 One of the things we've been doing over the last few months is building closer partnerships with the product teams that we support. One of the ways in which you can think about partnerships is how in which you work with other people, and how you work with other people is directly related to how you organize and structure your team. In January, you can think of analytics structured in two ways, centralized teams or embedded teams. In centralized teams, you have this central, singular analytics organization where analysts partner with business units or product teams, and they provide insights and analytics work. And there's a number of benefits to centralized analytics models. So there can be great alignment on methods across the analysts. There can be greater awareness of fast work. Analysts tend to have full objectivity. And there's also this bigger picture view, which is really beneficial. But some of the downsides are that, in oftentimes, the analyst lacks full context into the problems that their partners are trying to solve. And in often cases, you can end up seeing much more of a reactive resource rather than a proactive partner. Embedded models is where you take individual analysts, and they're actually embedded within the business units that they support, or within, in our case, the product teams. And again, there are a number of advantages, mainly being that you now have much fuller context into the problems that the product teams are trying to solve. There's a higher chance of full integration of analytics into the whole product development lifecycle. And there tends to be better alignment to product and as a result, more effective decisions. But the downside here is that the analysts often end up working in silos. This can lead to a bunch of redundant work, and also a lack of culture and identity within the analytics team themselves. So when I joined, the product analytics team was a single central team, and it was part of a larger finance and analytics team. And the individual analysts partnered with one or two product teams, but there was definitely a disconnect. We were being seen more of a reactive resource than a proactive partner. So a few months ago, we moved to something that sits somewhere in the middle, a bit of a hybrid model, so we still have this central product analytics team, but we offer a number of ways in which we're embedding, and the level and extent at which we embed really depends on the goals and projects at hand. A really simple way in which we're embedding, and I would argue the way that's actually had the greatest impact, is now the analysts on the team attend the daily stand-ups for the product teams that they support. So what this means is that they get day-to-day contacts into what it is that the product teams are working on, what's top of mind, what their key goals are for the week in question. And likewise, the product team now has complete exposure to the context of the analysts, what it is that's top of mind for them, what are their key priorities. And this key change just means that there's a lot more shared context between the analysts and the product team in question. And I suppose the biggest impact here is actually that the analyst feels really part of the product team that they're supporting, that they're a key team member, and likewise that the product team really feels like the analyst is actually part of their team. And this has had been a huge win for us in terms of developing closer partnerships.