Hi, I am curious about how AI workflow and agents can help with repetitive tasks.
Running a store seems to come with a dozens of repetitive job: copying orders into a sheet, tagging and sorting them, chasing leads, reformatting product data, sending the same follow-ups, and alot more.
I am building automation workflows for exactly this kind of thing, and I’m happy to help out here for free, since this also improves my AI skills too.
Drop a comment with the one task you wish would just run itself, and I’ll dive into it. No charge and no sales follow-up, so anyone with the same problem can use it too.
What’s yours? The more oddly specific, the better. It would also be great if you would love to share the automation that you are proud of to build.
I’d automate cleaning up and standardizing product data. Fixing titles, tags, variants, and missing fields across a large catalog gets repetitive very quickly.
Hi @annaprimma . How are you doing today!
Honestly, the biggest time saver for most stores? Auto tagging ans triggring follow ups automatially, set it once & never touch again.
Love this one. The great thing is, you’re automating the cause, not the symptom. And it’s very buildable: a brand DNA store that every generation step reads from before writing anything. Three quick questions so I can sketch it properly:
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Where does your brand info live today: a guidelines doc, scattered notes, or mostly in your head?
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Which 2-3 asset types hurt most, and for which channels?
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What does “that doesn’t sound like us” usually mean in practice? One example of a good output vs. a rejected one would be gold.
With that, I’ll start to sketch the workflow.
Hi, that’s a great pick here! Catalog cleanup is one of the highest ROI automations because it’s rule-based. A few questions to scope it:
- How many SKUs and where are the data stored?
- Do you have a target standard written down format?
- For missing fields — should they be inferred from what’s already there (description, images, product type), or pulled from another source like supplier data?
- Is this a one-time cleanup, or does new messy data keep flowing in (imports, multiple people editing)? That decides whether you need a batch job or an ongoing gatekeeper that checks every new/edited product.
Love to hear the answers 
Doing great, thanks! How are you handling the tagging logic: fixed rules (order value, product type, location) or something smarter that adapts as the catalog changes? And what triggers your follow-ups — time-based, behavior-based, or tag changes?
Would love it if you shared the actual flow. That’s exactly the kind of thing this thread is for, and I’m sure others here would steal it happily.
I’d automate cleaning up and standardizing product data. Fixing titles, tags, variants, and missing fields across a large catalog gets repetitive very quickly.
Catalog cleanup and tagging are great picks. The one I’d add: the post-order question pile — “where’s my order”, “can I change my address”, “how do returns work”. The same handful of answers typed over and over, all day. Pulling them straight from the order data so customers get an instant reply took the biggest chunk of busywork off our team. One rule we stuck to: anything that moves money (a refund) the AI drafts but a human clicks approve — automate the typing, not the decision.
Human in loop definitely matters.