What Schema Should I Use for Replacement-Part Compatibility by Model Number?

Why does compatibility content do well in AI answers?

Compatibility questions are specific and factual: "Will filter X fit my [brand] model 4500B?", "What blade fits a [brand] RM-22 mower?", "Which battery replaces the one in model TX-310?". Assistants answering them need a source that states the match explicitly. Generic product pages rarely do, and forum threads are often uncertain or outdated. A page with a clear table, "fits models 4500, 4500B and 4510; does not fit 4500X", gives a direct, quotable answer.

What does the markup look like?

Schema.org defines isAccessoryOrSparePartFor as a pointer to another product, or multiple products, for which this product is an accessory or spare part. It defines isConsumableFor for consumables. A part page can describe itself and the models it fits:

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Brenlow HF-30 Replacement HEPA Filter",
  "brand": { "@type": "Brand", "name": "Brenlow" },
  "mpn": "HF-30",
  "gtin13": "0000000000000",
  "isConsumableFor": [
    { "@type": "Product", "name": "Brenlow AirPure 300", "model": "AP-300" },
    { "@type": "Product", "name": "Brenlow AirPure 300B", "model": "AP-300B" },
    { "@type": "Product", "name": "Brenlow AirPure 310", "model": "AP-310" }
  ],
  "offers": {
    "@type": "Offer",
    "price": "24.99",
    "priceCurrency": "GBP",
    "availability": "https://schema.org/InStock"
  }
}

Fictional products and placeholder identifiers. Use the part's real GTIN where it has one, and never invent one.

Notes:

• Use isConsumableFor for parts used up in normal operation, such as filters, cartridges and blades, and isAccessoryOrSparePartFor for replacement components and accessories.
• Give compatible models their own identifiers in model, and mpn or gtin if you know them, so the relationship is unambiguous.
• Link to your own pages for those models, if you sell them, using url or a stable @id.
• Keep the markup identical to the visible table.

How replacement-part and compatibility content can earn AI answers for ecommerce stores

The visible page does most of the work:

1. Put the answer in the first line: "The HF-30 filter fits AirPure 300, 300B and 310 air purifiers."
2. Add a compatibility table with brand, model name, model number, and notes such as production years, regional variants or required adapters.
3. List exclusions explicitly: "Does not fit AirPure 300X (use HF-35)." Exclusions answer "will this fit?" questions as much as inclusions.
4. Include every form of the model number customers use, such as "AP-300", "AP300" and "AirPure 300", since people type them differently.
5. Explain how to find the model number on the appliance, with a photo and a text description.
6. Add a "check compatibility" search for large catalogues, but keep the full list in the HTML too. Script-only lookups are invisible to crawlers.
7. Give each part its own page; do not bury many parts in one table without individual URLs.
8. Cross-link: from each appliance page to its compatible parts, and from each part to its appliances.

How to fix wrong specifications in AI answers is covered in why AI models give wrong product specs for your brand.

Should you sell "compatible" or third-party parts differently?

Yes, in how you describe them. Many stores sell both original parts and compatible alternatives. Be precise:

• Say clearly which is which: "Original [brand] part" or "Compatible replacement made by [manufacturer], not [brand]".
• Use the original manufacturer's name only to identify compatibility, such as "fits [brand] AP-300". Do not imply the part is made or endorsed by that brand.
• State any differences: capacity, filtration grade, warranty implications or certification.
• Explain warranty effects honestly where the appliance maker's warranty says something about third-party parts.

Assistants asked "is a compatible filter as good as the original?" look for exactly this kind of plain comparison. A page that states differences openly is more credible than one that implies the parts are identical. The same issue arises with printer cartridges, as covered in why AI assistants recommend original HP toner but not compatible cartridges.

How should model number variants be handled?

Model numbers are messy. Customers type them with and without hyphens, with or without suffixes, and sometimes with regional codes. List each variant you know in the table, grouped under one model where they are interchangeable. Where a suffix changes compatibility, give it its own row with a clear note. Search on your site should normalise variants, so "AP300" finds "AP-300". But the full list must also appear in the HTML, because crawlers do not use your site search.

What about feeds and marketplaces?

Shopping answers draw on product feeds. Merchant Center's conversational attributes, intended for AI Mode, include related_product, which links a part to other products in your feed as an accessory or required part, and question_and_answer, which can carry a fit question such as "Does it fit the AirPure 300B?" with its answer. For appliance models you do not sell, list the key compatible model numbers in the description, where the rules allow. Automotive parts sellers often manage fitment through industry data standards: ACES for fitment and PIES for product information, maintained by the Auto Care Association. Marketplaces use these or their own compatibility systems. Keep feed and marketplace data consistent with your site, so assistants do not find conflicting fitment lists.

How do you keep compatibility data accurate?

• Maintain one master fitment table per part, with a source for each match, such as the manufacturer's parts list, your testing or customer confirmation.
• Generate the page table, the markup and the feed text from that master.
• Record changes with dates, especially when a new model is added or a revision breaks compatibility.
• Watch returns and support tickets for "did not fit" reasons, and correct the data quickly.
• Mark uncertain matches honestly, such as "reported compatible by customers; not tested", or leave them out.

What might an illustrative case look like?

Consider an illustrative online store selling vacuum cleaner parts that listed compatibility as a comma-separated string inside a collapsed tab loaded by JavaScript. AI answers to "which filter fits [brand] model V-240?" cited a forum thread and a competitor's page. The store rebuilt its part pages with a first-line compatibility statement and a visible table of models and model number variants. It listed exclusions and added isConsumableFor markup generated from the same data. It also added a guide to finding the model number. Within two months, assistants cited its part pages for model-specific questions, and "did not fit" returns fell.

What do people ask about compatibility markup?

Will Google show compatibility in search results?

Google does not document a rich result for these properties. The markup helps systems that read it; the visible table helps everyone.

Should we create pages for each appliance model?

Yes, for models people search for, listing their compatible parts. They answer "parts for [model]" questions directly.

How many compatible models can one page list?

As many as are true. Very long lists work best in a sortable, crawlable table with a search box.

What if the manufacturer's compatibility list is wrong?

Rely on your own tested data, note the discrepancy, and tell the manufacturer if you have a relationship.