SHA543: Segmentation and Price Optimization

Transcription

1 SHA543: Segmentation and Price Optimization

2 MODULE INTRODUCTION Module 1: Variable Prices and Segmentation Business that use variable pricing offer different prices to different market segments. This approach can increase overall revenue and profit, and is particularly beneficial to the hospitality industry. In this module we examine how variable pricing affects consumers' buying patterns and how we strategically apply pricing and segmentation to increase revenue. By the end of the module you will be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit Evaluate how prospect theory influences buying patterns Use prospect theory to better structure pricing communications Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers About the Course Project Track Variable and Dynamic Pricing In this course, you complete a project designed to evaluate the variable and dynamic pricing strategies of your firm or another travel-related firm. Over the duration of the course, you monitor and record prices at a firm of your choosing. It is important that you begin the project early in the course (preferably on the first day) so you will have enough time to collect the data needed. Toward the end of the course you analyze and report on the data.

3 TOPIC OVERVIEW Topic 1.1: Variable Pricing On a June weekend, wedding guests pay 90 for rooms the bride reserved the previous December. A businessman traveling cross-country checks into the same hotel and uses the same class of room, but he pays 150. Why would he receive a different rate? Across town, a mother takes her teenage son and infant daughter to the zoo for the day. Mom pays full price, the teenager pays half price, and the daughter is admitted for free. They are using the same resource (the zoo) at the same time, but each pays a different price for that experience. Why? These are examples of price segmentation or discrimination: a seller charges customers different prices for the same product or service, depending on their membership in a particular group or segment. In this topic, we explain that setting multiple prices for the same product-variable pricing-can benefit the buyer as well as the seller. Variable prices enable the seller to increase revenues while allowing more consumers to enter the market. By the end of this topic you will be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit

4 Price Discrimination Price discrimination is charging different customers different prices for the same product. It is a legal practice and common in the hospitality industry. Price discrimination enables companies to increase revenue by selling products and services at the highest prices that consumers are willing to pay, and also by using low prices to attract price-sensitive customers who might not otherwise buy. In price discrimination, the hotel or company setting prices must first identify its customer segments. This can be done by examining differences in the elasticity of demand: a group with a more price-inelastic demand will pay a higher price, and a group with a more elastic demand will pay a lower price. Once the company has identified the segments, it can target them using different prices. One problem companies face when using price discrimination is leakage. That is, customers who are willing to pay higher rates can sometimes slip down into lower rate categories. The company's goal, however, is to set a revenue-maximizing price for each distinct customer segment. If your company cannot effectively segment customers, implementing price discrimination is difficult. T rying to discriminate across nonsegmented customers is not recommended. Theoretically, price discrimination has three classifications: First-Degree Price Discrimination-Charge whatever the market will bear. First-degree price discrimination occurs when you charge the customer the maximum price he or she is willing and able to pay. Second-Degree Price Discrimination- Charge lower prices when the customer buys a larger quantity. Third-Degree Price Discrimination-This relies on customer attributes as a proxy for their willingness to pay. Because a customer's willingness to pay cannot be completely identified, sellers may find it effective to provide incentives for consumers to segment themselves. Hotels, airlines, and other users of revenue management excel at third-degree price discrimination. Businesses may sell rooms in hotels or seats on the plane or at the theater at a discounted rate close to the use date. To be successful, firms must limit the ability of consumers to resell their purchases to other consumers (that is, to become competitors). To avoid this problem, once purchased, these products or services are generally nonrefundable and nontransferable. Second- and third-degree price discrimination are not really mutually exclusive categorizations. Note: From this point forward, we use "differential pricing" or "price customization" as more customer-friendly terms to refer to price discrimination as applied in hospitality. These three terms are synonymous.

5 Price Customization Transcript: Price Customization Welcome, we're going to focus in on price customization and we're going to start that off looking at a relatively famous quote from the former CEO of American Airlines, Bob Crandall. And what Mr. Crandall stated was that if he had 2,000 customers on any given route and was utilizing 400 different prices then he was obviously short 1,600 prices. The idea that we would have an individual price for each individual customer. And so typically we don't go to that extreme but we're going to talk about some way in between one price and 2,000 prices-different methods on how to focus in on a dozen prices. Right, well so we'll focus on a level of prices, not a single price. Historically when we talk about multiple prices we can think of this almost as price discrimination. So here we have this downward-sloping demand curve, and if I was to set a single price then I would set that price such that the price defined by that rectangle, so the price quantity pair from that rectangle had the maximum area, and that would be the maximum revenue I could generate from a single price. One of the issues we see here is that there are two areas under this curve that are basically unmet. One of those is unmet demand and one of those is basically what we refer to as consumer surplus. Right, for all those customers who were willing to pay more than P-0 in this case, they are quite happy to pay-for all those consumers who are willing to pay more than P-0 they're quite happy only having to pay P-0 and as a result they get a consumer surplus. Similarly there's a whole subset of consumers over here on the right-hand side who are willing to pay less than P-0 and as a result of that they're priced out of the market. And the idea is as we go from one price to multiple prices we can capture some of that consumer surplus for people who are willing to pay more and we can also price in to that lower-valued market who is currently priced out of that market. So specifically if we were to also have a price P-1 which is higher than P-0 now we have the subset of consumers, Q-1, who before were paying P-0, now they're paying P-1, and so we generate some incremental profit from these individuals. That's because we're extracting this delta between P-1 and P-0. Similarly if we also price at P-2 which is less than P-0 now we're selling this difference between Q-2 and Q-0 into this

6 lower-valued segment that before was unmet demand and we could continue this process having more prices below P-2, you know, reaching a lower valued market, at the same time more prices above P-1, extracting some of the consumer surplus that individuals have at present. One of the issues we have with this is as I already talked about this was really not revenue management but this was more price discrimination, and what we want to think about is not price discrimination but price segmentation or customer segmentation. And so instead of having one downward-sloping demand curve we have a series of downward-sloping demand curves, each demand curve for each different segment, and then in each of these segments we set an optimal price. So instead of thinking this is one curve where you had multiple prices we have a series of different segments and each of those segments we have an optimal price, or even multiple prices if we can truly segment within that-or truly partition demand within that segment. And so this is what we refer to as price customization or differential pricing. Our goal here is to tap into these different segments with different willingnesses to pay at different prices. You know one of the issues is that we only have this one product, right, and so we only have one seat in our airline, we only have one rental car or one room. Obviously we can have some derivations of that product but for the most part a room is a room is a room, and so we have to think about how we set different prices for this same product, and at the same time prevent the P-1 people from buying down to P-0, so what we would refer to as prevent diversion. Right, so yes, I had this P-1 above P-0 but I only capture that gain if the P-1 people don't pay P-0. So in the RM space we typically think about restrictions or fences to help us achieve this segmentation. Some of these are more effective than others. We think about nonrefundable versus refundable products, we think about advanced purchase restrictions, you must purchase at least 21 days before arrival, are you staying a weekend or is it just a weekday stay? Right, so we have lots of different variants we try to structure around these different price points. For most hotels we can also segment by room types. Right, so if we have two doubles, a king suite, also potentially by floor obviously an airline is going to separate business from economy but they'd also like to do some segmentation even within economy. Right, and so we typically do this with some form of restrictions or what we all refer to as "fences," and we'll elaborate on this in subsequent sessions.

7 Examples of Rate Fences How can you differentiate and optimize the product you sell? By using rate fences. Rate fences allow you to charge different prices to different customer segments. Physical or direct fences are based on product attributes or characteristics and rely on direct differentiation of the good or service. Indirect fences (as the name indicates) are based more on consumer attributes. Direct or Physical Rate Fences Physical or direct rate fences are based on characteristics of the product, such as the view from a certain class of hotel room. For the firms that control them, these characteristics present opportunities to charge different rates for similar products. We see an extreme example of a direct rate fence in the airline industry, where customers can select from business class, with many perks, and coach class, with few or no perks. The cruise industry provides another example-customers pay differently depending on the physical locations of their rooms. Physical rate fences are based on physical characteristics such as: View King bed Two double beds Club floor Roominess of seat (business class versus coach class) Balcony Room or cabin size Car type (standard, economy, luxury, etc.) The first-class section of a ski resort with well-maintained conditions and a limited quantity of tickets Indirect Rate Fences Indirect price fences are based on characteristics of the consumer or the transaction, not the product. These fences can be divided into categories such as consumer, affiliation, and transaction. Consumer An example of a consumer rate fence is "r esidency," as with a cruise ticket. If a cruise is leaving from Florida in five days, discounting the price by $500 for residents of a certain state may attract customers who would not ordinarily purchase. Offering the discount for New York residents probably will not attract a segment that wouldn't have purchased otherwise-if they can afford the expensive airfare to Florida, $500 probably doesn't mean much to them. However, offering the discount to Florida residents (who do not have to buy airfare) will attract customers who may not have bought at the higher price. Other examples of consumer rate fences include attributes such as: Age of the consumer Ability to pay (for example, students) Rewards program member or season pass holder discounts Loyal customer Corporate traveler Affiliation Examples of affiliation fences include: Institution with which the consumer is affiliated Affiliation (for example, military) Rewards program member Transaction These rate fences are determined by the transaction. For example, nonrefundable reservations or those made online or through a promotion can generate corresponding rate fences. Nonrefundable-Fees apply if you change this ticket.

8 Refundable-Fares are fully refundable and may be changed at any time (fees may apply). Preferred upgrade-a "flexible" coach fare. If you're a Dividend Miles Preferred member and you buy this fare, you'll be upgraded immediately to first class (when seats are available and as long as the itinerary doesn't require a paper ticket). Other Fences Place of purchase (for example, online purchase versus in-person purchase) Advance requirement Quantity sold Coupons (for example, to certain customer groups or blasts) Time of use (for instance, weekday versus weekend. Golf fees are more expensive on the weekend. Weekend-segment people work during the week and can play only on the weekend.) Season of the year (for instance, high season versus low season)

9 Common Mistakes Using Differential Pricing Segmentation and differential pricing are excellent ways to increase revenue. But not all firms use these techniques wisely. More often than not, organizations use differential pricing to target more price-conscious consumers, allowing them access to discounts in a selected fashion. The goal, however, is to increase profits. If a company executes differential pricing poorly using imperfect segmentation, consumers with a higher willingness to pay may gain access to lower rates. This problem, stemming from an ineffective rate fence, is sometimes referred to as leakage. It results in lower average daily rates. As a hospitality company, you may be tempted to discount prices in hopes of selling more units to make up for the lower price. But this approach may bring the average price for both you and your competitors down. For example, when Hotel Ithaca first opened they had just one rate class: 250. In an effort to increase ADR and RevPAR, a year later, they expanded that to two rate classes: 350 and 250. Not long afterward, in an attempt to capture more market share, the hotel decided to offer a third rate class at 200. Though this move would reduce the ADR, the hope was that RevPAR would increase. As part of the plan, the hotel placed restrictions on the discounted rooms. Specifically, customers were required to purchase 30 days in advance, and those purchases were nonrefundable. Unfortunately, this rate fence did not work out as intended. The hotel soon found that some of its customers, those who would normally pay 250 (or 350), paid only 200. That is, there was leakage of the 250-paying customers into the 200 category with a less-than-anticipated increase in volume.

10 The lower rate did entice new customers for whom the 250 rate had been too high. However, the rate fence was still ineffective because the increase in demand was not enough to offset the lost contribution from 250-paying customers who were able to pay 200. The figures above illustrate the problem. The area to the right of 150 is new demand created by the 200 rate. Leakage can occur from two regions. First, the area below 250 and above 200, between 150 and 100, consists of some customers who are willing to pay 250 but now pay 200. Second, the area above 200 and below 350, to the left of 100, consists of some customers who are willing to pay 350 but now pay 200 (some of these customers may have also been paying 250 if the restrictions on the 250 rate were also imperfect). A company may choose to decrease its average price as a strategic move, but it should do so only if it can increase its RevPAR. If a hotel lowers its rate and its nearby competitor does the same, it will maintain the same market share but at a lower ADR. A company may choose to lower its average price as a strategic move, but it should do so only if it can realize a significant increase in occupancy. That is, it can lower its the ADR but must also increase its RevPAR. Firms too often structure restrictions in an effort to attract lower-value consumers. That is, they try to grow demand instead of attempting to extract the consumer surplus by getting current guests with higher willingness to pay (WTP) to pay closer to their WTP price. To extract customer surplus, firms use fences such as value-added packages that include free breakfast or Internet and are priced higher.

11 Empirical evidence suggests that firms pricing higher than their competitors tend to receive a RevPAR premium--the occupancy decline is more than offset by price increases. The adjoining figure summarizes data collected by Smith Travel Research (STR). The figure is based on data collected from 6000 properties over three years. The chart, comparing the annual ADR (horizontal axis) to occupancy and RevPAR (two series graphed) shows that avoiding lowering prices with imperfect fences (maintaining higher relative prices) may be a better strategy in certain circumstances. Obviously these results are not representative of all firms. Well-designed pricing and discounting efforts can increase RevPAR if companies are careful to avoid leakage. STR tracks supply and demand data for the hotel industry and provides market share analysis data. For further details on the data and study summarized in this figure see "Competitive Hotel Pricing in Uncertain Times," by Cathy A. Enz, Linda Canina, and Mark Lomanno. View the article. Note: you will need Adobe Reader to be able to view the article. If it is not already installed on your computer, you can download it (free) from the Adobe Web site.

12 Combat Market Dilution or Leakage Historically, major airlines have used rate fences to create segmentation. These fences included 7-, 14-, and 21-day advanced purchase restrictions, a round-trip purchase, and a Saturday-night stay. See Table 1. Fare Code Dollar Price Advance Purchase Round Trip Sat. Night Stay Percent Nonrefundable Y $ B $200 7 day Yes % M $ day Yes Yes 100% Q $ day Yes Yes 100% Table 1 Segmented Fare Classes In response to low-cost airlines that operated point-to-point one-way flights ( such as JetBlue), major carriers began to allow customers to combine two one-way tickets to create a round-trip ticket and eliminated the Saturday stay requirement. As a result, major carriers could no longer segment customers based on one-way flights or itineraries that had a Saturday night stay. Dilution started to occur because segmentation was not perfect. Customers who were willing to pay more were able to buy lower-priced fares because the restrictions (embedded with lower fares) no longer inhibited their purchases. Airlines saw the demand for B class move down to M class and people willing to pay $200 paying only $150. See Table 2. Fare Code Dollar Price Advance Purchase Round Trip Sat. Night Stay Percent Nonrefundable Y $ B $200 7 day % M $ day % Q $ day % Some airlines have been more successful in reversing this trend than others. Air Canada, for example, created more innovative restrictions by giving each fare class a name to which people can relate, in essence branding the product classes. They moved away from four fare classes--y, B, M, Q--and created five classes. The new fare classes are called Tango, Tango Plus, Latitude, Executive, and Executive Flexible. Each class presents the customer with a set of attributes rather than just a price. For example, customers who select Latitude class earn more bonus miles for travel than Tango class and they have access to priority check-in. Another distinction is access to the airline's lounge. The Executive classes are not charged incremental fees; Tango through Latitude classes are charged. Table 2 Reduced Segmentation This segmentation is not very different from what we typically expect from an airline product, but now it's associated with a name instead of a price. By simply giving the classes names and assigning them different qualities (cancellation fees, loyalty miles, advance check-in, etc.), Air Canada branded the fare classes and created more concrete differentiation. It

13 wanted consumers to ask themselves: "Is it worth selecting this to get my miles? Is it worth selecting this to get priority check-in?" Now consumers are selecting based on attributes as well as price. This has led to significant revenue gains for Air Canada.

