[MUSIC] All right, so the first thing we want to think about in terms of customers is, what is it that drives price sensitivity, this fundamental thing that dictates, how high or high low somebody's willingness to pay us for the product. So I'm going to go through some of the most common things that dictate price sensitivity and I'll leave you with an exercise to think about a couple of others. The first thing that really drives price sensitivity is ease of product comparison. So, if I have one product, product A with same made by manufacturer Johnson and Johnson and right next to it on the shelf, I have another product that's made by the retailer, a private brand as Barbara talked about. If they are really easy to compare and I can turn the products over and see that they're essentially the same thing, then I might be willing to buy the unbranded or the private label product. So, when comparison's made easy, consumer price sensitivity typically goes up. So as a seller, or a as a firm, as an entrepreneur, usually what you want to do is you want to make price comparison across your alternative and the competitor alternative somewhat difficult for the customer. You want to focus them on other things, like the quality of your product, your service, and so on. The second thing that's very, very important in terms of driving price sensitivity is the amount of overall expenditure that's being done. So if I'm going out and I'm buying new tires for my car, and the tires' $500 versus $600, I might be like man, I think I have to get those $500 tires, 100 bucks is a lot of money. But if I'm buying a car for $20,000, and the dealer Amy says to me, you know what, you can have these fancy tires for 600 or the rubbish tires for 500, I'm like, well, it's only another $100 on 20,000. It's nothing. So, when we're thinking about thing sin percentage terms, or as a small piece of an overall expenditure, our price sensitivity also goes down. So what's the implication for you, the seller? You want to try and get the buyer to think about what they're buying as really a small piece of the overall picture. The other thing of course that's related to this is if there's a separation between the buyer and the payer. So, maybe I shouldn't say this on a public video, but I've already started down the path, so let me do it anyway. So, I try to save the school money when I fly from Philadelphia to San Francisco, usually buying a coach class ticket and then trying to upgrade into first class if I'm lucky. But sometimes, I might actually pay, well not pay, I might actually buy a first class ticket, but of course I being reimbursed for that, so I'm less price sensitive because it's not coming directly from my pocket. But it's coming from the pocket of the institution. The other thing that's very, very interesting in price sensitivity is when there is a separation in time or method of payment. So, in an earlier video, we spoke about the matching of supply and demand and the example I gave you Uber, which is a car service where you can take your mobile phone and you can order a car to come and pick you up. And then the driver, let's say Chris, takes you wherever you want to go, you get out of the car, no money changes hands. Simply what happens is you get a text message or on the app you get the bill. So in that case I don't really feel the pain of payment, the pain of payment. If I had to take $20 out of my wallet every time I used Uber I might think about walking a little bit more often or taking the subway. But because the pain that is happening is just purely in my phone, and I'm not feeling it directly, I'm becoming less price sensitive. So that's another thing that makes price sensitivity lessened. A couple of other things that are interesting here, when there's a price/quality inference. I become less price sensitive. So if I needed to hire a lawyer for example, if I were in some kind of trouble with the immigration service, do I want Amy's cheap lawyers $50 an hour or do I want Chris's expertise lawyers $500 an hour. In that case, with as an inference that the higher price leads to a higher quality certainly for an important service, then my price sensitivity is again lessened. So hopefully those four things give you a sense of how you can have the customer psychologically feel a little bit less price sensitive. Now of course, this begs the question of how would one measure price sensitivity. Would you just do it intuitively, or would you try and do some research? What I'm going to take you through now is, there are really four ways to figure out price sensitivity. I'm going to show on the screen a two by two matrix that explains these four different ways. You could measure people in their natural environment, buying things or filling in surveys, that's the first column. Or you could run an experiment, sort of an unnatural environment but it's controlled either in the field or the lab or you could engage in something called trade-off analysis. Those are the two columns of this matrix. And then on the rows, you could either measure actual purchase behavior or you could measure their preferences and intentions. So, here's an example of an experiment. This was actually done by colleague of mine at the Wharton School, Steve Hoch, who's a professor here. And he wanted to try and understand the supermarket retailers whether or not they could raise prices or lower prices. So, what they did is that they cooperated with a institution in Chicago, those of you who are in Chicago called Dominick's Finer Foods. It's a supermarket chain located in the Chicago area, and what they did was in some of the stores, all the prices were systematically lowered by about 9% on a bunch of different products like detergents, paper towels, canned tuna and so on. In another group of stores, the prices were just kept as is. And in a third group of stores all of the prices on those same goods were Increased by 9%. So that's a classic experiment where we have a control group, we manipulate somethings downwards, somethings upwards and then we look at what happened. And what they found was very, very, interesting. They found that when prices were raised, demand went down by a little bit, as you can see in the light grey there on the chart, but actually, the drop in demand wasn't that much. Customers