Best practice for managing 900+ light bulb products with multiple attributes: tags vs metafields, faceted search & breadcrumbs

Technical Q&A
1

We are building a Shopify store specializing in light bulbs.
The final catalog will have over 900 products (all “light bulbs”) with multiple attributes:

  • Base type (E26 / E17, etc.)

  • Shape (A-shape / Globe / Spot, etc.)

  • Color temperature (Kelvin)

  • Lumen output

  • Dimmable (true/false)

  • Indoor/Outdoor use

  • Model number (e.g., ABC-1234)

Requirements:

  • Faceted filtering on collection pages

  • Searchable by model number

  • Breadcrumb navigation (category hierarchy)

  • Before bulk importing 900 products, we need to finalize the data structure and classification rules

Currently, about 10 products are registered as a test; the remaining will be imported via CSV by the client.
The main question is whether to manage attributes using tags or metafields.

Questions

  1. With many attributes (including numeric and boolean values), do you recommend metafields over tags for large catalogs, and why?

  2. If metafields are the choice, what are the best practices for managing them at scale (900+ products) — tools like Matrixify, API workflows, etc.?

  3. Any proven best practices for combining smart collections and breadcrumb navigation in Shopify?

  4. For model number search, would you store it in SKU or a dedicated metafield? Pros/cons?

Would love to hear from anyone with experience in similar-scale implementations.

2

Main reasons to choose metafields over tags:

  1. You can preset fixed choices for MF values (like E27/E14), etc – easier to manage in admin.
  2. For each MF you can get its own facet, while tags are a huge single heap in most modern themes.

Shopify has no collection/sub-collection hierarchy, so it needs to be worked around if necessary.

SKU/MF for model number depends more on your integrations with 3rdparty apps and services. There’s also barcode field…
https://help.shopify.com/en/manual/online-store/storefront-search/search-behavior#searching-specific-fields

3

yugeShopify Partner

1h

We are building a Shopify store specializing in light bulbs.
The final catalog will have over 900 products (all “light bulbs”) with multiple attributes:

  • Base type (E26 / E17, etc.)

  • Shape (A-shape / Globe / Spot, etc.)

  • Color temperature (Kelvin)

  • Lumen output

  • Dimmable (true/false)

  • Indoor/Outdoor use

  • Model number (e.g., ABC-1234)

Requirements:

  • Faceted filtering on collection pages

  • Searchable by model number

  • Breadcrumb navigation (category hierarchy)

  • Before bulk importing 900 products, we need to finalize the data structure and classification rules

Currently, about 10 products are registered as a test; the remaining will be imported via CSV by the client.
The main question is whether to manage attributes using tags or metafields.

Questions

  1. With many attributes (including numeric and boolean values), do you recommend metafields over tags for large catalogs, and why?

  2. If metafields are the choice, what are the best practices for managing them at scale (900+ products) — tools like Matrixify, API workflows, etc.?

  3. Any proven best practices for combining smart collections and breadcrumb navigation in Shopify?

  4. For model number search, would you store it in SKU or a dedicated metafield? Pros/cons?

Would love to hear from anyone with experience in similar-scale implementations.