14 Grand Casino de France Auditorium Seating Transcript: Grand Casino de France Auditorium Seating The Grand Casino to France has recently added a 20,000-seat auditorium in which their guests and others can enjoy internationally acclaimed performances. Currently, they are charging 200 per seat, but rarely do they ever sell out a performance. The casino is looking for some help in setting future prices. The auditorium is divided into three zones, zones A, B, and C. Zone A is the most desirable with a capacity of 3,000 seats. Zone B, the second most desirable, has 12,000 seats. And Zone C, the least desirable, has 5,000 seats. At their current price of 200, Zone A has a demand of 10,000, Zone B has a demand of 6,000, and Zone C has a demand of 2,000. As you can see, other than Zone A, there is surplus capacity in Zones B and C. They've engaged a marketing research firm to help them understand consumers' responses to price changes. Specifically, they've looked at three prices, that is the current 200, as well as decreasing down to 100, and then increasing up to 300. For Zone A, demand at 200 is 10,000 seats. If they were to decrease price to 100, demand would increase 100 percent or double to 20,000. Similarly, if they were to increase price from 200 to 300, then demand would decrease by 30 percent, decreasing from 10,000 to 7,000. Similarly, for Zone B, the base demand of 6,000 at 200 will double to 12,000 at 100, and then shrink to 50 percent to 3,000 at 300. Lastly, for Zone C, demand is very price responsive for Zone C, and we'll see here that if they drop price from 200 to 100, demand goes from 2,000 to 6,000 seats. Similarly, if they increase price from 200 to 300, demand is exhausted and goes to zero. So the question that we face is which of these prices should they be using, 100, 200, or 300? Should they have the same price across the entire auditorium? Should they have one price that's potentially different for each of the different zones, or at the extreme, should they have multiple prices for each of the zones? Instead of just selling at one price per zone, perhaps sell at both 100 and 200 in each of the zones. We're going to look at how we might tackle these questions knowing how responsive demand is to price. If we think about sales and revenue at a single price, let's focus on 100. We know that base demand was 10,000 for Zone A, doubling to 20,000 for Zone A at 100. Given that capacity is only 3,000, that means that even though demand is 20,000, we can only sell 3,000 seats. So 3,000 at 100 translates to 300,000 in revenue. For Zone B, if we were to price it at 100, the base demand of 6,000 would also double to 12,000. Capacity is actually 12,000, so we can meet all demand and generate 1.2 million in revenues. Lastly, for Zone C, if we were to decrease price from 200 to 100, demand triples from 2,000 to 6,000, and given that capacity is 5,000, we can only sell those 5,000 seats at 100 for a total of 500,000 resulting in a total revenue across all three zones of 2 million.

15 Now, let's go one step further and have fixed prices per zone, but potentially different prices across the zones, so one level of variable pricing. For argument's sake, let's set a price of 300 in Zone A. We know that at 300, demand decreased 30 percent from 10,000 down to 7,000, but we still only have 3,000 seats, so we're going to have sales of 3,000 generating 900,000 in revenue for Zone A. For Zone B, if we were to price at 200, our base demand of 6,000 stays the same, which generates 1.2 million in revenue. If we were to set a price of 100 in Zone C, remember our demand now went from a base demand of 2,000 to 6,000, but capacity is only 5,000 for Zone C, so we can only sell 5,000 seats even though demand is 6,000. Those 5,000 seats at 100 are generating 500,000 in revenue for a total of 2.6 million in revenue across the entire facility. Again, it's 2.6 million, higher than our 2 million at a constant price of 100 across the facility. Now, we can go one step further. Basically, we can have variable prices within a zone as well as across the zones. What this means is that Zone A may have a different price than Zone B, but Zone B may have multiple prices. If we remember back to our step one where we had our base demand and we looked at how that demand changed as a function of price, our base demand at 200 was 10,000, 6,000, and 2,000 across the three zones. That demand went to 20,000, 12,000, and 6,000 across those three zones at 100, and then decreased to 7,000, 3,000, and nothing at 300. Keep in mind our capacities are 3,000, 12,000, and 5,000 across each of those three zones. If I look at demand for Zone A at 300, that demand of 7,000 is greater than capacity, so life is easy for Zone A. We would simply just price at 300, our highest price and it clears all our inventory. Zone B is a little trickier. For Zone B, we had demand of 3,000 seats at 300. If we also priced at 200, remembering total demand at 200 was 6,000, but if we were to price it at 300, we've shaved off that top 3,000 initially. That remains the 6,000 minus the 3,000 and results in demand for another 3,000 seats at 200. Similarly, total demand at 100 was 12,000 for Zone B, but we've already sold 3,000 at 300, another 3,000 at 200, which leaves 6,000 seats of remaining demand at Zone B. If we look at Zone C, we had demand of 2,000 at 200 and demand of 6,000 at 100. If we were to price at 200, we would sell those 2,000. If we were also to price at 100, then we would have the remaining 4,000, which we could sell at Zone C. Keep in mind for Zone C, total capacity is only 5,000, so even though demand was 4,000 for 100 at Zone C, we're only going to be able to sell 3,000 of those seats owing to that capacity constraint. So the question that remains is how should we price. We've looked at three levels of complexity. For each of those levels of complexity, we have a set of optimal prices. If we were to set one price for the entire auditorium, what would that price be? Would it be 100, 200, or 300? We can go through that exercise and calculate total sales and resulting total revenues at 200, compare that to our 100, and do that again if we price at 300 and compare that to 200 and 100, and then decide which our optimal single price is across the facility. Similarly, if we focus on one price per zone, with those prices in each zone potentially being different, then what should the Zone A price be? What should the Zone B price be, and what should the Zone C price be? Earlier, we looked at a Zone A of 300, a Zone B of 200, and a Zone C at 100, but potentially, those aren't the revenue maximizing prices. Lastly, if we had multiple prices in each of the zones, what should those prices be? We went through the total demand and total sales of each of those prices. What's the resulting revenue as a function of those prices, and how does that compare to our first two cases?

16 Auditorium Pricing Exercise-Review In the previous exercise you analyzed revenue using different pricing strategies. You may download this spreadsheet that displays how we calculated the answers to the questions.

17 TOPIC OVERVIEW Topic 1.2: Communicating Prices How firms display or list their prices dramatically influences what customers buy and how much they spend. Although our lowest price may dominate our marketing communications, ideally we don't always want customers to pay the lowest available price. Additionally, most firms in the hospitality industry attempt to up-sell a customer to generate more revenue. A hotel may try to upgrade a standard room to a suite; a car rental agency may upgrade a customer to a luxury car or try to sell amenities such as a refueling package. You need to understand prospect theory to know how to display prices to discourage purchase at the lowest available price and to understand how to up-sell using upgrades to increase revenue. By the end of this topic you will be able to: Evaluate how prospect theory influences buying patterns Use prospect theory to structure pricing communications

18 Prospect Theory How you answered the previous poll illustrates an economic theory referred to as prospect theory. If you were to use a purely logical approach to answer, you would pick either A in both situations or B in both situations. In most cases, however, a significant number of people switch their preference from A to B or B to A as they move from question 1 to question 2. Quite often, people choose to receive the cash outright rather than take their chances at the game in question 1, but they take a substantive risk at a potentially large loss rather than knowing for sure that they are going to lose money in question 2. This finding is interesting because, logically, if you are taking a 50:50 chance at the game in question 1, you should be willing to take an 80:20 chance to play the game in question 2. Prospect theory (Kahneman and Tversky, 1979) argues that consumers make decisions based on the potential value of a loss or gain compared to a reference point, not compared to the actual value of the good or service (value is associated with anticipated changes in well-being). According to prospect theory, losses have more emotional impact than equivalent gains. The figure to the right illustrates the perceived impact of a $50 gain versus a $50 loss. Notice that the changes in state of being (positive or negative value) are different for the same absolute change: the negative value of a $50 loss is perceived to be greater than the positive value of a $50 gain. The figure also shows that the marginal change in well-being for gains is different than for losses. Changing from $110 to $120, for example, is almost as pleasurable as (actually, slightly less than) going from $10 to $20. Losses, however, tend to exhibit much stronger decreasing marginal impacts. Losing $10 is painful when going from $20 to $10, but the incremental pain felt when going from $110 to $100 is considerably less. Thus, once a consumer has agreed to pay a certain amount of money, getting the consumer to pay a little more is not difficult. D. Kahneman and A. Tversky "Prospect Theory: an analysis of decision under risk," Econometrica 47:

19 Ways to Communicate Transcript: Ways to Communicate So what we're going to do first is focus on three of the key aspects of prospect theory that relate to pricing. First: Letting consumers know the trade-offs of not booking. Basically, trade-offs of potentially paying higher prices if current prices become unavailable. Second: Realizing that gains are looked upon differently than losses. And then lastly: Once consumers have agreed to spend a certain amount, it's relatively straightforward to get them to pay a little more in subsequent transactions. So let's look at a potential airline display. This airline display is a very common display where I've searched for a set of departure and arrival dates, and I've also indicated that I'm flexible to travel in and around those dates. So what the airline has provided me is my base price in the middle of the matrix, as well as prices around my travel dates, allowing me to visualize those tradeoffs-that if I so choose to travel on these days, this is my price, but if I'm flexible I can move to lower prices. Or if I wait, I may have to pay higher prices for later departure or arrival times. We can look at a different airline display. Similar to our last airline display, this airline display has, across the top, different prices for different travel dates, but then below that, they have different prices for different flights within that travel date-so each one of these rows is a different departure time on that same day. But then within each one of those departure times, there's a series of different prices across the different products. So they have unrestricted products, and then they have business products, and a full spectrum in between, showing how prices increase across that spectrum. So allowing consumers to make those tradeoffs across potential itineraries and potential travel dates. Now interestingly, this is a third airline display. While initially, this display may look a lot like our last display, there's something that's fundamentally different here. As we go down the rows, we see that we have different departure times, like we have in our last display. But as we go across the columns, what we see here versus our last display is that these prices are decreasing from left to right, whereas before, our prices were increasing from left to right. So as I read across the screen-so as you're looking at this online, as you're reading it across your screen-then prices are decreasing. So this is a very different display than our last one. In addition to that, they're also providing some information of what product classes are unavailable-so creating this sense of urgency of booking now as part of the prices become red or zoned out, and unavailable. Prospect theory here would indicate that now as the consumer has sort of put his reference price on the first column price-the higher price-and then as he moves across the columns, those different prices are perceived as gains as prices decrease, whereas in our last display, the price on the most left-hand side was the lowest price. And as I moved

20 across the different price points, each one of those incremental price points was perceived as a loss as the prices went up. Given that gains are perceived differently than losses, the consumer is more apt to book at a higher price, with our high-to-low display, than they are with a low-to-high display. So this is some of the key aspects of something as simple as how we show these prices-are we going to get people to buy up versus always buy that lowest available product. So this sort of keeps in mind that when we're sort of thinking about quoting rates, we need to be going from high to low. This is something that we've cognizantly done at the call center or over the phone for years, but have really sort of resisted to implement online. We're basically communicating that we need to do those same strategic behaviors that we've seen on the phone, online when we sort of communicate those prices. This would be a standard hotel-related display. What we see here is a display that's linked to logic-logic by room type or package type-and not really fully capitalizing on prospect theory, in that prices are not monotonically increasing or decreasing. They're structured by product categories, and not fully capturing sort of the implications of consumer behavior upon how we set those prices, really leaving a lot of opportunities out there for the more innovative user of how they post those prices.

21 Reference Pricing You are at a restaurant and the waiter hands you a wine list with two options for the house merlot: Flying Goose Merlot 35 Flying Goose Merlot Reserve 45 Which wine do you choose? You're at the same restaurant and you receive this this modified wine list: Now which wine do you choose? Flying Goose Merlot 35 Flying Goose Merlot Reserve 45 Flying Goose Merlot Premium Reserve 55 The vast majority of people who select the 35 wine from the first list switch to the 45 wine in the second list. This is an example of reference pricing--the customer purchases the wine based on the price in relation to the other listed prices rather than to the wine itself. The way a business communicates prices (as well as the options available) influences our choices. Reference pricing is paramount in prospect theory. A reference price can come from a variety of sources. Memories of past prices What consumers have paid in the past for similar products. For example, if the customer paid 35 for a midsize car rental in Nice he might expect to pay the same amount a month later. Prices set by brand leader If McDonald's charges $1.20 for a hamburger, customers expect to pay about the same at another nearby fast food restaurant. Price of related products and services If airline coach travel from London to Paris costs 350, that helps create a reference price for airplane tickets for similar flights. The way the price is presented For instance, a firm may advertise a product available for four simple payments of 25 rather than one payment of 100. Another approach is strike-through pricing: the old price has a line through it with the new, limited-availability, lower price beside it, as you can see in the ad below. This creates a sense of urgency to purchase. The ad in the illustration showing the reference pricing with strike-through pricing presents a gain, and the sale tag "Hurry! Offer ends soon!" and "Only 4 rooms left at this price" creates some urgency and potentially increases the likelihood that the consumer will book.

22 When a firm reduces the offered price below the reference point, the customer views this as a "gain"--the customer "gains" more for the offered price. On the other hand, if the firm increases the offered price from the reference price, the customer views it as a "loss." Perhaps one of the major implications of reference pricing centers around universal discounting. During a downturn, firms often lower prices, and if a competing firm matches these prices, then the market price decreases. In essence the reference price for this market has now decreased. When demand picks up, consumers are accustomed to these lower prices, and it takes considerable time to increase prices as demand increases. It is much easier for firms to increase prices if they avoid reducing the reference price. One example of stimulating price-sensitive demand while minimizing reference price effects is the tactic of offering a free night with the purchase of multiple nights at the standard rate- Stay 3 nights, get the 4th night free. In this example the hotel effectively drops prices 25% for a four-night stay, yet the posted price or reference price is still the original price. If demand is price sensitive, it should respond to our increased value offer.

