John Andrews

Now you have to, as you start to bring in new products into the mix, something that you're designing you've never sold before, that's where then the machine learning comes into play to say, okay, help me build a model of this product

that I can then bounce against my choice model to identify what that demand is going to look like.

When you do that right, we've seen customers with anywhere from, you know, at points five to seven percent increase in revenue to, you know, upwards of, you know, 13 to 14 percent increase in gross margin.

No.

Now, the technology is getting better where there are in-store sensors.

There's RFID where you can see what goes into the dressing room, what comes out, and then what goes up and people buy.

The reality is, Nathan, is that you don't actually need that level of granularity to get the signal out of understanding customer preference.

Part of the technology, you need to identify what the selection set is that people are likely looking at.

Just by understanding what was in inventory and then what the customer bought gives us significantly more signal than just the transaction level information of what a customer bought.

Now, you brought up Amazon, right?

And everybody in the retail perspective is looking at Amazon in terms of what they're doing.

One of the benefits that Amazon has is just an enormous amount of data, right?

The challenge that other retailers have, even though they feel as though they have a lot of data, the issue is that they actually have very sparse data about an individual customer

And individual products and specifically with those customers interacting with those products.

Right.

So the reality is they need to be able to pull signal out of what is actually very sparse data.

And that's one of the things that makes this extremely hard to kind of pull that signal out where that idea of understanding choice becomes becomes critical.

So we're a SaaS-based subscription model.

What we do is we take a customer's data, we run it through our engine, and then we expose that information via a web-based interface that customers can interact with on real time.

So I'm mentioning earlier from the different solutions that I talked around on plan optimization, buy optimization.