 One example that comes to mind that I was involved in with my last company called Market Share was with Ticketmaster and, you know, it's pretty well known in the live entertainment space that upwards of 40% of all tickets go unsold, whether that's sporting events or music concerts, things like that. And the stuff that does sell very well sells out very quickly and then there's a big resell market that then the secondary market steps in. So the idea was, hey maybe there's a way to use algorithms to create more scientific dynamic pricing that dynamically optimizes that price by seat, by section, by event, by day, by artist, or by sports team or what have you. But not just looking at traditional velocity but looking at a whole variety of things from the weather to fuel prices to what else is happening in that city that evening to, you know, historical activities to Google activities and search activities, things like that. So bringing, you know, all those data variables together and then figuring out algorithmically how you could optimize led to double digit impact on the revenue. And as a result it also meant that the artist and the venues were able to take more of that upside as opposed to a secondary company, a secondary ticket company getting all that upside. So it was truly one of those win-win-wins where the, you know, the ticketing company did well, the venue loved it, and the artists loved it. And secondary ticket companies don't love it very much because it cuts into their upside but the point is it's the use of data analytics and algorithms. That became a very central piece of that partnership.