Yeah. To give you another example of how we can try to use analytics and make the best possible use of the data that's available to us, lets take the case of a performing arts center. You know, I've pulled out a couple of the decisions that the performing arts centers have to make. Yeah, they've got to decide what's the schedule of performances that they're going to show. What kind of pricing options are they going to have? What kind of subscription options should they be offering? Should it be a flexible subscription plan, where people can choose the particular shows available to them? Or is it going to be a fixed plan, where you get tickets for every single show in that plan? How do we define the seating tiers? What are the price options going to be on those different seating tiers? What about fundraising? Who are the people that we go to when we're trying to bring in additional funds to continue our operations? And just like other marketers, we've got to deal with advertising. So, how do I get people to show up to my programs? You know, if we think about this as building up an audience, same exercise that any brand is going to try to go through. I need to bring in new customers. I've got to keep my current customers happy, and I've got to retain them. So, if we look at, you know, look at the problem of building up the audience. Well, couple of ways that we can look at that. One way that we can look at this is from the programming that we bring in or from the products that we make available. Some products, some programs are going to be more costly than others whether it's bringing in performers or building up a new product that we haven't had before, developing new services that we haven't had before. There are going to be cost associated with that, but we've got to have an understanding for what products or which programs are going to appeal to our current and future customers. So, that's one set of decisions that we have to make that hopefully our data is going to inform for us. But then let's put ourselves in the position of the consumer. What are the media that consumers are using to acquire information? That's going to provide insight into where should I be doing my advertising. What are the demographics of an area? What types of programming do particular groups tend to like? Is it consistent with the mission of the performing arts center? What's pricing going to look like? Again, all of these are questions we're asking putting ourselves in the shoes of the consumer. What is the consumer looking for? What are their preferences? What are their price sensitivity? What is their responsiveness to advertising? If we look at the seating chart as an example, you know, we've got seats in the rear terrace, we've got seats in the orchestra section, and then we've got tables that are very close to the stage. Some of those might be more preferable than others for consumers who can afford those different options. But for others, the only option that they might be able to afford might be the rear terrace seats or the lawn seats. So, when we're constructing these pricing plans, we need to understand what types of consumers do we have in the marketplace, where is the price points that we're offering. To give just one more example of trying to map data, apply analytics to that, and map that onto the decisions that we're making, think of managing a sales force. You know, if it's a restaurant or a hotel, how many employees do I need working at a particular point in time? You know, if we take a restaurant, if you know it's going to be a busy night - it's the holiday season at a popular restaurant - you're probably going to have a full staff on hand. Whereas if it tends to be a slower night, maybe I don't need as many employees at a particular point in time. What are the tasks that need to be completed? It's going to depend not only on the employees that are available to you, but also what's happening with the customers at a particular point in time. Which tasks are the high priorities for the customers? If we look at it from another perspective, how do we think about retaining our top salespeople, our top employees? What's the compensation package that we need to look at? How much of an impact do those compensation packages have on employee retention, on employee performance? You know, if the typical job of the direct marketers, I've got customers or I have a list of potential customers, what's the best way for me to market to those customers? If we look at this example, am I giving away products for free? Well, is that going to appeal to these customers? Is it going to have a measurable impact in the long run for us? It's not just saying "Yes, they took the free sample." But is that going to turn these prospects into customers? Is it going to turn lower value customers into higher value customers? Maybe a discount is going to have more of an impact for some. Well, what's the magnitude of that impact that we should use? Is a five percent discount enough? Is a 10 percent discount going to do it? Should it be a specific dollar amount rather than a percentage discount? What's the appropriate message that we should be using? You know, if we think about the insurance industry, let's take the case of, you know, life insurance. Well, if you're trying to sell life insurance to new parents versus life insurance to individuals who don't have families yet, you know, you're going to probably use very different messages to appeal to them. Same thing if we're selling auto insurance, right? You know, if you're trying to put a message out there that you need to have the appropriate auto insurance for young drivers who have just recently graduated college versus the parents with two kids versus, let's say, people who are older, maybe empty nesters, you're not gonna use the same message for any of those groups. You're gonna try to tailor that message. Well, what's the appropriate message? What's the appropriate media to be delivering that message? How much should we be putting into the advertising? So, depending on the composition of our customer base, depending on the market that we're in, those are factors that are going to have an impact on the type of message, the volume of messaging that's done, the frequency with which the messages are put out there might also provide some insight into how quickly do I need to update that message, you know, the intent of marketing campaigns to deliver a somewhat similar message, but with a different creative. Well, it's going to make the campaign last longer as opposed to airing a single creative time after time after time. So, what's the appropriate time at which we change out those creatives or when we need to move on to a different campaign? All of these are problems that marketers are facing that can be addressed with the data that's available to them. So, the intent of this course, there are a couple of goals that I have. One is to get to deliver the message that marketing is a data-driven practice. You know, we have a lot of data internally, and we can apply that data to make better business decisions, and that's ultimately what this course is about. We are going to be focusing on doing work within Microsoft Excel primarily because it's a very common tool depending on the industry that you're in, the specific company or organization that you're working for. You may not have other tools at your disposal, you know, tools such as SAS, SPSS, R. These are all very powerful statistical tools, but depending on the organization where you're at, you may not have access to all of them. Microsoft Excel, chances are you're going to have available to you. The other part or the other reason why we use Excel in this class is, again, there is a lot that we can do with Excel, just the native capabilities. We're gonna go beyond using it to calculate averages and using it to store data. We're gonna use it to build decision support tools. We're gonna build tools that not only can you use but you can design them in such a way that they can be delivered to someone else and they'll be able to use the tool that you developed. And ultimately, that's what we want to do. We want to be able to say "Here's my business problem. Here is the data that I have. I want to be able to use this tool to solve that business problem." Right? So, at this point if you do have any questions, I'd encourage you to take those questions, post them onto the course site. And, you know, we'll be able to have the dialogue that way as far as making sure that we're all comfortable with not only the content and the pace, but making sure that I'm addressing any specific questions that you might have that is of particular relevance to why you're signed up for this course.