23 TOPIC OVERVIEW Topic 1.3: Upgrades Offering upgrades can be a strategic revenue-producing strategy if you know how and when to offer them to customers. To create an effective upgrade strategy, you must understand how your customers make purchase decisions. By the end of this topic you will be able to: Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers

24 Prospect Theory and Upgrading One of the most common applications of prospect theory happens daily in the hotel business. Hoteliers use prospect theory every time they attempt to up-sell guests to a better class of room or add some amenity for a small fee. These up-sells may be offered at check-in or online. With both approaches, the offer can be separated from the original purchase decision. For example, using the online approach, the upgrade offer appears after the customer selects the purchase and navigates to the checkout screen. The success of this strategy rests on one of the key tenets of prospect theory-it is easier to get customers who have already committed to purchase to spend an additional amount (the amount of an upgrade, for example) than it is to get them to make the more expensive purchase at the initial decision point. Many airlines use this strategy during both online transactions and check-ins at the kiosk. They may ask customers if they want to upgrade to business class or to a refundable fare for an extra charge. This example displays how one firm communicates the benefits of the upgrade (gain) before stating the fee (loss). Some strategies to gain revenue through online upgrading: Put time limits on the purchase; for example, "Act now to receive a free upgrade to a King Suite" or "Price good until 8 PM!" Clearly state how much the customer is saving (gaining) by purchasing or upgrading now. Using a strike-through is a good way to do this. Offer the upgrade at "checkout." Many Web site designs can provide offers for items related to the consumer's purchase in the Web site's pop-ups, banners, or sidebars once the consumer is at "checkout" or is checking the "shopping cart." This approach effectively uncouples the purchase and upgrade decisions.

25 Upgrading Online Transcript: Upgrading Online Now, we're going to focus on what I refer to as online upgrades and a further use or implementation of prospect theory. Prospect theory indicates that it's relatively easy to get consumers to agree to spend a little bit more given that they've already spent something. We would refer to this as the upgrade or the up-sell. You might think of it as getting nickeled and dimed to death. This is relatively easy to do at the front desk, but how do we do this online? You can think of a guest who is checking in late at night. The last thing they want to do is go through an up-sell at the front desk, so how do I move some of that upgrading process into the electronic world? What we can refer to here is the idea of the postconfirmation, nonguaranteed upgrade. Postconfirmation basically means the guest has already booked their reservation online, has received their confirmation code. Given that we're going to do this upgrading process 30, 60, or 90 days before check-in, we don't know what demand is going to happen in the next 30, 60, or 90 days. We want to offer this on a nonguaranteed basis. Basically, the supplier has the option, but not the right, to grant this upgrade. The consumer sees this offer, either accepts or rejects the offer, and then the supplier later, once demand has been realized, can also decide whether or not they want to accept or reject this offer. If we look at how this would be facilitated online, I've made my reservation, I'm at the hotel's Web site, and I've made my reservation. I receive my confirmation code. There might be a link to a discounted offer. It's important to communicate that this discounted offer is an offer but not a guaranteed offer. If the user clicked on this nonguaranteed offer, they would see a subset of potential upgrades. Maybe for $20 or $40, they could upgrade to one class of room. For $80, they could upgrade to two classes of room, and then for a higher price, they could upgrade to some sort of suite. It's important that you communicate to the user that what this upgrade is is a request for an upgrade. It's not a guaranteed upgrade. We may also send this upgrade offer via as well as right after that purchase decision. To allow for a separation between purchase event and upgrade event, we may later go through this process again, but via , so sending that confirmed guest an . Within that , we have this same offer. One of the things to remember is we can also send these upgrade offers to members of our loyalty programs. Presently, most of your loyalty program guests are probably expecting a free upgrade. What we would do is simply send them a set of offers, maybe three potential upgrade offers, and the first one would be free. Here we're communicating, this is your base-level upgrade. It costs you nothing, but here are two other higher levels of service, which are incrementally more expensive. Here's a great way to communicate that we value your service, and here's what we're going to upgrade you to

26 for free, but just in case, here are a couple better classes of service and an opportunity for you to even extract further revenues from these high-valued guests.

27 Benefits of Upgrading Consumers are often motivated to upgrade a product or service by the desire to get the best-quality product or service for their money. In addition to providing benefits for consumers, upgrading can increase profits and improve guest loyalty for sellers, and online upgrading also offers ease of implementation and management. Increased profits Organizations may increase profits by using properly structured upgrade strategies. Upgrades provide the opportunity to increase profits dramatically by selling off product lines that are generally undersold. After you have effectively segmented your product line, upgrades help you combat against people buying down to lower rates or lower-priced products. Even if the upgrade is steeply discounted or free, the next time that consumer comes to buy, he or she is more likely to purchase the same grade of product or class of service that the previous transaction was upgraded to in the past. Generally, people price shopping online are looking for a deal. Customers perceive the offer of an additional product or a discounted luxury item as a gain, and that can lead to a revenue boost for you. Improved customer loyalty Upgrading can help an organization improve guest loyalty. An effective upgrade strategy can strengthen guest relationships and loyalty by providing increased value. Also, because you are exposing your premium product or service to a wider audience, you increase future demand. At the front desk, you could upgrade a returning guest to free up a room valued at a lower amount. This helps develop brand loyalty by rewarding guests who stay frequently with a complementary upgrade to a higher-priced room. An online upgrade or loyalty system can further increase both your revenue and your customers' satisfaction. Online, you can show loyal customers what their loyalty will provide them in the form of a free upgrade. You can then show them the next greater upgrade, which they can purchase for a small fee. You can extract more revenue from your loyal customers by converting your top-tier loyalty consumers from complementary upgrades to paid upgrades. At the same time, you keep them happy by providing what they view as a gain: a nicer, better product or service, for just a little more than they originally planned to spend. Exclusive online "clubs" for frequent buyers and loyal customers are another way to use upgrades to improve loyalty and increase revenue. You can offer members of these groups perks such as free meals, discounted rooms for their birthdays, percentage-off discounts on their purchases, or guest passes for friends and family to encourage new consumers. Prime examples of using upgrade programs to increase loyalty are frequent-flyer airline programs. These programs provide free flights, free upgrades to first and business class, free drinks and meals, and many other benefits to increase customer loyalty; they increase revenue by requiring a certain number of purchases (ensuring that the customer will keep coming back) to earn the benefit. Easy to implement and manage online Online upgrade programs additionally provide the benefit of easy implementation and management. If it's online, you don't have to train people to solicit the upgrade purchases. Generally, with online upgrade programs, you incur no up-front charge for setup, implementation, or maintenance, and you have final authority over the upgrade and pricing structure. An online solution requires minimal daily management and demands little implementation time or effort. You can quickly generate additional revenue at little to no cost.

28 Upgrading at Ideal Car: Review In the last practice exercise you determined how many cars Peter should keep for "true" luxury customers. If you had trouble with the exercise, please review this spreadsheet with the completed analysis and try the quiz again.

29 Module Wrap-Up You should now understand how we use variable prices to increase the breadth of consumers we reach and to increase our profit. We discussed how we can employ prospect theory to encourage buy-up and to avoid market dilution. All these tactics are aimed at having a menu of prices available at any given time with the goal of increasing our average selling price. Having completed this module, you should be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit Evaluate how prospect theory influences buying patterns Use prospect theory to better structure pricing communications Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers

30 MODULE INTRODUCTION Module 1: Variable Prices and Segmentation Business that use variable pricing offer different prices to different market segments. This approach can increase overall revenue and profit, and is particularly beneficial to the hospitality industry. In this module we examine how variable pricing affects consumers' buying patterns and how we strategically apply pricing and segmentation to increase revenue. By the end of the module you will be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit Evaluate how prospect theory influences buying patterns Use prospect theory to better structure pricing communications Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers About the Course Project Track Variable and Dynamic Pricing In this course, you complete a project designed to evaluate the variable and dynamic pricing strategies of your firm or another travel-related firm. Over the duration of the course, you monitor and record prices at a firm of your choosing. It is important that you begin the project early in the course (preferably on the first day) so you will have enough time to collect the data needed. Toward the end of the course you analyze and report on the data.

31 TOPIC OVERVIEW Topic 1.1: Variable Pricing On a June weekend, wedding guests pay 90 for rooms the bride reserved the previous December. A businessman traveling cross-country checks into the same hotel and uses the same class of room, but he pays 150. Why would he receive a different rate? Across town, a mother takes her teenage son and infant daughter to the zoo for the day. Mom pays full price, the teenager pays half price, and the daughter is admitted for free. They are using the same resource (the zoo) at the same time, but each pays a different price for that experience. Why? These are examples of price segmentation or discrimination: a seller charges customers different prices for the same product or service, depending on their membership in a particular group or segment. In this topic, we explain that setting multiple prices for the same product-variable pricing-can benefit the buyer as well as the seller. Variable prices enable the seller to increase revenues while allowing more consumers to enter the market. By the end of this topic you will be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit

32 Price Discrimination Price discrimination is charging different customers different prices for the same product. It is a legal practice and common in the hospitality industry. Price discrimination enables companies to increase revenue by selling products and services at the highest prices that consumers are willing to pay, and also by using low prices to attract price-sensitive customers who might not otherwise buy. In price discrimination, the hotel or company setting prices must first identify its customer segments. This can be done by examining differences in the elasticity of demand: a group with a more price-inelastic demand will pay a higher price, and a group with a more elastic demand will pay a lower price. Once the company has identified the segments, it can target them using different prices. One problem companies face when using price discrimination is leakage. That is, customers who are willing to pay higher rates can sometimes slip down into lower rate categories. The company's goal, however, is to set a revenue-maximizing price for each distinct customer segment. If your company cannot effectively segment customers, implementing price discrimination is difficult. T rying to discriminate across nonsegmented customers is not recommended. Theoretically, price discrimination has three classifications: First-Degree Price Discrimination-Charge whatever the market will bear. First-degree price discrimination occurs when you charge the customer the maximum price he or she is willing and able to pay. Second-Degree Price Discrimination- Charge lower prices when the customer buys a larger quantity. Third-Degree Price Discrimination-This relies on customer attributes as a proxy for their willingness to pay. Because a customer's willingness to pay cannot be completely identified, sellers may find it effective to provide incentives for consumers to segment themselves. Hotels, airlines, and other users of revenue management excel at third-degree price discrimination. Businesses may sell rooms in hotels or seats on the plane or at the theater at a discounted rate close to the use date. To be successful, firms must limit the ability of consumers to resell their purchases to other consumers (that is, to become competitors). To avoid this problem, once purchased, these products or services are generally nonrefundable and nontransferable. Second- and third-degree price discrimination are not really mutually exclusive categorizations. Note: From this point forward, we use "differential pricing" or "price customization" as more customer-friendly terms to refer to price discrimination as applied in hospitality. These three terms are synonymous.

33 Price Customization Transcript: Price Customization Welcome, we're going to focus in on price customization and we're going to start that off looking at a relatively famous quote from the former CEO of American Airlines, Bob Crandall. And what Mr. Crandall stated was that if he had 2,000 customers on any given route and was utilizing 400 different prices then he was obviously short 1,600 prices. The idea that we would have an individual price for each individual customer. And so typically we don't go to that extreme but we're going to talk about some way in between one price and 2,000 prices-different methods on how to focus in on a dozen prices. Right, well so we'll focus on a level of prices, not a single price. Historically when we talk about multiple prices we can think of this almost as price discrimination. So here we have this downward-sloping demand curve, and if I was to set a single price then I would set that price such that the price defined by that rectangle, so the price quantity pair from that rectangle had the maximum area, and that would be the maximum revenue I could generate from a single price. One of the issues we see here is that there are two areas under this curve that are basically unmet. One of those is unmet demand and one of those is basically what we refer to as consumer surplus. Right, for all those customers who were willing to pay more than P-0 in this case, they are quite happy to pay-for all those consumers who are willing to pay more than P-0 they're quite happy only having to pay P-0 and as a result they get a consumer surplus. Similarly there's a whole subset of consumers over here on the right-hand side who are willing to pay less than P-0 and as a result of that they're priced out of the market. And the idea is as we go from one price to multiple prices we can capture some of that consumer surplus for people who are willing to pay more and we can also price in to that lower-valued market who is currently priced out of that market. So specifically if we were to also have a price P-1 which is higher than P-0 now we have the subset of consumers, Q-1, who before were paying P-0, now they're paying P-1, and so we generate some incremental profit from these individuals. That's because we're extracting this delta between P-1 and P-0. Similarly if we also price at P-2 which is less than P-0 now we're selling this difference between Q-2 and Q-0 into this

34 lower-valued segment that before was unmet demand and we could continue this process having more prices below P-2, you know, reaching a lower valued market, at the same time more prices above P-1, extracting some of the consumer surplus that individuals have at present. One of the issues we have with this is as I already talked about this was really not revenue management but this was more price discrimination, and what we want to think about is not price discrimination but price segmentation or customer segmentation. And so instead of having one downward-sloping demand curve we have a series of downward-sloping demand curves, each demand curve for each different segment, and then in each of these segments we set an optimal price. So instead of thinking this is one curve where you had multiple prices we have a series of different segments and each of those segments we have an optimal price, or even multiple prices if we can truly segment within that-or truly partition demand within that segment. And so this is what we refer to as price customization or differential pricing. Our goal here is to tap into these different segments with different willingnesses to pay at different prices. You know one of the issues is that we only have this one product, right, and so we only have one seat in our airline, we only have one rental car or one room. Obviously we can have some derivations of that product but for the most part a room is a room is a room, and so we have to think about how we set different prices for this same product, and at the same time prevent the P-1 people from buying down to P-0, so what we would refer to as prevent diversion. Right, so yes, I had this P-1 above P-0 but I only capture that gain if the P-1 people don't pay P-0. So in the RM space we typically think about restrictions or fences to help us achieve this segmentation. Some of these are more effective than others. We think about nonrefundable versus refundable products, we think about advanced purchase restrictions, you must purchase at least 21 days before arrival, are you staying a weekend or is it just a weekday stay? Right, so we have lots of different variants we try to structure around these different price points. For most hotels we can also segment by room types. Right, so if we have two doubles, a king suite, also potentially by floor obviously an airline is going to separate business from economy but they'd also like to do some segmentation even within economy. Right, and so we typically do this with some form of restrictions or what we all refer to as "fences," and we'll elaborate on this in subsequent sessions.

