present, correct and still there next quarter.
Layer three
AI readiness:
who answers
with it.
Be a known thing
Language models reason about entities — this brand, this model, this store. Ambiguity gets resolved in someone else's favour.
Be quotable
Fitment questions answered in a form a model can lift directly, rather than buried in a spec table image.
Be reachable
Clean feed endpoints and llms.txt-style surfaces, so retrieval finds current data instead of a cached guess.
We also measure it. Appearing in AI answers isn't a yes/no you can feel — it's something to monitor per store, per model, over time, the same way you'd watch rankings.
People ask an assistant first now. Your inventory is either in that answer or it isn't.
Why the data layer moved
What changes
From guesswork
to a legible
listing.
Nothing here is theoretical work you'll never see. Each layer produces something concrete on your pages and something you can check.
| What we deliver | What it changes | How you check it |
|---|---|---|
| Master fitment data | Your listings can be found by the machine somebody actually owns, not just the part number they don't know. | Fitment search on your own site |
| Part-number canonicalisation | One part is one part, across OEM numbering, aftermarket equivalents and supersessions. | Duplicate and orphan SKU counts |
| Structured-data deployment | Search engines read price, availability and fitment straight off the page. | Rich result and markup validation |
| AI-readiness work | Your store and your stock become citable inside AI-generated answers. | AI visibility score, tracked over time |
| Visibility reporting | You can see which in-stock units are digitally invisible, and what holding them costs. | The console, any morning |
| National demand channel | Stock with no local buyer gets a country-sized audience instead of a write-down. | Co-op listings and sell-through |
Common questions
The practical
answers.
- Do I have to change website vendors?No. The structured-data layer is built as templates per platform and deployed onto the site you already run.
- Who owns the data about my store?You do. Anything used to improve the shared fitment dataset is aggregated and anonymised.
- Is this just SEO with a new name?Traditional SEO tunes pages for ranking. This work makes your catalogue legible to machines that answer questions — a related job with different requirements, and both matter.
- What if my DMS data is a mess?Most are. Cleaning SKUs and reconciling part numbers is part of the work, not a prerequisite for starting it.
- Do I have to use all three products?No. The fitment and structured-data layer stands on its own. The console and the co-op are there when you want to see the gap and close it.