[MUSIC] Hotels benchmark their rates using a metric called ADR, or average daily rate. This means that the hotel takes the average of all the room rates paid by the customers. As mentioned previously in module two, introduction to segmentation, understanding segmentation is important for forecasting, which then impacts pricing and other decisions. Your segmentation is the cornerstone of forecasting discussed in module three, which results in being the cornerstone for effective pricing. If you have high compression, meaning unconstrained demand over the property's capacity, with appropriate pricing, you should be able to hit 100% constrained and unconstrained demand by the actual stay date. If you're pricing appropriately, that unconstrained forecast should smooth to 100% by the stay date, which means that you've effectively yield appropriately to drive down that overall demand to a sellout. Pricing, especially per channel, can have long-term effects on your consumer buying behavior. As mentioned with that New York City example, a hotel should be thinking about it's repeat customers first. It is really imperative to be thinking about your pricing holistically and how it might impact the consumer that might just be searching another channel. If you're quoting a group a significantly higher rate than they might find on Expedia, that could have long-term residual effects, for not only that consumer and their group, but they could tell their friends. Say, something on social media and thus causing ripple effects, which could be disastrous for the property due to that one pricing decision. Improved technology has lead to an easier means of developing organized pricing decisions using multiple data sources, which helps the hotel set prices per segment, per room type. These new technologies give users more power to control demand through price than ever before. Legacy systems made it easy to restrict but not easy to change the price differentials. Whereas new integration's between PMS's, CRS's, revenue systems and channel managers, enable hotels to have more flexible pricing. Data helps you evaluate trends and determine what prices you should be set at. There are two main types of data hotels deal with. As we discussed in module three, introduction to forecasting. One, internal property performance data. And two, external data sources. There are a few basic things to consider on a per segment basis when you're dynamically pricing each of your different segments. If you're manually forecasting and determining a price, these are the three basic things to be considering to give guidelines to pricing decisions. First, you have your booking curve management, pace and pickup. As mentioned in module one, booking curve management is really about understanding your demand trends. Traditional ways of looking at a demand were more report based, but the visual aspects of a booking curve, allowed a user to see trends more clearly and make adjustments as needed. To monitor a hotel's booking trends, there are really two key terminologies to understand. Pace and pick-up. A hotel's pace is at the rate at which they're getting bookings. And then the hotel's pick-up, is the amount of bookings over a certain time interval. So often times in the industry you'll hear, what's my three day pick-up? This is the amount of customers that the hotel got over the last three day interval. So really, this ties into your booking curve that you can see here down at the bottom of the screen. This booking curve is broken apart by different segments. And you can see it goes from right to left, from 200 days before arrival to the actual stay date. Some booking curves will have the far left side day be minus one. Since hotel run night audits at one or two in the morning, the minus one room count is the final count after the stay date, whereas day zero is the stay date. Understanding your pace and pickup over certain time intervals, through a booking curve, really enables you to make appropriate pricing changes for a hotel. So if you start to notice a specific customer segment, whether it's discount, retail or OTA, start to have larger volumes of pick-up over a certain time period than you were expecting, you should raise rates for that segment. And with effective yielding through open pricing, you can then optimize rates for all room types and discounts within that segment. Something we'll get into later in this module. Looking at changes and booking curves will also help you with forecasting. How are your days trending? Are they all the same booking shape? Seeing patterns in your booking curve will improve your overall forecast. Next, we have market volatility and demand reports. As discussed in module three, there are tools in the hotel industry that are meant for benchmarking and also meant for forecasting. These tools help hotels understand market volatility, general market performance, and where a hotel should be priced. If it's a high demand period or high season, your customers will be anticipating to pay higher prices than during a low season. Additionally, if there are huge market wide offense, or opportunities to anticipate constraint, it gives you the ability to yield prices appropriately. Lastly, we have competitive set pricing, which relates the tracking what a hotel's competitive set its pricing, relative to where that hotel stands pricing wise. How are those competitors pricing different customer segments? Can pricing impact a hotel's demand, thus impacting the hotel's ability to price? Is the hotel priced appropriately relative to market perceptions and market placement? The most effective strategies weigh all three of these things together. If a hotel puts too much emphasis on its comp set, or pick-up, or comparison to last year, it can leave you blindsided because all of these are a factor constantly changing. And if you're not looking at the big picture and how they all play together, you won't be setting an appropriate price. Many hotels do not have the most effective pricing strategies. In the next video we will discuss some of the most common mistakes hotels make when setting prices.