35 Examples of Rate Fences How can you differentiate and optimize the product you sell? By using rate fences. Rate fences allow you to charge different prices to different customer segments. Physical or direct fences are based on product attributes or characteristics and rely on direct differentiation of the good or service. Indirect fences (as the name indicates) are based more on consumer attributes. Direct or Physical Rate Fences Physical or direct rate fences are based on characteristics of the product, such as the view from a certain class of hotel room. For the firms that control them, these characteristics present opportunities to charge different rates for similar products. We see an extreme example of a direct rate fence in the airline industry, where customers can select from business class, with many perks, and coach class, with few or no perks. The cruise industry provides another example-customers pay differently depending on the physical locations of their rooms. Physical rate fences are based on physical characteristics such as: View King bed Two double beds Club floor Roominess of seat (business class versus coach class) Balcony Room or cabin size Car type (standard, economy, luxury, etc.) The first-class section of a ski resort with well-maintained conditions and a limited quantity of tickets Indirect Rate Fences Indirect price fences are based on characteristics of the consumer or the transaction, not the product. These fences can be divided into categories such as consumer, affiliation, and transaction. Consumer An example of a consumer rate fence is "r esidency," as with a cruise ticket. If a cruise is leaving from Florida in five days, discounting the price by $500 for residents of a certain state may attract customers who would not ordinarily purchase. Offering the discount for New York residents probably will not attract a segment that wouldn't have purchased otherwise-if they can afford the expensive airfare to Florida, $500 probably doesn't mean much to them. However, offering the discount to Florida residents (who do not have to buy airfare) will attract customers who may not have bought at the higher price. Other examples of consumer rate fences include attributes such as: Age of the consumer Ability to pay (for example, students) Rewards program member or season pass holder discounts Loyal customer Corporate traveler Affiliation Examples of affiliation fences include: Institution with which the consumer is affiliated Affiliation (for example, military) Rewards program member Transaction These rate fences are determined by the transaction. For example, nonrefundable reservations or those made online or through a promotion can generate corresponding rate fences. Nonrefundable-Fees apply if you change this ticket.

36 Refundable-Fares are fully refundable and may be changed at any time (fees may apply). Preferred upgrade-a "flexible" coach fare. If you're a Dividend Miles Preferred member and you buy this fare, you'll be upgraded immediately to first class (when seats are available and as long as the itinerary doesn't require a paper ticket). Other Fences Place of purchase (for example, online purchase versus in-person purchase) Advance requirement Quantity sold Coupons (for example, to certain customer groups or blasts) Time of use (for instance, weekday versus weekend. Golf fees are more expensive on the weekend. Weekend-segment people work during the week and can play only on the weekend.) Season of the year (for instance, high season versus low season)

37 Common Mistakes Using Differential Pricing Segmentation and differential pricing are excellent ways to increase revenue. But not all firms use these techniques wisely. More often than not, organizations use differential pricing to target more price-conscious consumers, allowing them access to discounts in a selected fashion. The goal, however, is to increase profits. If a company executes differential pricing poorly using imperfect segmentation, consumers with a higher willingness to pay may gain access to lower rates. This problem, stemming from an ineffective rate fence, is sometimes referred to as leakage. It results in lower average daily rates. As a hospitality company, you may be tempted to discount prices in hopes of selling more units to make up for the lower price. But this approach may bring the average price for both you and your competitors down. For example, when Hotel Ithaca first opened they had just one rate class: 250. In an effort to increase ADR and RevPAR, a year later, they expanded that to two rate classes: 350 and 250. Not long afterward, in an attempt to capture more market share, the hotel decided to offer a third rate class at 200. Though this move would reduce the ADR, the hope was that RevPAR would increase. As part of the plan, the hotel placed restrictions on the discounted rooms. Specifically, customers were required to purchase 30 days in advance, and those purchases were nonrefundable. Unfortunately, this rate fence did not work out as intended. The hotel soon found that some of its customers, those who would normally pay 250 (or 350), paid only 200. That is, there was leakage of the 250-paying customers into the 200 category with a less-than-anticipated increase in volume.

38 The lower rate did entice new customers for whom the 250 rate had been too high. However, the rate fence was still ineffective because the increase in demand was not enough to offset the lost contribution from 250-paying customers who were able to pay 200. The figures above illustrate the problem. The area to the right of 150 is new demand created by the 200 rate. Leakage can occur from two regions. First, the area below 250 and above 200, between 150 and 100, consists of some customers who are willing to pay 250 but now pay 200. Second, the area above 200 and below 350, to the left of 100, consists of some customers who are willing to pay 350 but now pay 200 (some of these customers may have also been paying 250 if the restrictions on the 250 rate were also imperfect). A company may choose to decrease its average price as a strategic move, but it should do so only if it can increase its RevPAR. If a hotel lowers its rate and its nearby competitor does the same, it will maintain the same market share but at a lower ADR. A company may choose to lower its average price as a strategic move, but it should do so only if it can realize a significant increase in occupancy. That is, it can lower its the ADR but must also increase its RevPAR. Firms too often structure restrictions in an effort to attract lower-value consumers. That is, they try to grow demand instead of attempting to extract the consumer surplus by getting current guests with higher willingness to pay (WTP) to pay closer to their WTP price. To extract customer surplus, firms use fences such as value-added packages that include free breakfast or Internet and are priced higher.

39 Empirical evidence suggests that firms pricing higher than their competitors tend to receive a RevPAR premium--the occupancy decline is more than offset by price increases. The adjoining figure summarizes data collected by Smith Travel Research (STR). The figure is based on data collected from 6000 properties over three years. The chart, comparing the annual ADR (horizontal axis) to occupancy and RevPAR (two series graphed) shows that avoiding lowering prices with imperfect fences (maintaining higher relative prices) may be a better strategy in certain circumstances. Obviously these results are not representative of all firms. Well-designed pricing and discounting efforts can increase RevPAR if companies are careful to avoid leakage. STR tracks supply and demand data for the hotel industry and provides market share analysis data. For further details on the data and study summarized in this figure see "Competitive Hotel Pricing in Uncertain Times," by Cathy A. Enz, Linda Canina, and Mark Lomanno. View the article. Note: you will need Adobe Reader to be able to view the article. If it is not already installed on your computer, you can download it (free) from the Adobe Web site.

40 Combat Market Dilution or Leakage Historically, major airlines have used rate fences to create segmentation. These fences included 7-, 14-, and 21-day advanced purchase restrictions, a round-trip purchase, and a Saturday-night stay. See Table 1. Fare Code Dollar Price Advance Purchase Round Trip Sat. Night Stay Percent Nonrefundable Y $ B $200 7 day Yes % M $ day Yes Yes 100% Q $ day Yes Yes 100% Table 1 Segmented Fare Classes In response to low-cost airlines that operated point-to-point one-way flights ( such as JetBlue), major carriers began to allow customers to combine two one-way tickets to create a round-trip ticket and eliminated the Saturday stay requirement. As a result, major carriers could no longer segment customers based on one-way flights or itineraries that had a Saturday night stay. Dilution started to occur because segmentation was not perfect. Customers who were willing to pay more were able to buy lower-priced fares because the restrictions (embedded with lower fares) no longer inhibited their purchases. Airlines saw the demand for B class move down to M class and people willing to pay $200 paying only $150. See Table 2. Fare Code Dollar Price Advance Purchase Round Trip Sat. Night Stay Percent Nonrefundable Y $ B $200 7 day % M $ day % Q $ day % Some airlines have been more successful in reversing this trend than others. Air Canada, for example, created more innovative restrictions by giving each fare class a name to which people can relate, in essence branding the product classes. They moved away from four fare classes--y, B, M, Q--and created five classes. The new fare classes are called Tango, Tango Plus, Latitude, Executive, and Executive Flexible. Each class presents the customer with a set of attributes rather than just a price. For example, customers who select Latitude class earn more bonus miles for travel than Tango class and they have access to priority check-in. Another distinction is access to the airline's lounge. The Executive classes are not charged incremental fees; Tango through Latitude classes are charged. Table 2 Reduced Segmentation This segmentation is not very different from what we typically expect from an airline product, but now it's associated with a name instead of a price. By simply giving the classes names and assigning them different qualities (cancellation fees, loyalty miles, advance check-in, etc.), Air Canada branded the fare classes and created more concrete differentiation. It

41 wanted consumers to ask themselves: "Is it worth selecting this to get my miles? Is it worth selecting this to get priority check-in?" Now consumers are selecting based on attributes as well as price. This has led to significant revenue gains for Air Canada.

42 Grand Casino de France Auditorium Seating Transcript: Grand Casino de France Auditorium Seating The Grand Casino to France has recently added a 20,000-seat auditorium in which their guests and others can enjoy internationally acclaimed performances. Currently, they are charging 200 per seat, but rarely do they ever sell out a performance. The casino is looking for some help in setting future prices. The auditorium is divided into three zones, zones A, B, and C. Zone A is the most desirable with a capacity of 3,000 seats. Zone B, the second most desirable, has 12,000 seats. And Zone C, the least desirable, has 5,000 seats. At their current price of 200, Zone A has a demand of 10,000, Zone B has a demand of 6,000, and Zone C has a demand of 2,000. As you can see, other than Zone A, there is surplus capacity in Zones B and C. They've engaged a marketing research firm to help them understand consumers' responses to price changes. Specifically, they've looked at three prices, that is the current 200, as well as decreasing down to 100, and then increasing up to 300. For Zone A, demand at 200 is 10,000 seats. If they were to decrease price to 100, demand would increase 100 percent or double to 20,000. Similarly, if they were to increase price from 200 to 300, then demand would decrease by 30 percent, decreasing from 10,000 to 7,000. Similarly, for Zone B, the base demand of 6,000 at 200 will double to 12,000 at 100, and then shrink to 50 percent to 3,000 at 300. Lastly, for Zone C, demand is very price responsive for Zone C, and we'll see here that if they drop price from 200 to 100, demand goes from 2,000 to 6,000 seats. Similarly, if they increase price from 200 to 300, demand is exhausted and goes to zero. So the question that we face is which of these prices should they be using, 100, 200, or 300? Should they have the same price across the entire auditorium? Should they have one price that's potentially different for each of the different zones, or at the extreme, should they have multiple prices for each of the zones? Instead of just selling at one price per zone, perhaps sell at both 100 and 200 in each of the zones. We're going to look at how we might tackle these questions knowing how responsive demand is to price. If we think about sales and revenue at a single price, let's focus on 100. We know that base demand was 10,000 for Zone A, doubling to 20,000 for Zone A at 100. Given that capacity is only 3,000, that means that even though demand is 20,000, we can only sell 3,000 seats. So 3,000 at 100 translates to 300,000 in revenue. For Zone B, if we were to price it at 100, the base demand of 6,000 would also double to 12,000. Capacity is actually 12,000, so we can meet all demand and generate 1.2 million in revenues. Lastly, for Zone C, if we were to decrease price from 200 to 100, demand triples from 2,000 to 6,000, and given that capacity is 5,000, we can only sell those 5,000 seats at 100 for a total of 500,000 resulting in a total revenue across all three zones of 2 million.

43 Now, let's go one step further and have fixed prices per zone, but potentially different prices across the zones, so one level of variable pricing. For argument's sake, let's set a price of 300 in Zone A. We know that at 300, demand decreased 30 percent from 10,000 down to 7,000, but we still only have 3,000 seats, so we're going to have sales of 3,000 generating 900,000 in revenue for Zone A. For Zone B, if we were to price at 200, our base demand of 6,000 stays the same, which generates 1.2 million in revenue. If we were to set a price of 100 in Zone C, remember our demand now went from a base demand of 2,000 to 6,000, but capacity is only 5,000 for Zone C, so we can only sell 5,000 seats even though demand is 6,000. Those 5,000 seats at 100 are generating 500,000 in revenue for a total of 2.6 million in revenue across the entire facility. Again, it's 2.6 million, higher than our 2 million at a constant price of 100 across the facility. Now, we can go one step further. Basically, we can have variable prices within a zone as well as across the zones. What this means is that Zone A may have a different price than Zone B, but Zone B may have multiple prices. If we remember back to our step one where we had our base demand and we looked at how that demand changed as a function of price, our base demand at 200 was 10,000, 6,000, and 2,000 across the three zones. That demand went to 20,000, 12,000, and 6,000 across those three zones at 100, and then decreased to 7,000, 3,000, and nothing at 300. Keep in mind our capacities are 3,000, 12,000, and 5,000 across each of those three zones. If I look at demand for Zone A at 300, that demand of 7,000 is greater than capacity, so life is easy for Zone A. We would simply just price at 300, our highest price and it clears all our inventory. Zone B is a little trickier. For Zone B, we had demand of 3,000 seats at 300. If we also priced at 200, remembering total demand at 200 was 6,000, but if we were to price it at 300, we've shaved off that top 3,000 initially. That remains the 6,000 minus the 3,000 and results in demand for another 3,000 seats at 200. Similarly, total demand at 100 was 12,000 for Zone B, but we've already sold 3,000 at 300, another 3,000 at 200, which leaves 6,000 seats of remaining demand at Zone B. If we look at Zone C, we had demand of 2,000 at 200 and demand of 6,000 at 100. If we were to price at 200, we would sell those 2,000. If we were also to price at 100, then we would have the remaining 4,000, which we could sell at Zone C. Keep in mind for Zone C, total capacity is only 5,000, so even though demand was 4,000 for 100 at Zone C, we're only going to be able to sell 3,000 of those seats owing to that capacity constraint. So the question that remains is how should we price. We've looked at three levels of complexity. For each of those levels of complexity, we have a set of optimal prices. If we were to set one price for the entire auditorium, what would that price be? Would it be 100, 200, or 300? We can go through that exercise and calculate total sales and resulting total revenues at 200, compare that to our 100, and do that again if we price at 300 and compare that to 200 and 100, and then decide which our optimal single price is across the facility. Similarly, if we focus on one price per zone, with those prices in each zone potentially being different, then what should the Zone A price be? What should the Zone B price be, and what should the Zone C price be? Earlier, we looked at a Zone A of 300, a Zone B of 200, and a Zone C at 100, but potentially, those aren't the revenue maximizing prices. Lastly, if we had multiple prices in each of the zones, what should those prices be? We went through the total demand and total sales of each of those prices. What's the resulting revenue as a function of those prices, and how does that compare to our first two cases?

44 Auditorium Pricing Exercise-Review In the previous exercise you analyzed revenue using different pricing strategies. You may download this spreadsheet that displays how we calculated the answers to the questions.

