How do I make my parts listings show up in ChatGPT and other AI assistants?

Why this matters now

Shoppers increasingly ask an AI assistant before they search a store. Traffic from generative AI tools to U.S. retail sites rose 693% in the 2025 holiday season (Adobe Analytics). For parts, the question is almost always some form of “does this fit my machine?”. The listing that answers it gets recommended.

How an AI assistant answers “does this part fit?”

When a shopper asks ChatGPT, Perplexity, Claude or Google's AI features about a part, the assistant searches the web, reads the pages it can reach, and answers from what those pages say. It can only recommend your part if three things are true:

1. Its crawler is allowed to fetch your page, and the content is in the HTML rather than loaded later by JavaScript.
2. The page identifies the part unambiguously, so the assistant knows it's the same part the shopper means.
3. The page states fitment clearly enough to match the shopper's year, make and model (or engine, or model number).

Here's the difference on an example part. The part is the same in both listings; only the data changes.

How to make a parts listing AI-ready, step by step

1. 1

   Let AI crawlers reach the page

   Check robots.txt for each AI search crawler (for example OAI-SearchBot, ChatGPT-User, Claude-SearchBot and PerplexityBot), not just Googlebot. Check whether your firewall or bot protection blocks them, remove noindex or nosnippet from product pages you want cited, and make sure the product details are in the page HTML without JavaScript.

2. 2

   Identify the part exactly

   Brand, manufacturer part number (MPN), GTIN or UPC where one exists, and the OEM part numbers the part replaces, including superseded numbers.

3. 3

   Put fitment in fields, using your category's key

   Store fitment as structured rows (for example year, make, model, trim) rather than a sentence in the description. Use the key your category's buyers shop by: the table below lists them.

4. 4

   Say what it doesn't fit, and when

   Exclusions (“not for models with a factory winch”) and qualifiers (front or rear, engine size, serial range) are what let an assistant say yes with confidence instead of “probably”.

5. 5

   Add the specs and contents buyers ask about

   Dimensions, materials, ratings, what's in the box and how it installs. These answer the follow-up questions after “does it fit?”.

6. 6

   Publish it as structured data too

   Add schema.org Product JSON-LD with the same identifiers, specs and fitment that the visible page shows. Keep the two consistent; conflicting values are a reason for an assistant not to trust either.

7. 7

   Fill gaps from supplier data, never by guessing

   If the data you have doesn't support a fitment claim, request it from the supplier or manufacturer. A wrong “fits” costs more than a missing one.

Fitment keys by category

Each category has its own way of saying “fits”. Use the one your buyers shop by.

Guides by category

• How do I get powersports parts recommended by ChatGPT and other AI assistants?
• How do I get marine parts recommended by ChatGPT and other AI assistants?
• How do I get auto & truck parts recommended by ChatGPT and other AI assistants?

Guides for RV and trailer, outdoor power equipment, ag and heavy equipment, appliance and bicycle parts are coming next. Until then, the industry pages list the fitment details each category needs.

Beyond vehicle parts: anything that has to work with something else

The same problem applies to filters, printer ink and toner, batteries, phone cases and chargers. The shopper's question is “will this work with my model?”, and the answer depends on a compatible-model list the assistant can read. See how to structure compatibility data for AI.

Check your own listings

A quick manual test: ask an AI assistant whether one of your parts fits a specific machine, and see whether it cites your page. For a fuller picture, the free AI Readiness Check scores a product page or a CSV of up to 10 parts, shows exactly what's missing, and marks gaps your own data can't fill as “Needs supplier data”. You can see an example report first.