hadn't really noticed this pretty small price change as order of magnitude 9%. So profits went up quite a bit. So this experiment would indicate that those multi-product retailers, could probably increase their price a little bit. And you can probably think of some psychological reasons why that works in a grocery environment. Like it's not really efficient for me to pay attention to every single price and try and remember it. Now of course this study was done in the 1990s, might be a different thing if they did it today in 2013, because again, I could take out my friendly iPhone, and have my entire grocery list on here, I could use an app. Like the SaveOn app or the SnipSnap coupon app. And from those apps, I would be able to remember the prices or at least my device will do it for me. Second way that we can measure price, and this is a method that was really developed by one of our former colleagues at the Wharton School, Professor Paul Green. Paul is a very, very influential fellow in the area of marketing and he was one of the founders of what's been known as conjoined analysis or trade off analysis. So in the conjoined analysis, you present people different kinds of stimuli. And what you do is you manipulate certain things. So I give a personal example on this, when the four students who founded former students, who founded the company Warby Parker, selling glasses and eye wear on the internet, we did a project together here at the Wharton School to try to understand gee, what the heck should we charge for these glasses? What should be the price? Now we knew of course we didn't want to price purely from the cost and do cost plus pricing, we wanted to figure out from the top down, the customer willingness to pay the ceiling. So what we did is we presented different groups of people, glasses and we manipulated just one feature of the glasses. So Amy's group would see a pair of nice, blue Warby Parker glasses, and the price will be $75 and then we ask Amy and the other people in the survey how willing they would be to buy that product. And in the second group, we'll say Chris' group, we would raise the price to $85 but show the same pair of glasses and see what the response was. And we did this for four prices, 75, 85, 95 and 105. And through the conjoint analysis, we noticed the following. Demand was highest at $75, it dropped at $85. $85 to $95 was about the same. And then once we went to $105, it was another drop. So from this pretty rigorous statistical analysis, it was clear to us. But among those four prices, $95 would be the right price. This is something for those of you out there who want to do conjoined analysis. There are many very good commercial providers and consulting firms who can help you do this, and a lot of good publicly available information. I'd encourage you to learn a little bit about conjoined analysis, we don't have time to go into all the details here, because it's also a method that's very useful for trying to value your brand. As well as just set prices. Okay, the other two methods that sometimes get used, just direct surveys, now when you ask people how much they're willing to pay you have to be very careful, if you ask them directly because they'll low ball you and give you a really low price. So, the better way to ask that question through a survey is indirectly. So again, I could say to my friend Amy, here's a pair of Warby Parker glasses for $95. On a scale of one to seven, one meaning very unlikely to buy, seven meaning very likely to buy, how likely would you be to buy this product? And maybe the group exposed to that condition, gives an average score of six. And then I take the same survey and I take it to Chris and a bunch of other people and I say, how likely would you be to buy these pair of glasses were they $105 and I find that the average score for that group on a seven point scale is only five. So see the way I am getting at the price, I am getting it Indirectly rather than directly. That's the best way to do it to a survey. And then finally, this is not a direct topic for our cause together, but something I do a lot of my own research. As you go around on what's called a regression analysis. So you could take some real sales data and you could look at various prices and other things that are affecting sales. And you could compute that thing that revolved about economics The price elasticity of demand by doing some statistical and quantitative analysis. So those are the four ways that you can measure price sensitivity. Okay, you can run an experiment. You can run some statistical regression analysis. You could do surveys, or you could finally do a conjoint analysis. All four of those methods would allow you to get that. So now I'd like to spend a little bit of time just on psychological factors. Of course there are a huge number of books written on consumer psychology and so forth, so I just want to touch on the main ideas as they relate to pricing. So in certain countries or cultures, digits have particular meanings. Some Western cultures, nines usually indicate a discount or sale or something of that magnitude. So that's why a lot of products are priced at 3.99, 2.99, $1,900.99, somehow it feels better than just $2,000. So nines are a special kind of number at least in Western cultures. The second that's important to know is from a psychological point of view, as the demand curve is not always smooth, it doesn't always go down. If this is price on the X axis, demand doesn't always fall as prices are increased and it doesn't always fall evenly. So let me give you an example of that, simple experiment that was done in the UK. In some supermarkets over there, where the regular price of product of margarine is about $0.83 and at $0.83 the supermarket was selling a couple thousand units every week. When they discounted the product to $0.63, price went down, demand went up. Increased by almost 200%. So dropping the price $0.20 led to a 200% increase in demand. However, when the experimenters dropped the price just a little bit more, from 63 down to 59, then the increase relative to the $0.83 price was 406. So that's a classic example of a threshold, or a nonlinear response to a price reduction. Just by taking off another four cents or a small percentage, you almost double the lift that you got. [MUSIC]