45 TOPIC OVERVIEW Topic 1.2: Communicating Prices How firms display or list their prices dramatically influences what customers buy and how much they spend. Although our lowest price may dominate our marketing communications, ideally we don't always want customers to pay the lowest available price. Additionally, most firms in the hospitality industry attempt to up-sell a customer to generate more revenue. A hotel may try to upgrade a standard room to a suite; a car rental agency may upgrade a customer to a luxury car or try to sell amenities such as a refueling package. You need to understand prospect theory to know how to display prices to discourage purchase at the lowest available price and to understand how to up-sell using upgrades to increase revenue. By the end of this topic you will be able to: Evaluate how prospect theory influences buying patterns Use prospect theory to structure pricing communications

46 Prospect Theory How you answered the previous poll illustrates an economic theory referred to as prospect theory. If you were to use a purely logical approach to answer, you would pick either A in both situations or B in both situations. In most cases, however, a significant number of people switch their preference from A to B or B to A as they move from question 1 to question 2. Quite often, people choose to receive the cash outright rather than take their chances at the game in question 1, but they take a substantive risk at a potentially large loss rather than knowing for sure that they are going to lose money in question 2. This finding is interesting because, logically, if you are taking a 50:50 chance at the game in question 1, you should be willing to take an 80:20 chance to play the game in question 2. Prospect theory (Kahneman and Tversky, 1979) argues that consumers make decisions based on the potential value of a loss or gain compared to a reference point, not compared to the actual value of the good or service (value is associated with anticipated changes in well-being). According to prospect theory, losses have more emotional impact than equivalent gains. The figure to the right illustrates the perceived impact of a $50 gain versus a $50 loss. Notice that the changes in state of being (positive or negative value) are different for the same absolute change: the negative value of a $50 loss is perceived to be greater than the positive value of a $50 gain. The figure also shows that the marginal change in well-being for gains is different than for losses. Changing from $110 to $120, for example, is almost as pleasurable as (actually, slightly less than) going from $10 to $20. Losses, however, tend to exhibit much stronger decreasing marginal impacts. Losing $10 is painful when going from $20 to $10, but the incremental pain felt when going from $110 to $100 is considerably less. Thus, once a consumer has agreed to pay a certain amount of money, getting the consumer to pay a little more is not difficult. D. Kahneman and A. Tversky "Prospect Theory: an analysis of decision under risk," Econometrica 47:

47 Ways to Communicate Transcript: Ways to Communicate So what we're going to do first is focus on three of the key aspects of prospect theory that relate to pricing. First: Letting consumers know the trade-offs of not booking. Basically, trade-offs of potentially paying higher prices if current prices become unavailable. Second: Realizing that gains are looked upon differently than losses. And then lastly: Once consumers have agreed to spend a certain amount, it's relatively straightforward to get them to pay a little more in subsequent transactions. So let's look at a potential airline display. This airline display is a very common display where I've searched for a set of departure and arrival dates, and I've also indicated that I'm flexible to travel in and around those dates. So what the airline has provided me is my base price in the middle of the matrix, as well as prices around my travel dates, allowing me to visualize those tradeoffs-that if I so choose to travel on these days, this is my price, but if I'm flexible I can move to lower prices. Or if I wait, I may have to pay higher prices for later departure or arrival times. We can look at a different airline display. Similar to our last airline display, this airline display has, across the top, different prices for different travel dates, but then below that, they have different prices for different flights within that travel date-so each one of these rows is a different departure time on that same day. But then within each one of those departure times, there's a series of different prices across the different products. So they have unrestricted products, and then they have business products, and a full spectrum in between, showing how prices increase across that spectrum. So allowing consumers to make those tradeoffs across potential itineraries and potential travel dates. Now interestingly, this is a third airline display. While initially, this display may look a lot like our last display, there's something that's fundamentally different here. As we go down the rows, we see that we have different departure times, like we have in our last display. But as we go across the columns, what we see here versus our last display is that these prices are decreasing from left to right, whereas before, our prices were increasing from left to right. So as I read across the screen-so as you're looking at this online, as you're reading it across your screen-then prices are decreasing. So this is a very different display than our last one. In addition to that, they're also providing some information of what product classes are unavailable-so creating this sense of urgency of booking now as part of the prices become red or zoned out, and unavailable. Prospect theory here would indicate that now as the consumer has sort of put his reference price on the first column price-the higher price-and then as he moves across the columns, those different prices are perceived as gains as prices decrease, whereas in our last display, the price on the most left-hand side was the lowest price. And as I moved

48 across the different price points, each one of those incremental price points was perceived as a loss as the prices went up. Given that gains are perceived differently than losses, the consumer is more apt to book at a higher price, with our high-to-low display, than they are with a low-to-high display. So this is some of the key aspects of something as simple as how we show these prices-are we going to get people to buy up versus always buy that lowest available product. So this sort of keeps in mind that when we're sort of thinking about quoting rates, we need to be going from high to low. This is something that we've cognizantly done at the call center or over the phone for years, but have really sort of resisted to implement online. We're basically communicating that we need to do those same strategic behaviors that we've seen on the phone, online when we sort of communicate those prices. This would be a standard hotel-related display. What we see here is a display that's linked to logic-logic by room type or package type-and not really fully capitalizing on prospect theory, in that prices are not monotonically increasing or decreasing. They're structured by product categories, and not fully capturing sort of the implications of consumer behavior upon how we set those prices, really leaving a lot of opportunities out there for the more innovative user of how they post those prices.

49 Reference Pricing You are at a restaurant and the waiter hands you a wine list with two options for the house merlot: Flying Goose Merlot 35 Flying Goose Merlot Reserve 45 Which wine do you choose? You're at the same restaurant and you receive this this modified wine list: Now which wine do you choose? Flying Goose Merlot 35 Flying Goose Merlot Reserve 45 Flying Goose Merlot Premium Reserve 55 The vast majority of people who select the 35 wine from the first list switch to the 45 wine in the second list. This is an example of reference pricing--the customer purchases the wine based on the price in relation to the other listed prices rather than to the wine itself. The way a business communicates prices (as well as the options available) influences our choices. Reference pricing is paramount in prospect theory. A reference price can come from a variety of sources. Memories of past prices What consumers have paid in the past for similar products. For example, if the customer paid 35 for a midsize car rental in Nice he might expect to pay the same amount a month later. Prices set by brand leader If McDonald's charges $1.20 for a hamburger, customers expect to pay about the same at another nearby fast food restaurant. Price of related products and services If airline coach travel from London to Paris costs 350, that helps create a reference price for airplane tickets for similar flights. The way the price is presented For instance, a firm may advertise a product available for four simple payments of 25 rather than one payment of 100. Another approach is strike-through pricing: the old price has a line through it with the new, limited-availability, lower price beside it, as you can see in the ad below. This creates a sense of urgency to purchase. The ad in the illustration showing the reference pricing with strike-through pricing presents a gain, and the sale tag "Hurry! Offer ends soon!" and "Only 4 rooms left at this price" creates some urgency and potentially increases the likelihood that the consumer will book.

50 When a firm reduces the offered price below the reference point, the customer views this as a "gain"--the customer "gains" more for the offered price. On the other hand, if the firm increases the offered price from the reference price, the customer views it as a "loss." Perhaps one of the major implications of reference pricing centers around universal discounting. During a downturn, firms often lower prices, and if a competing firm matches these prices, then the market price decreases. In essence the reference price for this market has now decreased. When demand picks up, consumers are accustomed to these lower prices, and it takes considerable time to increase prices as demand increases. It is much easier for firms to increase prices if they avoid reducing the reference price. One example of stimulating price-sensitive demand while minimizing reference price effects is the tactic of offering a free night with the purchase of multiple nights at the standard rate- Stay 3 nights, get the 4th night free. In this example the hotel effectively drops prices 25% for a four-night stay, yet the posted price or reference price is still the original price. If demand is price sensitive, it should respond to our increased value offer.

51 TOPIC OVERVIEW Topic 1.3: Upgrades Offering upgrades can be a strategic revenue-producing strategy if you know how and when to offer them to customers. To create an effective upgrade strategy, you must understand how your customers make purchase decisions. By the end of this topic you will be able to: Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers

52 Prospect Theory and Upgrading One of the most common applications of prospect theory happens daily in the hotel business. Hoteliers use prospect theory every time they attempt to up-sell guests to a better class of room or add some amenity for a small fee. These up-sells may be offered at check-in or online. With both approaches, the offer can be separated from the original purchase decision. For example, using the online approach, the upgrade offer appears after the customer selects the purchase and navigates to the checkout screen. The success of this strategy rests on one of the key tenets of prospect theory-it is easier to get customers who have already committed to purchase to spend an additional amount (the amount of an upgrade, for example) than it is to get them to make the more expensive purchase at the initial decision point. Many airlines use this strategy during both online transactions and check-ins at the kiosk. They may ask customers if they want to upgrade to business class or to a refundable fare for an extra charge. This example displays how one firm communicates the benefits of the upgrade (gain) before stating the fee (loss). Some strategies to gain revenue through online upgrading: Put time limits on the purchase; for example, "Act now to receive a free upgrade to a King Suite" or "Price good until 8 PM!" Clearly state how much the customer is saving (gaining) by purchasing or upgrading now. Using a strike-through is a good way to do this. Offer the upgrade at "checkout." Many Web site designs can provide offers for items related to the consumer's purchase in the Web site's pop-ups, banners, or sidebars once the consumer is at "checkout" or is checking the "shopping cart." This approach effectively uncouples the purchase and upgrade decisions.

53 Upgrading Online Transcript: Upgrading Online Now, we're going to focus on what I refer to as online upgrades and a further use or implementation of prospect theory. Prospect theory indicates that it's relatively easy to get consumers to agree to spend a little bit more given that they've already spent something. We would refer to this as the upgrade or the up-sell. You might think of it as getting nickeled and dimed to death. This is relatively easy to do at the front desk, but how do we do this online? You can think of a guest who is checking in late at night. The last thing they want to do is go through an up-sell at the front desk, so how do I move some of that upgrading process into the electronic world? What we can refer to here is the idea of the postconfirmation, nonguaranteed upgrade. Postconfirmation basically means the guest has already booked their reservation online, has received their confirmation code. Given that we're going to do this upgrading process 30, 60, or 90 days before check-in, we don't know what demand is going to happen in the next 30, 60, or 90 days. We want to offer this on a nonguaranteed basis. Basically, the supplier has the option, but not the right, to grant this upgrade. The consumer sees this offer, either accepts or rejects the offer, and then the supplier later, once demand has been realized, can also decide whether or not they want to accept or reject this offer. If we look at how this would be facilitated online, I've made my reservation, I'm at the hotel's Web site, and I've made my reservation. I receive my confirmation code. There might be a link to a discounted offer. It's important to communicate that this discounted offer is an offer but not a guaranteed offer. If the user clicked on this nonguaranteed offer, they would see a subset of potential upgrades. Maybe for $20 or $40, they could upgrade to one class of room. For $80, they could upgrade to two classes of room, and then for a higher price, they could upgrade to some sort of suite. It's important that you communicate to the user that what this upgrade is is a request for an upgrade. It's not a guaranteed upgrade. We may also send this upgrade offer via as well as right after that purchase decision. To allow for a separation between purchase event and upgrade event, we may later go through this process again, but via , so sending that confirmed guest an . Within that , we have this same offer. One of the things to remember is we can also send these upgrade offers to members of our loyalty programs. Presently, most of your loyalty program guests are probably expecting a free upgrade. What we would do is simply send them a set of offers, maybe three potential upgrade offers, and the first one would be free. Here we're communicating, this is your base-level upgrade. It costs you nothing, but here are two other higher levels of service, which are incrementally more expensive. Here's a great way to communicate that we value your service, and here's what we're going to upgrade you to

54 for free, but just in case, here are a couple better classes of service and an opportunity for you to even extract further revenues from these high-valued guests.

55 Benefits of Upgrading Consumers are often motivated to upgrade a product or service by the desire to get the best-quality product or service for their money. In addition to providing benefits for consumers, upgrading can increase profits and improve guest loyalty for sellers, and online upgrading also offers ease of implementation and management. Increased profits Organizations may increase profits by using properly structured upgrade strategies. Upgrades provide the opportunity to increase profits dramatically by selling off product lines that are generally undersold. After you have effectively segmented your product line, upgrades help you combat against people buying down to lower rates or lower-priced products. Even if the upgrade is steeply discounted or free, the next time that consumer comes to buy, he or she is more likely to purchase the same grade of product or class of service that the previous transaction was upgraded to in the past. Generally, people price shopping online are looking for a deal. Customers perceive the offer of an additional product or a discounted luxury item as a gain, and that can lead to a revenue boost for you. Improved customer loyalty Upgrading can help an organization improve guest loyalty. An effective upgrade strategy can strengthen guest relationships and loyalty by providing increased value. Also, because you are exposing your premium product or service to a wider audience, you increase future demand. At the front desk, you could upgrade a returning guest to free up a room valued at a lower amount. This helps develop brand loyalty by rewarding guests who stay frequently with a complementary upgrade to a higher-priced room. An online upgrade or loyalty system can further increase both your revenue and your customers' satisfaction. Online, you can show loyal customers what their loyalty will provide them in the form of a free upgrade. You can then show them the next greater upgrade, which they can purchase for a small fee. You can extract more revenue from your loyal customers by converting your top-tier loyalty consumers from complementary upgrades to paid upgrades. At the same time, you keep them happy by providing what they view as a gain: a nicer, better product or service, for just a little more than they originally planned to spend. Exclusive online "clubs" for frequent buyers and loyal customers are another way to use upgrades to improve loyalty and increase revenue. You can offer members of these groups perks such as free meals, discounted rooms for their birthdays, percentage-off discounts on their purchases, or guest passes for friends and family to encourage new consumers. Prime examples of using upgrade programs to increase loyalty are frequent-flyer airline programs. These programs provide free flights, free upgrades to first and business class, free drinks and meals, and many other benefits to increase customer loyalty; they increase revenue by requiring a certain number of purchases (ensuring that the customer will keep coming back) to earn the benefit. Easy to implement and manage online Online upgrade programs additionally provide the benefit of easy implementation and management. If it's online, you don't have to train people to solicit the upgrade purchases. Generally, with online upgrade programs, you incur no up-front charge for setup, implementation, or maintenance, and you have final authority over the upgrade and pricing structure. An online solution requires minimal daily management and demands little implementation time or effort. You can quickly generate additional revenue at little to no cost.

56 Upgrading at Ideal Car: Review In the last practice exercise you determined how many cars Peter should keep for "true" luxury customers. If you had trouble with the exercise, please review this spreadsheet with the completed analysis and try the quiz again.

