I'd like to welcome everybody to the marketing analytics section of our Coursera course. My name's Eric Bradlow. I'm professor of marketing and statistics here at the Wharton School, and I'm really excited to be with you and to teach you really what I've been doing for the last 20 years. So what I get to talk about, being that I'm the last person in the session, are the five major application areas of analytics today in the field of marketing. And that's right, I get to talk to you about the really cool stuff. What is Google doing with analytics? What is Amazon doing with analytics? What are big firms, other firms that you may not be thinking about doing with analytics? And I get to spend some time talking about my own research and what I've been doing with analytics over the last 20 years. There will be basically a five part structure to what I'm going to talk to you about. The first and most important question, and this is where everybody should start, is the data. If you don't have the right data, if you don't have the individual level of data, then you can't do customer analytics. So part of what I want to talk to you about is, how do you build the right infrastructure collect the right data? The second part is exploring the data. A lot of want to rush and field, rush and fit fancy statistical models, I'm a statistician, I love fancy statistical models, but it's never where you should start. You should always start with basic exploration of the data, and I can always give you an example from the days I spent at DuPont. I spent three years as a marketing person at DuPont. The first thing when I presented the statistical model to one of my colleagues or my boss, he'd say, Eric, that's very interesting, but can you show me something basic in the data that suggests that this effect is actually real. That's what I'm going to talk to you about. The third part is prediction. So there's the old joke, the old adage, prediction's only hard when you're talking about the future, but that is what marketing people do. We make predictions about the future. But the key, and this is what this module is about, we do it one customer at a time. One of the old stories I like to tell is, you know, if Sony pictures calls me on the phone and says about the Marvel film, we want to predict how many people are going to watch Ant Man in every state of the United States. I would say great topical problem, really interesting problem, but that's not customer analytics. If you want to predict what each person's going to do, how many of them are going to see Ant Man, how many are going to see the previous Marvel films, how many are going to see the future Marvel films, that's a customer analytics problem. And it's not just a motion picture studio that has that problems, grocery stores, consulting firms, Amazon, Google, Facebook, all of these companies have this type of prediction problem. Then the fourth part of course is predicting the future's nice, but optimizing the future is even better, and that's really why marketing has now gotten a seat at the C-suite. Which is, we can now talk about pricing for optimization. We can now talk about emailing for optimization. We can talk about discounting for optimization. Optimization. And so, once you have the right business problem and the right data, you have explored the data, and you fit a model, you want to optimize against it. Because that's firms goal, firms want to maximize revenue and profitability. And then of course, the last piece is taking business action. And so, the nice thing about going last in this module, and talking about applications and case studies, is I can talk to you about how firms have actually used analytics for decision-making. And to be honest with you, this is really, has been a 20 year journey for me. It's been me working with lots of different companies, lots of interesting problems. A lot of people again ask me, you know, what's the difference between being a statistician out of marketing, and I'm saying today, it's not either or. The one thing I always say is, if you don't understand about business analytics and its application to marketing, there's a cement ceiling sitting on top of you that you cannot go beyond within a company. And it doesn't matter whether you want to be the CEO, the CIO, the CMO, the CFO, everybody needs to understand how to make money one customer at a time, and I'm going to talk to you about how firms are doing today. I'm really excited about it and come join me for the journey. >> Good.