 Hey everybody. Hello from New York and spending a bunch of days here. It's my pleasure to see all your faces again. I'm going to do a quick overview of the dashboard that I've been building that allows us to keep better track of client growth, answer questions like who are our users, where they come from, how are they engaging with our products, where are they blocked, and ultimately where are the those blockers translated into opportunities for new features and products that help us scale the network. So as you might remember the next slide from a previous conversation, the TLDR here is can we actually start answering these questions in a data-driven way? As a growth practitioners, we are held accountable by the metrics we set and we have to really deeply understand the whole user journey coming from product marketing through to data cap provisioning and then ultimately how they're actually using our product. And so my launchpad project was around wearing my data scientist hat yet again. Deep was making a great joke yesterday. He was saying, you don't go to SQL. SQL comes to you. So wearing that hat that I've always enjoyed wearing and sharpening my data engineering knives and getting things all chopped up and ready to go in a beautiful dashboard, trying to get a bunch of different sources from Airtable, HubSpot, and Google Analytics and the whole bunch of things and GitHub, a whole bunch of things connected. So the next slide gives you a good sense of like the different places where I'm drawing information from. This has essentially been a really productive collaboration with the Sentinel team that is building an awesome PL data warehouse and figuring out ways in which we can use five-time connectors, for instance, to integrate all these different things into a common place where we can actually build out a suite of really clean databases with easy to use primary keys at a client level, at a deal level and actually understand the full end to end flow of our users across the data onboarding experience. This is the first version of the client dashboard. There's been actually a bunch of changes made under the hood since we last saw each other two weeks ago. A bunch of cleanup work, really, and a bunch of new integrations. So in this first section, we can answer the question, how are our users finding us and what are they interested in? I'm about to integrate Google Analytics too, so you get a good sense of like the actual places where they're actually on the Internet, where they're finding us. Over here, we get to see some information on data cap provisioning, some crucial metrics like time to data cap, which refers to the time between someone requesting some data that they want to upload through the FieldPlus program and the time where they actually get that data cap. So you see a nice kind of trend here where we are reducing the time necessary to provision the data cap necessary, keeping an eye out on the various requests and what state they're currently in. And then crucially, I call a few different funnel views. One here, I think, is an extremely useful view of how on a weekly basis, our clients are segmented into their different sizes. In other words, how much data have they uploaded so far. And so this is really interesting to see that growth is coming from both people who are just beginning to upload, but also people who have uploaded a significant amount. And this allows us to see where we might put in some of our resources, investing into more of the product marketing early stage, aha moment, versus making it easier to upload data at scale. Because believe me, it's not easy to upload one heavy byte of data. All this culminating with a few things, understanding who our clients are. The National Library is uploading 500 terabytes of data this week. How can we support them down to the people who are actually uploading for the first time? So all in all, this is something that was built with I think a lot of metrics attention. And we are going to, in the next steps, try to integrate things more, document a bunch of things, automate the production of a couple of weekly reports, and hopefully create the space for a data analyst maybe, or in general, create the space for everybody at PL to come in, understand how our growth is actually growing, and really make our, you know, get to a great place where our demand side scales. Thank you so much.