Are you still kind of looking at similar types of data in terms of like growth in stores to really see where things are performing well and how to optimize it?

Yeah, it's two sides of it.

It's one on the front end of what do you want the category to be, right? So if you look at soup and specifically, there's a lot of what I would just call legacy brands, legacy formats, legacy flavors.

So the question is, would you just totally turn that on its head? And, you know, we have some items like a cheeseburger soup or a pizza soup, which initially sounds like an incredible idea, right? So just bringing totally new innovation to the category, something that no consumers had before in a retail product.

but the problem is those consumers aren't necessarily looking for that right if you're going for your shopping list it's you know i'm probably going to get my chicken noodle or my tomato basil so you end up with two sides of it where we end up with core flavors obviously we make tomato basil things like that they'll end up being the core drivers of the most of the revenue but things like a cheeseburger or something like that really bring in a new incremental customer right it's 100 incremental to the category of course because it's the only item like it so So you get two sides, like what is driving the core of the business from a revenue point of view, but then what is also exciting to bring new customers to the end.

So soup's an unusually large category that hasn't had a lot of innovation.

So we just got to really play with that.

But from it, what are some of the most important improvements compared to kind of the current version?