AI handles data in eCommerce segmentation but misses brand-specific intuition. Over-segmenting and stale lists are classic mistakes AI doesn't automatically fix. Marketers still need to catch subtle overlaps, unexpected interests, and fit-style nuances that algorithms overlook.
In your opinion, like which are the kind of the classic segmentation sins? So over-segmenting, letting lists go stale. Would you say that AI does not automatically fix? And this therefore is the need for the kind of marketer and human to still kind of step in and override or kind of execute themselves?
When it comes to some of the things that AI is not sort of as great with today, you know, I'd say like stale lists currently is some of it. I think over time that'll help more because really anything that's like very data-oriented, it does a pretty good job. Some of the places where we see it falling over a little bit is just like that intuition. Like there's a level, like we were talking about, right? There's a level of like brand intuition that like a CMO, whoever, head of marketing or founder has about their brand where they're going, especially like cross-sell-wise or like what kinds of customers that are similar sort of problem profiles or personas might have kind of overlapping interests. So we've seen that a few times where we've gotten some really great gems out of our system for that. But then there's also been instances where, like, you know, where a brand has said, hey, look, like, you know, we've got, you know, certain fit styles, you know, of our apparel. And when you fall into a fit category, like you just care about those things in that category. And AI is not going to be as good at sort of identifying that and saying like, hey, you should create a bunch of segments around this specifically. And by the way, here's overlap between, say, these 2 kinds of sports that you might not necessarily think about.
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