Hey there, this is really cool, thanks for putting this walkthrough together! It’s awesome to see more merchants diving into direct AI integrations with their stores.
What I’m finding super interesting right now, especially with tools like this that let AI actually do stuff on your store, is how critical the underlying structured data becomes. When AI is generating product descriptions or making SEO tweaks, it’s really leaning on how well your store’s data is organized and presented. I’ve seen some amazing results when stores have really clean, rich product data that AI can just slurp up and re-purpose. But if that data is messy or incomplete, even the smartest AI can struggle to make truly impactful changes.
It makes me wonder, from your experience, what are some of the common data gaps or areas where merchants should really focus on cleaning up their product data before handing the reins over to an AI agent like this? Or have you found that AI is actually pretty good at inferring and fixing those gaps on its own?
Always learning on this front, so genuinely curious about your thoughts!