At the beginning of our time together, I mentioned that I'm the co-director at a research center, the Wharton Customer Analytics Initiative. But I never really took the time to describe what it is that we do or how it fits in with my overall desire to get companies to understand and become more customer-centric. So let me tell you a little bit about both of those things. So what do we do? Well, actually, we're a matchmaker. We don't actually do the research. We'll find companies that are sitting on top of lots of interesting customer level data. So whether it's data about individual consumers buying things or whether it's physicians writing proscriptions or whether it's insurance brokers writing policies. We're very agnostic about what we mean by customer, and in all these cases the customers, whoever they may be, we have lots of data on what they're doing over time. And lots of desires to extract insights from that data to help the company become more customer-centric. So, here's the way it works. We'll sit down with a company and we'll talk about all the different data assets that they have and all the business problems that either arise from or motivate some of those data assets. Then we'll hold a webinar, and we'll basically announce those data assets. We don't give the data away, but we'll describe the data to academics all over the world. So all schools, all disciplines, all geographies, we basically say, hey researchers, here's this dataset, or this set of datasets. What would you do with it if you could get access to it? You tell us. What theories would you test? What models would you develop? What algorithms would you come up with? You tell us what's interesting, both from an academic and a commercial standpoint, write us a proposal. We'll get 40 or 50 proposals. We'll sort them into buckets based on what techniques people are proposing or what substantive questions they're attempting to answer. Then we can go to the company and say, hey, company, here's 40 great ideas. Some of them might be more interesting and relevant than others, and that's fine. You pick as many of them as you want. You pick, say, a dozen of them. We'll go back to those researchers, give them the data and say go to it. And at the end of the process a few months later, we'll have this private symposium where the company gets together with all of these academics to talk about the data and the insights and the commercial value. And it's really terrific, because all too often we'll have practitioners and academics kind of talking over each other's heads, thinking that the other one doesn't understand the problem. But if we have the company that gave us the data and all those academics that have been working on it, they're seeing eye-to-eye. We'll see just tremendous insights, and again, commercial value that can be tied to meaningful financial results arising from these projects. So part of it is that it's nice to see better research happen. It's nice to help companies raise their quantitative literacy. It's nice to have researchers work on more practical, relevant problems than the usual ivory tower stuff. And this whole mechanism is just a nice way to bring customer-centricity across. because while I'm talking to companies and talking about customer-centricity and everything that we've been covering here, sometimes it's hard for them to get going. Sometimes they need the data, they need the metrics, the COV, the customer retention. So maybe we can start on that side and we can have top academics all around the world show them how they can derive some of those analytics from their data, and it becomes much easier for them to start to do the strategic thing as well. So it's just a really nice triangulation between the kind of pure talk that we have about the customer-centricity and the research work that we do. And it all meets together, and it all makes the world a better place. At least when it comes to customer-centricity.