Configure YMM metafield values

What this does

Drives Vehicle Finder fitment data from product metafields instead of (or alongside) a spreadsheet import — useful if your product data pipeline already writes vehicle compatibility to metafields and you’d rather not maintain a separate spreadsheet. This guide covers the parallel list metafields approach (custom.vehicles_*), which remains fully supported for existing shops. For an alternative single-metafield JSON format, see Import vehicle data.

The app links Year, Make, and Model together by matching list index, not by value — so getting the index alignment right on every product is what makes the dropdowns show the correct Model and Year options after a shopper picks a Make.

Steps

1. On each product, create metafields with namespace custom and keys starting with vehicles_ — specifically:

   • product.metafields.custom.vehicles_year
   • product.metafields.custom.vehicles_make
   • product.metafields.custom.vehicles_model

2. Set each metafield to a list of values, not a single value.

3. Add the product’s full set of Year/Make/Model combinations, keeping the same index aligned across all three lists. For example, a product fitting 2020 Toyota Camry, 2021 Toyota Camry, and 2021 Toyota Corolla needs:

   Index	vehicles_year	vehicles_make	vehicles_model
   0	2020	Toyota	Camry
   1	2021	Toyota	Camry
   2	2021	Toyota	Corolla

4. After saving metafields in Shopify, re-sync products (or wait for the product update webhook) so Vehicle Finder can use the new values.

Tips

• Be consistent with spacing and spelling — “Toyota” is not the same value as “toyota”.
• Every product that should appear in Vehicle Finder needs these metafield values set.
• Use the same metafield definitions and format across all relevant products.

Related pages

• Set up Vehicle Finder form
• Configure Vehicle Finder fields
• Import vehicle data (spreadsheet + optional combined JSON metafield)

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