57 Module Wrap-Up You should now understand how we use variable prices to increase the breadth of consumers we reach and to increase our profit. We discussed how we can employ prospect theory to encourage buy-up and to avoid market dilution. All these tactics are aimed at having a menu of prices available at any given time with the goal of increasing our average selling price. Having completed this module, you should be able to: Describe the benefits of variable pricing Use variable pricing to maximize profit Evaluate how prospect theory influences buying patterns Use prospect theory to better structure pricing communications Assess how prospect theory affects upgrade decisions Discuss the benefits of upgrading customers

58 MODULE INTRODUCTION Module 2: Dynamic Pricing and Segmentation If performed properly, dynamic pricing (adjusting prices throughout the booking window in response to demand) complements price segmentation and leads to increased overall revenues and profits. If performed poorly, dynamic pricing can erode revenues and encourage consumers to become strategic or to time their purchase in an effort to obtain goods or services as cheaply as possible. In this module, we discuss how dynamic pricing can be paired with segmentation to increase profits and avoid leakage. By the end of the module you will be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations Predict how customers will react to dynamic pricing Discuss how to best structure prices available online

59 TOPIC OVERVIEW Topic 2.1: Booking Curves Dynamic pricing requires an understanding of how prices evolve over time. It's possible to build that understanding by tracking the evolution of demand using booking curves. In this topic, find out how to use dynamic pricing to create a successful pricing strategy. By the end of this topic, you will be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations

60 Variable Pricing Versus Dynamic Pricing We've been discussing variable pricing, but let's compare that with a different way to set prices: dynamic pricing. Variable pricing for a particular product or service involves setting multiple price points for distinct market segments. The prices are preplanned, and all prices could potentially be offered simultaneously. For example, on June 3, a customer checking room prices at the Milton Hotel for a July 3 stay may find that a single costs 135, the double costs 157, and the king suite costs 200 per night. These are preplanned, variable prices for a room in that hotel. By contrast, dynamic pricing involves an expectation that prices will change over time in response to demand uncertainty. Usually you decrease price in an attempt to stimulate demand and increase price in response to strong demand. For example, on June 3 a customer calling the Milton Hotel to request a king suite for July 3 (one month from the request date) may receive a quote of 200 per night. Another customer calling on June 25 to request a king suite for July 3 (one week from the request date) may receive a quote of 250 per night. That's dynamic pricing: the same room sells for different prices depending on the date of purchase. The airline industry is often cited as a dynamic pricing success story. In fact, it employs the technique so artfully that most of the passengers on any given airplane have paid different ticket prices for the same flight. On a flight from Ontario, Canada, to Los Angeles, the traveler in seat 7A may have paid $470, whereas the traveler in 7B may have paid $640. The difference in ticket price depends on when these passengers booked their flights.

61 Introduction to Booking Curves Transcript: Introduction to Booking Curves So as we move from variable pricing to dynamic pricing, remember that dynamic pricing is the evolution of those variable prices over time. What that requires is for us to have some idea of how demand is going to materialize over time. And booking curves are our most common form of understanding how demand is evolving over time and hence what are the opportunities to capture with a dynamic pricing strategy. Booking curves are relatively straightforward to construct; they are basically the average reservations on hand, for different days before arrivals, so some sort of snapshot of how demand typically materializes over time. So typically on the right-hand side we have 90 or 120 days before arrival and then over time demand picks up as we get closer to departure for a plane or check-in for our guest. So this basically shows the evolution of reservations as we get closer to the service date. So we would typically have different booking curves for different segments, or more specifically, each segment should have a different booking curve, so we would have different booking curves for our product classes or rate classes, different booking curves for length of stay, and different booking curves for day of the week. One could argue that if the booking curves are not distinct then those are really not distinct segments because they are booking in the same fashion. And so ideally as we compare these booking curves from one product class to another, we would expect them to have different shapes and different levels of materialization and that would sort of tell us that these are potentially different segments. One extreme might be comparing your discounted booking curve versus your full-fared booking curve. And as this particular example shows, here we have our discount demand coming in relatively early, and we have our full-fare demand coming in relatively late. So what this tells us is that my discount rate can be available probably all the way up until three, four, or five days before check-in and I have very little potential for dilution. Very unlikely that a full fare customer is going to arrive and purchase a discounted product because those full-fare people are not in the market yet, their booking curve says they really don't start to pick up any traction until somewhere around four days before arrival. And so this tells that if we're going to have prices evolve over time that we could have our low price out there right up until about five days before arrival and then if we kept our low price in the market after five days, we run the risk of dilution of our high-priced demand buying down to that low-priced product.

62 How Booking Curves Are Created One of the most important sources of data we have to support dynamic pricing decisions is booking curves. When we look at them, one goal is to be able to determine how people book over time, and then compare the booking behaviors of different segments over time. We define segments by such factors as rate class, length of stay, or channel (that is, through an online travel agent site or by word of mouth). Ideally we construct booking curves for all segments i n an effort to identify possible leakage or demand losses if we change prices (that is, if we employ dynamic pricing). Booking curves provide insight into pricing opportunities and also show when dilution may be a problem. Table 1 displays the ROH for the day of arrival (0) and 7, 14, 21, and 28 DBA over the course of five stay dates (say the last five Mondays). At the bottom of Table 1 we calculate the Average ROH for each of the DBAs (0,7,... 21); we also display the average as a Percentage of Average ROH at arrival (DBA 0). Table 1 Table 2 shows the calculations used for the Average ROH and the Percent Average ROH. In this table, we calculate Average ROH by entering the formula =AVERAGE(B3:B7) in B9 and then copying that formula to cells C9 through F9 (C9:F9). To calculate the Percent Average ROH, we entered the formula =B9/$B$9 in B10 and then copied it to C10:F Table 2 To facilitate decision making, we convert this data from a matrix into a graph or booking curve. The booking curve graph makes it easier to visualize the booking pace at the firm. To create a booking curve of the Average ROH for the DBA: Use your mouse to select cells B9:F9 Locate the Insert chart option on your version of Excel Select the Line graph option

63 Right-click the line graph, click Select Data Click the x-axis labels and select cells B2:F2 and click OK Figure 1 shows this graph Figure 1 We most often use booking curves in combination, to compare one rate class to another or one length of stay to another, for example. Because one rate may have substantively more (or fewer) bookings than another, it's best to use percentages of the averages. You find this percentage by dividing all the averages by the maximum average ROH. In Table 1, we divide the averages by 163 (the maximum average on the day of arrival). Now, instead of graphing the averages, we create the booking curve by graphing the percentages. To create a booking curve of the percent average ROH for the DBA: Use your mouse to select cells B10:F10 Locate the Insert chart option on your version of Excel Select the Line graph option Right-click the line graph, click Select Data Click the x-axis labels and select cells B2:F2 and click OK Figure 2 shows this graph Figure 2 If we had data on multiple segments, we could then plot these booking curves (as percentages) on the same graph to compare when each booked. If you do this for your own hotel and you don't find any major differences among the graphs, then perhaps you need to revisit your segmentation!

64 In the following exercise, you download a spreadsheet that includes detailed instructions for creating the booking curves and you create your own booking curve.

65 Create a Booking Curve-Review If you had difficulty creating a booking curve for Hotel Ithaca, download the Hotel Ithaca spreadsheet to view a correct booking curve and to find out how the curve was created.

66 Using Booking Curves Transcript: Using Booking Curves So we're going to further continue our discussion on booking curves. Here we're going to focus on how to use these booking curves to understand segments, and at some level control inventory. So here, what I'm gonna show is a series of booking curves for demand into the Hawaiian Islands. And this is specifically demand that's generated at an online travel agent. Each of these graphs is going to show three different series: a solid line, which is a package product. A package product would be someone purchasing a hotel room and an airline seat together-as one product. We have the dotted series, where the consumer is purchasing their hotel room opaquely-so that basically means they know it's a four-star hotel, they don't know which four-star hotel. And then lastly, the dashed line is a consumer who's purchasing just the hotel room-so he's not purchasing air along with that hotel room-just the hotel room. So what we see here is the opaque product and the hotel-only product seem to exhibit the same booking characteristics-the shape of the curves is relatively the same. What the solid line shows is our package purchases are those consumers who are purchasing both air and hotel together. Its distinct shape from the hotel-only product indicates that these consumers are in the market much earlier than those looking for just hotel room only. Specifically for the package, roughly 90 percent of those purchases are made prior to 14 days before arrival. So here's a nice way to segment. You know that people who are in the market early-the price-sensitive consumers-are more likely package purchasers. So you could have a discounted hotel rate as part of a package, and have your higher-price hotel rate as part of a nonpackage product. But if we look at those same curves in a different way-so here, see we have the same three curves-package, hotel-only, and opaque-but now we look at a short length of stay. So what we see here now is that these booking curves are not all that distinctive. So this is a guest who's staying one, two, or three nights. If we compare this graph to our next graph, which shows those same three curves but for a longer length of stay, we see here that a large part of the segmentation is length of stay, and not necessarily the purchasing mechanism. If someone is purchasing a week, that they tend to purchase that further in advance than someone who's purchasing two or three nights. So one could sort of think about the segments here, the individual flying into the Hawaiian Islands for two or three nights is probably a business traveler, whereas the consumer flying into the Hawaiian Islands for seven days or longer is probably a leisure traveler, is in the market earlier for more discount prices. So in addition to segmenting by package versus hotel-only, we can augment that with short and long length of stay. If we compare and contrast this across product quality-so here we're going to go through a series of booking curves-each of these booking curves is for a quality of service. Initially here we have one- to two-and-a-half-star hotels. Our next graph

67 is three-or four-star hotels. What we see here is that the behavior is consistent across the different channels, across the stars. So stars-star quality-is not as prolific a segmenter as, say, the channel or the length of stay. So in summer here we saw that length of stay was a good segmenter, also that package versus hotel-only was a good segmenter. These are very logical, and we're just confirming that logic by looking at our booking curves. So quite often booking curves are simply testing some of these logical hypotheses that you have put forth from a marketing standpoint.

68 TOPIC OVERVIEW Topic 2.2: Strategic Consumer Behavior To create an effective dynamic pricing strategy, you must understand consumer behavior. With the availability of online tools, today's consumers are more strategic in their purchasing decisions than ever before. It is therefore critical that firms understand their customers' decision processes and the tools they are using to make those decisions. This information can be used to strengthen the firm's dynamic pricing strategy. By the end of this topic, you will be able to: Predict how customers will react to dynamic pricing Discuss how best to structure prices available online

69 Consumers and Dynamic Pricing Dynamic pricing by definition indicates that prices, in response to demand, evolve over the booking window. As dynamic pricing becomes more commonplace, consumers may learn to anticipate price changes and attempt to time their purchases to get better prices. They may see that, in general, prices do not change monotonically (that is, prices do not either consistently increase and never decrease or consistently decrease and never increase) as the service date approaches. The accompanying figure shows a typical price curve for many service firms deploying a dynamic pricing strategy. As the curve shows, prices often are higher early in the booking cycle, decrease in reaction to demand uncertainty, and then increase in the final few days or weeks prior to service, in response to later-arriving business travelers with greater willingness to pay. Such a price curve works well when Risk-averse consumers willing to pay a higher rate book early to ensure they get access to service (perhaps for an annual vacation) Consumers looking for a discount book in the midrange time frame-for an airline typically two to six weeks prior to departure Late-arriving consumers exhibit greater willingness to pay owing to their need to travel and their inability to have flexible plans or plan in advance When customers follow this pattern, firms can close discount fares or rates after a certain time period and increase rates as the service date approaches. But the use of dynamic pricing may change consumer behavior. If consumers anticipate price changes, they may postpone purchase decisions even though they may be happy with current prices. Before price-shopping moved online, it was difficult for consumers to compare prices across firms (to compare airline A to airline B, for example) and over time (comparing today to next week, for instance). Now it is becoming increasingly easy for consumers to see how prices evolve over time. The Internet makes it easy for buyers to look at the pattern of pricing and demand and to evaluate where pricing currently is in the U-shaped curve. As a result of these nonmonotonic prices, consumers are perpetually checking prices to try to get the best deal. As a service provider, you want to encourage customers who are willing to purchase from you to decide right away, not to wait for a better price. If the customer does not decide right away, he or she may get access to lower prices later. If your prices don't decrease and your competitor's prices do, you run the risk of losing the customer.

70 Strategic Consumer Behavior-Airlines Transcript: Strategic Consumer Behavior-Airlines All right, our focus today is going to be on strategic consumers, and ultimately their impact upon segmentation, and then how that leads to pricing. So historically, if we think about how prices evolve for a particular airline flight-so that flight might start going on sale six months prior to departure. Then if we look at how those prices evolve as we get closer to the plane actually departing, those prices have historically looked like a very squished "U." Where early on, prices are relatively high, as we get closer to departure they decrease, and then ultimately they increase as we get to the last two or three weeks prior to departure. But more recently what's happened is a series of information providers which potentially has some implications upon that price curve. The first we'll focus on is Bing-so, Microsoft's search engine. If I was to perform a search on Bing for a flight-so here's a flight from Newark to San Francisco-so not only do they provide me with information on that flight, they also potentially suggest some alternative routes. So instead of flying to San Francisco, maybe I want to fly into San Diego or Sacramento. Instead of flying from Newark, maybe I want to fly from LaGuardia. So they're already leading me to other routes that may be more price-competitive. In addition to that, when I actually focus on my route, they show a set of prices, but then they also provide to me a barometer of where they think prices are going to go-"should I wait, or should I buy now?" Basically, they come up with a probabilistic estimate of whether or not they think prices are decreasing. If they think prices are decreasing, then we should wait; if prices are increasing, then you should buy. So really sort of providing some insight into that movement of prices, i.e., where are you in that sort of flattened out U shape. If we think of the other big search engine-in this case Google-Google has a similar product called "Flights." Little bit different than Microsoft, but they basically provide an array of flights for different origins and destinations. But they also provide some metrics on if your travel is flexible, if you can adjust your departure dates, they'll provide this sort of graph of how those prices are evolving at these different departure dates. So if you're flexible in your travel plans, then maybe you should choose an alternative time to fly, basically trying to pick a spot in that U for different departure dates. They also allow to sort of simplify that set of flights that you look at into what we refer to as an "efficient set"-so basically flights that are short and cheap. So we can sort of look at a two-dimensional view of prices. So I only want flights that are less than ten hours and that are less than $ So I don't consider flights outside of that set. So what's the implications of this? Well, if we think of the information provided by these two search engines, and then if we think about that U-shaped set of historic prices, well really, we're not going to achieve some of that desired segmentation. If we were pricing relatively higher early on in the sort of selling window, so back at six months maybe to three months before departure, and the consumer is now privy to this information from these information providers-that prices are

71 decreasing and that they should wait-then that really means that our ability to sell at those higher prices early on is lost. And so we've lost some of that desired segmentation as customers will delay that purchase decision. So as more consumers are privy to that information, our ability to have that desired set of prices, and ultimately achieve that segmentation, is decreased as a result of improved information in the eyes of the consumer.

