So let's dive right in and start talking about data. The kinds of data that Rigou was talking about. The kinds of data that you as a consumer might be creating. The kinds of data that you as a manager might be using in order to make statements about how well your business is doing. So just imagine, let's just take one consumer. Imagine that the consumer is seeing some ads over here, here, and here, maybe she's getting some direct mail,or maybe email from the company. She's getting messages and offers here, here, and here. And maybe she's making purchases. So she buys something over here, here, and here. And maybe she returns one of these products as well. Or maybe she has contacts with customer service. Or maybe she's engaged in social media and she's posting ratings and reviews, or interacting with other friends about this product or service. So you start to a sense of the wealth of data that becomes available. And again Rigou did a nice job of talking of both some of these individual metrics. As well as the different kind of marketing activities, competitive information, you might want to put on top of that macro economic data, there's all kinds of factors out there that we might be tracking. And that might have some influence on the kinds of behavior that people are doing. Well, what are you gonna wanna do with that data? Well, besides trying to just draw inferences from it. So just tell me how much stuff I sold. Tell me what my market share is. Tell me how many promotions I ran, and how many things I sold during those promotions. All of that stuff is great. But if you notice as I'm talking about it I'm gesturing over here. Cuz what's over here? That's the past, right? And it's great to be able to summarize data, and it's great to be able to draw insights from the data that you have, but that's not enough. If you wanna run your business most effectively, if you really wanna take full advantage of the kinds of analytics that, well, that's why you're taking this course. We want to be over here. Right? We want to be making some predictions about the future, and that's the hard part. So that's where I want to talk about different kinds of predictions that we might want to make. So again, it might be how many purchases this person is going to make in the future. It might be is this person going to churn? Are they going to drop their subscription with us or not? And while a lit of these things might sound just wildly different from each other, as I said before, we can break them down into basically two kinds of buckets. And so for so many times when we're making predictions, we wanna make predictions about a fixed period in the future. So we might wanna know, in the next month or in the next year, how many purchases will this person make? Or how many products will they evaluate, or how many products will they return? So we're gonna take a fixed period of time and we wanna make statements about it. And likewise it might not only be questions about how many purchases or returns or whatever people are doing. We might want to make statements about whether or not someone's going to do something of interest. Will they make a purchase? Will they drop their contract? Okay so, there's different kinds of decisions, but it's all taking place within that fixed period. Now, I'm going hand things back to. So, he's going talk about some simple, popular, but very powerful techniques. So he's gonna let us answer some of those questions about how many things might take place, or whether or not certain activies might take place. So we're gonna cut to Rigou, we're gonna hear him talk about some of those models, then we're gonna come back and I'm gonna talk about an entirely different framework based on the very same kind of data. But to be able to ask and answer questions about when, how long, beyond one single period.