So, what I'd like to do is let's go back and look at the geographic data. Let's go to Rob's point, and that is that if you are looking at this and know anything about Chicago, you know that in the city people tend to have lower incomes and the suburbs people generally have higher incomes. Now, on top of that different suburbs look different. You get some suburbs that are xxx existing, they've been around for 50 or 100 years, they tend to be blue-collar workers, you have other suburbs that tend to be white-collar suburbs. So, just one indication of that would be to go back and look at the percent of adults with college education. The point is that, some suburbs like Evanston, you get close to 60% of the adults have a college education. In other suburbs, if you look in Chicago, on South Side, you get about 2% of the adults have a college education. So, the point is just that, you see a lot of diversity The point is, I could the price elasticity and I could do a lot of things just to come up with some kind of estimate: is the store sensitive, or not sensitive. And the point is, is that now you see some of things matching up pretty well. Like, down here, you see that low college education results in stores that are very sensitive to price changes. In some of these northern suburbs, you see that the yellows are xxxx, so the point is that in these stores of high education levels tend to indicate that people are not going to be price sensitive. So the whole result that we keep going after is this - first say, you know it's going to important, so lets measure price sensitivity. Then after we've done that, you know, can we go back and improve this? Because we do have some good reasons to expect that price elasticity isn't just some random variable. And the fact that college educated I have a higher income and I'm xxx , I've got a car, you know it implies something about my taste and my preferences.