How are you making Shopify product data usable for LLMs (ChatGPT, Gemini)?
I’ve been experimenting with how LLMs (ChatGPT, Gemini, etc.) interpret Shopify product data, and I’m noticing some gaps.
Out of the box, most product data is pretty unstructured:
- title
- description (free text)
- tags (inconsistent)
When you try to query products through an LLM (or simulate recommendations), it seems like they struggle unless the data is very explicit (materials, use-case, context, etc.).
Curious how others are thinking about this:
- Are you structuring product data differently for AI use cases?
- Are metafields enough, or do we need more standardized schemas?
- Has anyone experimented with generating structured attributes automatically?
Feels like Shopify data wasn’t really designed with LLM consumption in mind.
Would love to hear how others are approaching this.