Hi, everybody. I know Thomas talked to you about willingness to pay, and you can imagine that something you really want to find out when you're making a pricing decision, how much of these customer's really willing to pay for what you're selling. It's now time in the course to get down to the hard work of measuring this, and we're going to start with surveys. Why surveys? Surveys or many respects the easiest way to measure willingness to pay. They are quick, they are relatively cheap and sometimes they can give us very good information about that willingness to pay metrics. So let's just dive in on this. So one way to try to find out willingness to pay, is just to ask people directly. How much are you willing to pay for that? And someone would say, hey, I know how much I'm willing to pay, I'd pay $850 for that bicycle. And that may be true, but when they answer the question, they may have other things on their mind as well. Think about it for a moment. If you thought [SOUND], whatever answer I give might influence the price that the individuals going to charge for it. So if I really want to buy the object, whatever they happen to be selling, maybe I should low ball them. Telling them I'm willing to pay less. And says, hmmm, better tell them I'm only willing to pay $500. And maybe they'll lower the price. So a couple of things come into play here. One is exactly what we're talking about here. People might shave the price down with the hope that they can get a better deal on whatever you're selling. It's also true that sometimes people don't really know exactly how much they be willing to pay when you ask them on a survey. And only when they get to the point of making a choice do they really discover to themselves how much they'd be willing to pay for whatever they're looking at. We're going to try to make this a little bit better in the survey. We're going to try to get rid of at least this problem that we're talking about right here. How are we going to do that? Well, instead of asking people directly, how much would you be willing to pay. We're going to ask them two questions, and from those questions we're going to be able to deduce the populations or the segments that we're after, willingness to pay. So let's start with the question that looks like this, at what price would this product be so inexpensive that you would doubt it's quality. Now, what is that mean? Well, I imagine you had shopping situations like this in your life where you go into a store and maybe there's a wool sweater and they're charging $29 for it and you're thinking, well, $29 for a wool sweater. There is no way that can be a decent wool sweater. It must be thin, there's something must be going on. It's gotta be defective. So there are prices at which, for some and she said, if the number is below that, I doubt it's quality so much that really even, I wouldn't consider buying it even though it looks like a good deal. So you can ask that question of people and people will give you responses on surveys and you can build up data that looks like this. Now, what is this data tell you? Well, over here on the left hand side we have these minimum prices. These are prices that different people have written down in terms of their minimum willingness to pay. The price below which they would question the quality of the particular object. So we have some prices sitting down here, and then here we have the number of people who answered each of those different prices. Obviously this is an example, so they're kind of small numbers here for the responses, and each of these numbers represents a certain percentage of the overall response, and that's given right over here in this column. And then, finally, the interesting column is this cumulative percentage column over here on the right. What does that mean? It means that if you charge $1 for this item only 9.1% of your target population would do that is, acceptable. Most people the vast majority would people say $1 is just too low, the vast majority wrote down a larger number is that minimum for us hold on their survey. If you get up to here, let's look at $10 and that's about 81.8%. What does that mean? It means for 81.8% of your target population $10 is an acceptably low price. That means it might be cheap to them but it's okay, they wouldn't doubt the quality and if you get all the way up here to $25 100% of the target population says, if I see $25, I'm not going to question the quality. So I hope this is clear to you. This is something that you can grab the PowerPoints and look back at this to make sure the numbers make sense. But that's what this is, these are acceptably low prices, now the other side of that coin is what price would this product be so expensive that it wouldn't be worth it? At what price is just too high? And I don't care how much I like it, I'm just not going to pay that amount of money. So people write down their maximum prices. And those were given over here in the left-hand column. There there's frequencies again and those percentages calculated in just like they were before. But let's think about what this cumulative percentage column means over here this time. That means what percent of the population would find that number, just too high. If you get $35, it's 45.5% of you target population. If you're up to $55 no one is going to be willing to pay that much. You have 100% of your population if you are all the way down at $20 it's only 18.2%. So if you do some quick math here you know 82% of those just 100 minus 18 would view that is acceptable. Now, what we have is, how many people think it's too low, and how many people think a particular price is too high? We can combine that information in a way that's really going to help us get at the overall population's willingness to pay.