72 Strategic Consumer Behavior-Hotel Transcript: Strategic Consumer Behavior-Hotel All right, we're going to continue our discussion on strategic consumer behavior. This time we're going to focus on the acquisition of hotel rooms. So similar to air, we think about hotel search, Bing is providing lots of information to the consumer. So I've searched for a hotel room, say, in New York City. In addition to providing me with a list of prices for a set of hotels in New York City, what the search engine is doing here is providing some indicator of what they think about those prices-specifically, are those prices deals, not deals, or typical rates? So they have this sort of barometer of rates. So I can either see that in the list, or I can see that as a map, and so I get a sense of what part of the city are prices high or low. So they're not providing me any indicator of whether or not I should wait or buy, but they're at least providing me a check of whether or not these are realistic prices for that market. Bing provides me some information on how it estimates this sort of deal or not deal, and that's basically by comparing current rates to historic rates for similar travel periods. So I'm traveling on the fourth Monday in March, and so Bing might compare current prices for this fourth Monday in March to the fourth Monday in March last year, or maybe the fourth Monday in March this year to the second or third Monday in March. So I get a sense of how prices stack up to similar prices-the kind of thing that I would do as though I was a regular traveler into that market. If I'm an irregular traveler and I have no sense for those prices, this is some sort of barometer of where those prices are. Similarly, Google has a product called "Hotel Finder," which provides, again, that sort of barometer of prices. Unlike Bing, which has categorized it into three, basically what Google does is provide this continuous scale of the percent of current prices to typical to give you a sense of whether or not it's a good time to be in that market for a hotel room. More recently, online travel agents have sort of started offering new products, which are similar, or facilitating, this shopping behavior. The first of those was Orbitz, which offered a product called "Price Assurance," which basically indicated that if you booked a hotel through Orbitz, and somebody else after you booked that same hotel room-the basic same hotel, same room type-for the same check-in and check-out dates and got a better deal than you did, then Orbitz would refund you the difference between what you paid and that later-arriving customer paid. So some incentive to book with those to get access to this deal. More recently, Tingo has entered this space, and basically what Tingo is doing is taking Orbitz's model one step further, and instead of monitoring who has booked after you, they simply monitor prices. So if you've booked a hotel room and

73 prices drop, then what Tingo does is automatically cancel your reservation and rebook you into that same hotel, same room type, but at this decreased room rate. So unlike Orbitz, Tingo is shopping and automatically doing this sort of cancel-rebook, whereas Orbitz is only doing it if there's a transaction. So what are some of the implications of this strategic consumer behavior? Well, anecdotally, we observe that approximately 20 percent of hotel prices are decreasing from the time of booking to check in. And these typical price decreases are around 10 percent, so the product of the 10 and the 20 is 2 percent. So if all consumers were to cancel and rebook if prices decreased, then prices would drop by about 2 percent. So this gives the idea that we need to focus more on segmentation-perhaps create some more structured products that have cancellation fees, or are all prepaid products. So trying to make the hotel booking similar to the air booking, where it's very hard to cancel and rebook-so as to deter that strategic behavior on the act of the consumer. So if you think the consumer thinks they're going to travel, then they should buy now versus waiting. Ultimately, our goal is, consumer looks at our prices, finds them attractive, then we want them to transact now. The last thing we want to do is have a consumer who looks at our prices, sees them, and decides not to transact, but to wait in the future and potentially transact later. So in the best-case scenario, when they decide to transact later, they may still transact with us, but if they decide to postpone their purchase decision and our prices go up, and one of our competitors' prices goes down, then now we've potentially lost that consumer. So our goal is to transact when the consumer was happy with our price, and just sort of deter that strategic behavior.

74 Enabling Strategic Reservations Consumers now have access to online rate comparers, third-party companies that enable price shopping, as well as a series of new entrants that facilitate consumer transactions at the lowest possible prices through a series of cancellations and rebooks. These new entrants continue to search the Internet for lower prices even after you have made your reservation, cancelling and rebooking your reservation automatically if they find a better a price. Sometimes these online offers are predominantly for marketing purposes. For example, Orbitz's price-assurance policy states that it will issue you a refund if, after you book with them, another customer gets the same thing at a lower price. But how does this really work? After your reservation is confirmed, Orbitz tracks to see if any other Orbitz customer subsequently books the same flight or hotel on Orbitz at a lower price. If that happens, they will issue a refund to you for the difference. However, although the refund comes out of the pockets of Orbitz (not the airline or hotel), Orbitz is risking very little by making this offer. For you to receive a refund, another customer must book exactly the same room or flight with the same legs on the same date and time-a relatively unlikely event. Two newer entrants target rental cars and hotels specifically. Like Orbitz, they compare prices. But they extend the Orbitz model in that, if they find better prices for your desired service, they automatically cancel and rebook your reservation at the newly found lower price. Let's look at these services next. To initiate a request through the rental car service, the customer specifies a location, car type, dates, and brand-just like with other rental car services. He or she may then make a tentative reservation. Subsequently, the service monitors prices daily between the time of the initial reservation and the car pickup, automatically cancelling and rebooking the reservation if prices decrease. In essence, this service has automated strategic consumer behavior. This is facilitated by the fact that most rental car firms have no fees or penalties associated with cancelling a reservation or not showing up for a reservation. The other service, similar to the one for rental cars, is for hotel rooms. Through it, customers make a reservation at their hotel of choice (room type and stay dates). If a lower price becomes available, this company automatically cancels and rebooks the customer at the lower price. These last two examples are distinct from Orbitz because the supplier bears the risk of this behavior. These services physically cancel the original reservation and replace it with a new one at the lower price. The supplier (rental car or hotel) pays the "cost" of this strategic rebook behavior. Orbitz, on the other hand, rebates the original customer out of its commissions. have implications for service providers: Automated cancel-and-rebook service providers and online rate comparers Consumers quickly learn about pricing mistakes. Consumers can adapt to pricing strategies. Purchasing decisions may become more focused on price, with decreasing emphasis placed on brand loyalty. In summary, it is a great time to be a consumer. But it's not a great time to be a company with a poor pricing strategy-a strategy that misuses revenue management-related actions. Armed with a good pricing strategy and an understanding of these consumer resources, a firm can use these rate comparers for its own benefit.

75 Module Wrap-Up In this module, we investigated how prices evolve over time. We discussed this in relation to dynamic pricing, and we looked at how we can use dynamic pricing to increase profits. We also examined consumer purchasing strategies. You should now be prepared to use this information to improve your pricing strategies and maximize revenue. Having completed this module, you should be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations Predict how customers will react to dynamic pricing Discuss how best to structure prices available online

76 Course Wrap-up If you have completed all of the modules in the course-congratulations! Having completed this course, you should be able to: Make smart pricing decisions based on market segmentation Apply variable versus dynamic pricing strategies Use prospect theory to structure pricing communications Predict the diluting impact of poor segmentation Develop an upgrade strategy and evaluate its marginal value Determine how best to structure prices posted online

77 Thank You and Farewell Congratulations on completing the Segmentation and Price Optimization course. The course examined techniques available for analyzing and setting prices, given that technology has revolutionized the way we do pricing. We focused on variable and dynamic pricing strategies, and how to make smart pricing decisions based on market segmentation. I hope to see everyone in the remaining courses in the series. Thanks, this is Chris Anderson.

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79 MODULE INTRODUCTION Module 2: Dynamic Pricing and Segmentation If performed properly, dynamic pricing (adjusting prices throughout the booking window in response to demand) complements price segmentation and leads to increased overall revenues and profits. If performed poorly, dynamic pricing can erode revenues and encourage consumers to become strategic or to time their purchase in an effort to obtain goods or services as cheaply as possible. In this module, we discuss how dynamic pricing can be paired with segmentation to increase profits and avoid leakage. By the end of the module you will be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations Predict how customers will react to dynamic pricing Discuss how to best structure prices available online

80 TOPIC OVERVIEW Topic 2.1: Booking Curves Dynamic pricing requires an understanding of how prices evolve over time. It's possible to build that understanding by tracking the evolution of demand using booking curves. In this topic, find out how to use dynamic pricing to create a successful pricing strategy. By the end of this topic, you will be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations

81 Variable Pricing Versus Dynamic Pricing We've been discussing variable pricing, but let's compare that with a different way to set prices: dynamic pricing. Variable pricing for a particular product or service involves setting multiple price points for distinct market segments. The prices are preplanned, and all prices could potentially be offered simultaneously. For example, on June 3, a customer checking room prices at the Milton Hotel for a July 3 stay may find that a single costs 135, the double costs 157, and the king suite costs 200 per night. These are preplanned, variable prices for a room in that hotel. By contrast, dynamic pricing involves an expectation that prices will change over time in response to demand uncertainty. Usually you decrease price in an attempt to stimulate demand and increase price in response to strong demand. For example, on June 3 a customer calling the Milton Hotel to request a king suite for July 3 (one month from the request date) may receive a quote of 200 per night. Another customer calling on June 25 to request a king suite for July 3 (one week from the request date) may receive a quote of 250 per night. That's dynamic pricing: the same room sells for different prices depending on the date of purchase. The airline industry is often cited as a dynamic pricing success story. In fact, it employs the technique so artfully that most of the passengers on any given airplane have paid different ticket prices for the same flight. On a flight from Ontario, Canada, to Los Angeles, the traveler in seat 7A may have paid $470, whereas the traveler in 7B may have paid $640. The difference in ticket price depends on when these passengers booked their flights.

82 Introduction to Booking Curves Transcript: Introduction to Booking Curves So as we move from variable pricing to dynamic pricing, remember that dynamic pricing is the evolution of those variable prices over time. What that requires is for us to have some idea of how demand is going to materialize over time. And booking curves are our most common form of understanding how demand is evolving over time and hence what are the opportunities to capture with a dynamic pricing strategy. Booking curves are relatively straightforward to construct; they are basically the average reservations on hand, for different days before arrivals, so some sort of snapshot of how demand typically materializes over time. So typically on the right-hand side we have 90 or 120 days before arrival and then over time demand picks up as we get closer to departure for a plane or check-in for our guest. So this basically shows the evolution of reservations as we get closer to the service date. So we would typically have different booking curves for different segments, or more specifically, each segment should have a different booking curve, so we would have different booking curves for our product classes or rate classes, different booking curves for length of stay, and different booking curves for day of the week. One could argue that if the booking curves are not distinct then those are really not distinct segments because they are booking in the same fashion. And so ideally as we compare these booking curves from one product class to another, we would expect them to have different shapes and different levels of materialization and that would sort of tell us that these are potentially different segments. One extreme might be comparing your discounted booking curve versus your full-fared booking curve. And as this particular example shows, here we have our discount demand coming in relatively early, and we have our full-fare demand coming in relatively late. So what this tells us is that my discount rate can be available probably all the way up until three, four, or five days before check-in and I have very little potential for dilution. Very unlikely that a full fare customer is going to arrive and purchase a discounted product because those full-fare people are not in the market yet, their booking curve says they really don't start to pick up any traction until somewhere around four days before arrival. And so this tells that if we're going to have prices evolve over time that we could have our low price out there right up until about five days before arrival and then if we kept our low price in the market after five days, we run the risk of dilution of our high-priced demand buying down to that low-priced product.

83 How Booking Curves Are Created One of the most important sources of data we have to support dynamic pricing decisions is booking curves. When we look at them, one goal is to be able to determine how people book over time, and then compare the booking behaviors of different segments over time. We define segments by such factors as rate class, length of stay, or channel (that is, through an online travel agent site or by word of mouth). Ideally we construct booking curves for all segments i n an effort to identify possible leakage or demand losses if we change prices (that is, if we employ dynamic pricing). Booking curves provide insight into pricing opportunities and also show when dilution may be a problem. Table 1 displays the ROH for the day of arrival (0) and 7, 14, 21, and 28 DBA over the course of five stay dates (say the last five Mondays). At the bottom of Table 1 we calculate the Average ROH for each of the DBAs (0,7,... 21); we also display the average as a Percentage of Average ROH at arrival (DBA 0). Table 1 Table 2 shows the calculations used for the Average ROH and the Percent Average ROH. In this table, we calculate Average ROH by entering the formula =AVERAGE(B3:B7) in B9 and then copying that formula to cells C9 through F9 (C9:F9). To calculate the Percent Average ROH, we entered the formula =B9/$B$9 in B10 and then copied it to C10:F Table 2 To facilitate decision making, we convert this data from a matrix into a graph or booking curve. The booking curve graph makes it easier to visualize the booking pace at the firm. To create a booking curve of the Average ROH for the DBA: Use your mouse to select cells B9:F9 Locate the Insert chart option on your version of Excel Select the Line graph option

84 Right-click the line graph, click Select Data Click the x-axis labels and select cells B2:F2 and click OK Figure 1 shows this graph Figure 1 We most often use booking curves in combination, to compare one rate class to another or one length of stay to another, for example. Because one rate may have substantively more (or fewer) bookings than another, it's best to use percentages of the averages. You find this percentage by dividing all the averages by the maximum average ROH. In Table 1, we divide the averages by 163 (the maximum average on the day of arrival). Now, instead of graphing the averages, we create the booking curve by graphing the percentages. To create a booking curve of the percent average ROH for the DBA: Use your mouse to select cells B10:F10 Locate the Insert chart option on your version of Excel Select the Line graph option Right-click the line graph, click Select Data Click the x-axis labels and select cells B2:F2 and click OK Figure 2 shows this graph Figure 2 If we had data on multiple segments, we could then plot these booking curves (as percentages) on the same graph to compare when each booked. If you do this for your own hotel and you don't find any major differences among the graphs, then perhaps you need to revisit your segmentation!

85 In the following exercise, you download a spreadsheet that includes detailed instructions for creating the booking curves and you create your own booking curve.

86 Create a Booking Curve-Review If you had difficulty creating a booking curve for Hotel Ithaca, download the Hotel Ithaca spreadsheet to view a correct booking curve and to find out how the curve was created.

