AI is becoming extremely useful for a lot of things, including analysing huge amounts of data. Does that mean it can replace an experienced Amazon team altogether? Not quite. Or at least, not yet. There’s certainly a lot it can do well, especially when it has accurate data to work with, but you still need people with the experience and commercial judgement to know what to do with the results.
Watch the video below for a discussion of where AI can help Amazon sellers and why experienced people still matter.
AI Advice Needs Account Data and Business Context
Getting useful advice from AI depends heavily on what you actually give it to work with. Ask how an Amazon advertising campaign should be structured and you’ll probably get a decent starting point. But it doesn’t automatically know your account, your products or how those products have been performing unless you provide that information or connect it to the relevant data.
Pricing is a good example. You might be told to keep a product within 5% of the cheapest competitor, but that’s not particularly useful if there’s hardly any profit margin left at that price. And depending on the product, being the cheapest might not be particularly important anyway.
Advertising decisions need the same context. You need to know what you’re spending, whether people are clicking and, more importantly, whether those clicks are converting. Without access to the actual account data, the advice is likely to remain general.
Experienced People Still Need to Check and Act
Amazon changes all the time, and this is another area where relying entirely on AI can cause problems. Ask how to do something in Seller Central and you may get outdated instructions that bear little resemblance to what you’re actually looking at today. Check them against the current interface and Amazon’s guidance before acting.
You also need to keep an eye on what happens after you’ve followed the advice. A new image might look considerably better than the old one, but that doesn’t necessarily mean it will perform better. Compare click-through and conversion rates using enough data to judge the change, and consider whether pricing, stock or advertising have also changed.
Then you’ve got catalogue problems and support cases, where knowing what to do next often comes from experience. Sometimes the first answer from Amazon simply doesn’t resolve the problem and you need to keep pushing it. This is where an experienced Amazon consultancy can be particularly useful.
Where AI Can Save Time for Amazon Teams
You can still use AI for a lot of the Amazon donkey work, particularly when it saves somebody spending hours doing something that can now be done in minutes. Working through large amounts of information is a perfect example. Customer feedback, supplier documents and research can all be pulled together much faster when you already have the source material available.
Content is another useful application. AI can help get a first draft together, come up with different ideas for a listing or give you something to start working from rather than staring at a blank page. Our guide to using AI for Amazon listings explains how to approach this in practice.
On top of that, it’s also becoming much easier to build internal tools for repetitive jobs that previously had to be done manually. You still need to check the information, product details and what happens to performance afterwards, but there’s little benefit in doing everything the slow way simply because that’s how it used to be done. Use AI to speed up routine work, with experienced people responsible for the decisions and results.
For a broader look at the opportunities and limitations, read our guide to what AI can and can’t do for Amazon sellers.