87 Using Booking Curves Transcript: Using Booking Curves So we're going to further continue our discussion on booking curves. Here we're going to focus on how to use these booking curves to understand segments, and at some level control inventory. So here, what I'm gonna show is a series of booking curves for demand into the Hawaiian Islands. And this is specifically demand that's generated at an online travel agent. Each of these graphs is going to show three different series: a solid line, which is a package product. A package product would be someone purchasing a hotel room and an airline seat together-as one product. We have the dotted series, where the consumer is purchasing their hotel room opaquely-so that basically means they know it's a four-star hotel, they don't know which four-star hotel. And then lastly, the dashed line is a consumer who's purchasing just the hotel room-so he's not purchasing air along with that hotel room-just the hotel room. So what we see here is the opaque product and the hotel-only product seem to exhibit the same booking characteristics-the shape of the curves is relatively the same. What the solid line shows is our package purchases are those consumers who are purchasing both air and hotel together. Its distinct shape from the hotel-only product indicates that these consumers are in the market much earlier than those looking for just hotel room only. Specifically for the package, roughly 90 percent of those purchases are made prior to 14 days before arrival. So here's a nice way to segment. You know that people who are in the market early-the price-sensitive consumers-are more likely package purchasers. So you could have a discounted hotel rate as part of a package, and have your higher-price hotel rate as part of a nonpackage product. But if we look at those same curves in a different way-so here, see we have the same three curves-package, hotel-only, and opaque-but now we look at a short length of stay. So what we see here now is that these booking curves are not all that distinctive. So this is a guest who's staying one, two, or three nights. If we compare this graph to our next graph, which shows those same three curves but for a longer length of stay, we see here that a large part of the segmentation is length of stay, and not necessarily the purchasing mechanism. If someone is purchasing a week, that they tend to purchase that further in advance than someone who's purchasing two or three nights. So one could sort of think about the segments here, the individual flying into the Hawaiian Islands for two or three nights is probably a business traveler, whereas the consumer flying into the Hawaiian Islands for seven days or longer is probably a leisure traveler, is in the market earlier for more discount prices. So in addition to segmenting by package versus hotel-only, we can augment that with short and long length of stay. If we compare and contrast this across product quality-so here we're going to go through a series of booking curves-each of these booking curves is for a quality of service. Initially here we have one- to two-and-a-half-star hotels. Our next graph

88 is three-or four-star hotels. What we see here is that the behavior is consistent across the different channels, across the stars. So stars-star quality-is not as prolific a segmenter as, say, the channel or the length of stay. So in summer here we saw that length of stay was a good segmenter, also that package versus hotel-only was a good segmenter. These are very logical, and we're just confirming that logic by looking at our booking curves. So quite often booking curves are simply testing some of these logical hypotheses that you have put forth from a marketing standpoint.

89 TOPIC OVERVIEW Topic 2.2: Strategic Consumer Behavior To create an effective dynamic pricing strategy, you must understand consumer behavior. With the availability of online tools, today's consumers are more strategic in their purchasing decisions than ever before. It is therefore critical that firms understand their customers' decision processes and the tools they are using to make those decisions. This information can be used to strengthen the firm's dynamic pricing strategy. By the end of this topic, you will be able to: Predict how customers will react to dynamic pricing Discuss how best to structure prices available online

90 Consumers and Dynamic Pricing Dynamic pricing by definition indicates that prices, in response to demand, evolve over the booking window. As dynamic pricing becomes more commonplace, consumers may learn to anticipate price changes and attempt to time their purchases to get better prices. They may see that, in general, prices do not change monotonically (that is, prices do not either consistently increase and never decrease or consistently decrease and never increase) as the service date approaches. The accompanying figure shows a typical price curve for many service firms deploying a dynamic pricing strategy. As the curve shows, prices often are higher early in the booking cycle, decrease in reaction to demand uncertainty, and then increase in the final few days or weeks prior to service, in response to later-arriving business travelers with greater willingness to pay. Such a price curve works well when Risk-averse consumers willing to pay a higher rate book early to ensure they get access to service (perhaps for an annual vacation) Consumers looking for a discount book in the midrange time frame-for an airline typically two to six weeks prior to departure Late-arriving consumers exhibit greater willingness to pay owing to their need to travel and their inability to have flexible plans or plan in advance When customers follow this pattern, firms can close discount fares or rates after a certain time period and increase rates as the service date approaches. But the use of dynamic pricing may change consumer behavior. If consumers anticipate price changes, they may postpone purchase decisions even though they may be happy with current prices. Before price-shopping moved online, it was difficult for consumers to compare prices across firms (to compare airline A to airline B, for example) and over time (comparing today to next week, for instance). Now it is becoming increasingly easy for consumers to see how prices evolve over time. The Internet makes it easy for buyers to look at the pattern of pricing and demand and to evaluate where pricing currently is in the U-shaped curve. As a result of these nonmonotonic prices, consumers are perpetually checking prices to try to get the best deal. As a service provider, you want to encourage customers who are willing to purchase from you to decide right away, not to wait for a better price. If the customer does not decide right away, he or she may get access to lower prices later. If your prices don't decrease and your competitor's prices do, you run the risk of losing the customer.

91 Strategic Consumer Behavior-Airlines Transcript: Strategic Consumer Behavior-Airlines All right, our focus today is going to be on strategic consumers, and ultimately their impact upon segmentation, and then how that leads to pricing. So historically, if we think about how prices evolve for a particular airline flight-so that flight might start going on sale six months prior to departure. Then if we look at how those prices evolve as we get closer to the plane actually departing, those prices have historically looked like a very squished "U." Where early on, prices are relatively high, as we get closer to departure they decrease, and then ultimately they increase as we get to the last two or three weeks prior to departure. But more recently what's happened is a series of information providers which potentially has some implications upon that price curve. The first we'll focus on is Bing-so, Microsoft's search engine. If I was to perform a search on Bing for a flight-so here's a flight from Newark to San Francisco-so not only do they provide me with information on that flight, they also potentially suggest some alternative routes. So instead of flying to San Francisco, maybe I want to fly into San Diego or Sacramento. Instead of flying from Newark, maybe I want to fly from LaGuardia. So they're already leading me to other routes that may be more price-competitive. In addition to that, when I actually focus on my route, they show a set of prices, but then they also provide to me a barometer of where they think prices are going to go-"should I wait, or should I buy now?" Basically, they come up with a probabilistic estimate of whether or not they think prices are decreasing. If they think prices are decreasing, then we should wait; if prices are increasing, then you should buy. So really sort of providing some insight into that movement of prices, i.e., where are you in that sort of flattened out U shape. If we think of the other big search engine-in this case Google-Google has a similar product called "Flights." Little bit different than Microsoft, but they basically provide an array of flights for different origins and destinations. But they also provide some metrics on if your travel is flexible, if you can adjust your departure dates, they'll provide this sort of graph of how those prices are evolving at these different departure dates. So if you're flexible in your travel plans, then maybe you should choose an alternative time to fly, basically trying to pick a spot in that U for different departure dates. They also allow to sort of simplify that set of flights that you look at into what we refer to as an "efficient set"-so basically flights that are short and cheap. So we can sort of look at a two-dimensional view of prices. So I only want flights that are less than ten hours and that are less than $ So I don't consider flights outside of that set. So what's the implications of this? Well, if we think of the information provided by these two search engines, and then if we think about that U-shaped set of historic prices, well really, we're not going to achieve some of that desired segmentation. If we were pricing relatively higher early on in the sort of selling window, so back at six months maybe to three months before departure, and the consumer is now privy to this information from these information providers-that prices are

92 decreasing and that they should wait-then that really means that our ability to sell at those higher prices early on is lost. And so we've lost some of that desired segmentation as customers will delay that purchase decision. So as more consumers are privy to that information, our ability to have that desired set of prices, and ultimately achieve that segmentation, is decreased as a result of improved information in the eyes of the consumer.

93 Strategic Consumer Behavior-Hotel Transcript: Strategic Consumer Behavior-Hotel All right, we're going to continue our discussion on strategic consumer behavior. This time we're going to focus on the acquisition of hotel rooms. So similar to air, we think about hotel search, Bing is providing lots of information to the consumer. So I've searched for a hotel room, say, in New York City. In addition to providing me with a list of prices for a set of hotels in New York City, what the search engine is doing here is providing some indicator of what they think about those prices-specifically, are those prices deals, not deals, or typical rates? So they have this sort of barometer of rates. So I can either see that in the list, or I can see that as a map, and so I get a sense of what part of the city are prices high or low. So they're not providing me any indicator of whether or not I should wait or buy, but they're at least providing me a check of whether or not these are realistic prices for that market. Bing provides me some information on how it estimates this sort of deal or not deal, and that's basically by comparing current rates to historic rates for similar travel periods. So I'm traveling on the fourth Monday in March, and so Bing might compare current prices for this fourth Monday in March to the fourth Monday in March last year, or maybe the fourth Monday in March this year to the second or third Monday in March. So I get a sense of how prices stack up to similar prices-the kind of thing that I would do as though I was a regular traveler into that market. If I'm an irregular traveler and I have no sense for those prices, this is some sort of barometer of where those prices are. Similarly, Google has a product called "Hotel Finder," which provides, again, that sort of barometer of prices. Unlike Bing, which has categorized it into three, basically what Google does is provide this continuous scale of the percent of current prices to typical to give you a sense of whether or not it's a good time to be in that market for a hotel room. More recently, online travel agents have sort of started offering new products, which are similar, or facilitating, this shopping behavior. The first of those was Orbitz, which offered a product called "Price Assurance," which basically indicated that if you booked a hotel through Orbitz, and somebody else after you booked that same hotel room-the basic same hotel, same room type-for the same check-in and check-out dates and got a better deal than you did, then Orbitz would refund you the difference between what you paid and that later-arriving customer paid. So some incentive to book with those to get access to this deal. More recently, Tingo has entered this space, and basically what Tingo is doing is taking Orbitz's model one step further, and instead of monitoring who has booked after you, they simply monitor prices. So if you've booked a hotel room and

94 prices drop, then what Tingo does is automatically cancel your reservation and rebook you into that same hotel, same room type, but at this decreased room rate. So unlike Orbitz, Tingo is shopping and automatically doing this sort of cancel-rebook, whereas Orbitz is only doing it if there's a transaction. So what are some of the implications of this strategic consumer behavior? Well, anecdotally, we observe that approximately 20 percent of hotel prices are decreasing from the time of booking to check in. And these typical price decreases are around 10 percent, so the product of the 10 and the 20 is 2 percent. So if all consumers were to cancel and rebook if prices decreased, then prices would drop by about 2 percent. So this gives the idea that we need to focus more on segmentation-perhaps create some more structured products that have cancellation fees, or are all prepaid products. So trying to make the hotel booking similar to the air booking, where it's very hard to cancel and rebook-so as to deter that strategic behavior on the act of the consumer. So if you think the consumer thinks they're going to travel, then they should buy now versus waiting. Ultimately, our goal is, consumer looks at our prices, finds them attractive, then we want them to transact now. The last thing we want to do is have a consumer who looks at our prices, sees them, and decides not to transact, but to wait in the future and potentially transact later. So in the best-case scenario, when they decide to transact later, they may still transact with us, but if they decide to postpone their purchase decision and our prices go up, and one of our competitors' prices goes down, then now we've potentially lost that consumer. So our goal is to transact when the consumer was happy with our price, and just sort of deter that strategic behavior.

95 Enabling Strategic Reservations Consumers now have access to online rate comparers, third-party companies that enable price shopping, as well as a series of new entrants that facilitate consumer transactions at the lowest possible prices through a series of cancellations and rebooks. These new entrants continue to search the Internet for lower prices even after you have made your reservation, cancelling and rebooking your reservation automatically if they find a better a price. Sometimes these online offers are predominantly for marketing purposes. For example, Orbitz's price-assurance policy states that it will issue you a refund if, after you book with them, another customer gets the same thing at a lower price. But how does this really work? After your reservation is confirmed, Orbitz tracks to see if any other Orbitz customer subsequently books the same flight or hotel on Orbitz at a lower price. If that happens, they will issue a refund to you for the difference. However, although the refund comes out of the pockets of Orbitz (not the airline or hotel), Orbitz is risking very little by making this offer. For you to receive a refund, another customer must book exactly the same room or flight with the same legs on the same date and time-a relatively unlikely event. Two newer entrants target rental cars and hotels specifically. Like Orbitz, they compare prices. But they extend the Orbitz model in that, if they find better prices for your desired service, they automatically cancel and rebook your reservation at the newly found lower price. Let's look at these services next. To initiate a request through the rental car service, the customer specifies a location, car type, dates, and brand-just like with other rental car services. He or she may then make a tentative reservation. Subsequently, the service monitors prices daily between the time of the initial reservation and the car pickup, automatically cancelling and rebooking the reservation if prices decrease. In essence, this service has automated strategic consumer behavior. This is facilitated by the fact that most rental car firms have no fees or penalties associated with cancelling a reservation or not showing up for a reservation. The other service, similar to the one for rental cars, is for hotel rooms. Through it, customers make a reservation at their hotel of choice (room type and stay dates). If a lower price becomes available, this company automatically cancels and rebooks the customer at the lower price. These last two examples are distinct from Orbitz because the supplier bears the risk of this behavior. These services physically cancel the original reservation and replace it with a new one at the lower price. The supplier (rental car or hotel) pays the "cost" of this strategic rebook behavior. Orbitz, on the other hand, rebates the original customer out of its commissions. have implications for service providers: Automated cancel-and-rebook service providers and online rate comparers Consumers quickly learn about pricing mistakes. Consumers can adapt to pricing strategies. Purchasing decisions may become more focused on price, with decreasing emphasis placed on brand loyalty. In summary, it is a great time to be a consumer. But it's not a great time to be a company with a poor pricing strategy-a strategy that misuses revenue management-related actions. Armed with a good pricing strategy and an understanding of these consumer resources, a firm can use these rate comparers for its own benefit.

96 Module Wrap-Up In this module, we investigated how prices evolve over time. We discussed this in relation to dynamic pricing, and we looked at how we can use dynamic pricing to increase profits. We also examined consumer purchasing strategies. You should now be prepared to use this information to improve your pricing strategies and maximize revenue. Having completed this module, you should be able to: Use booking curves to assess how different segments reserve inventory over the booking window Compare booking curves across segments to determine when each segment tends to make reservations Predict how customers will react to dynamic pricing Discuss how best to structure prices available online

97 Course Wrap-up If you have completed all of the modules in the course-congratulations! Having completed this course, you should be able to: Make smart pricing decisions based on market segmentation Apply variable versus dynamic pricing strategies Use prospect theory to structure pricing communications Predict the diluting impact of poor segmentation Develop an upgrade strategy and evaluate its marginal value Determine how best to structure prices posted online

98 Thank You and Farewell Congratulations on completing the Segmentation and Price Optimization course. The course examined techniques available for analyzing and setting prices, given that technology has revolutionized the way we do pricing. We focused on variable and dynamic pricing strategies, and how to make smart pricing decisions based on market segmentation. I hope to see everyone in the remaining courses in the series. Thanks, this is Chris Anderson.