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How to Optimize Your Hotel’s Pricing Using Analytics

12/17/2013| 10:05:05 AM| 中文

By using analytics to zoom in on the three “pillars of pricing”—demand, capacity and price sensitivity—hoteliers can more easily determine pricing strategies that maximize demand and optimize revenue.

Are Your Hotels Pricing Right? Your hotels have a dynamic pricing strategy in place - rates are increased or decreased according to demand. But how do you know these are the right rates and spectrum of rates, or if you are inadvertently turning away demand?

According to a study by Mckinsey & Company, Inc., “the fastest and most effective way for a company to realize its maximum profit is to get its pricing right.” 1 As it demonstrates that getting the price right is one of the most fundamental and important management functions, one of the hotel industry’s greatest challenges is how to create the right prices for the right customers at the right time. Particularly in the age of dynamic pricing, finding effective pricing strategies for maximizing revenue can seem like a complex, time-consuming and elusive process.

Fortunately for hotels, this is where analytics can make a tremendous difference. By using analytics to zoom in on the three “pillars of pricing”—demand, capacity and price sensitivity—hoteliers can more easily determine pricing strategies that maximize demand and optimize revenue.

In fact, with the right pricing models in place, hoteliers can achieve valuable returns to the bottom line. By giving hoteliers a much clearer vision of their data, analytics bring more accuracy and consistency—versus gut instinct—to the forecasting process and Best Available Rate (BAR) strategies.

The Three Pillars of Pricing

Keeping in mind that price is the key lever in driving profitability in a hotel, it’s time to explore how science, in the form of analytics, can help hoteliers stay competitive and achieve optimal pricing. When applying science to pricing, there are three pillars to consider: demand, capacity and price sensitivity.

1. Demand: Dynamic pricing approaches demand as a function of price. Put in simple terms, increase the price, and demand will drop. Decrease the price, and demand will be higher. This is, of course, nothing new to most revenue managers. However, this concept is an important element that helps us determine the right price to sell, the demand to be achieved at that price-point, and the corresponding revenues that can be attained.

2. Capacity: Revenue management works well in environments where products are “perishable”. This means that we must at all times try and optimize our inventory to take maximum advantage of the capacity that we have available.

3. Price Sensitivity: Where analytics really start to come into play. Defined as the degree to which a product or service’s price affects consumer purchasing behavior, price sensitivity can help hoteliers determine when to offer specific pricing into the marketplace to optimize revenue. Price sensitivity is measured by calculating the change in demand as a result of the change in price. Low sensitivity means that changes in price have a relatively small effect on the quantity of the rooms demanded, while high sensitivity means that changes in price have a relatively large effect on the quantity of rooms demanded. In order to maximize overall revenue, hoteliers want to know low sensitivity versus high sensitivity by market segment, and they want to know the quantity of rooms those market segments are purchasing.

Preparing for Analysis

During analysis, the end-goal is to determine the optimal rate spectrum based upon the price sensitivity of demand and the capacity of distribution. In order to do this efficiently, it’s critical to have access to the right data points or variables. These include room type, length of stay and day of week (weekday versus weekend). 

In addition, hoteliers need to have access to at least 15 months of historical, transaction-level data in order to more easily compare current and predicted activity levels. This should include the transaction’s original booking date, the arrival date and the departure date, as well as the number of rooms associated with the transaction, the rates and the room type, such as deluxe or standard. In some cases, the hotel also has to take a refurbishment or special event into consideration. 

An Example of Optimizing Revenue Using Analytics

For the sake of space and simplicity, this example will only delve into pricing analytics for the standard hotel room.

Assumptions: 

1. A limited-service, 225-room hotel

2. Experiencing peak season with high demand

3. Assume same demand
 
The figure above only explored optimization strategies for one day and one room type. As you can image, the impact of doing this one pricing exercise for the hotel is tremendous. (You can find more information on this example from the IDeaS white paper: How to Optimize Your Hotel's Pricing Using Analytics 2)

Key Takeaways and Best Practices

Below are seven key takeaways hoteliers can use for maximizing revenue across their hotel or portfolio of hotels.

1. Start with the BAR pricing: These prices are the most important for hoteliers to focus on, as they affect more prices than hoteliers may think, such as all the BAR-anchored prices.

2. Fencing and discount strategies are important: Demand should determine when to open and close fences, and hoteliers should use fencing strategies to ensure productivity of pricing and avoid cannibalization.

3. Build a repeatable process: About every 12 to 14 months, preferably around planning season, it’s important for hoteliers to revisit their price points.

4. Focus on the most price sensitive market segments: Price points with the most price sensitivity will likely be the most productive, or booked.

5. Look for large ranges between the BAR minimum and BAR maximum: If a hotelier notices a large discrepancy between these two price points, it’s a sign that these BARs aren’t very productive and presents the opportunity to re-do the rates. However, it’s important not to confuse special event pricing with BAR pricing.

6. Make sure the reservation systems can accept new BAR levels: Some reservations systems and on-line channels have a limitation on the number of BARs hoteliers can set. If this is the case, check to see if your channels need to be configured to accept new BARs, or if the optimization should stay within its current levels.

7. Prices don’t always go up: Sometimes a price point goes down and below the current BAR rate to capture demand and ensure the hotel’s competitiveness. This is a perfectly good strategy depending on the price sensitivity of customers and whether increased rate or increased volume will drive results for the hotel.

Price with Confidence and Precision

Given that a number of factors and variables play into the process, it’s nearly impossible for hoteliers to manually process the amount of data needed in time to capitalize on consumer behavior. However, the emergence of more sophisticated rate optimization software and analytics in the hotel industry has made it infinitely simpler to create pricing strategies.

IDeaS Price Optimization Service (POS) 3combines extensive industry experience and proprietary pricing models with the world-class power of SAS® Analytics to deliver unmatched precision in determining optimal demand-based pricing strategies that maximize revenue potential across the entire estate. IDeaS POS eliminates the sometimes manual, subjective and incomplete nature of current pricing methods and delivers powerful insights from your unique data set – insights that find the best opportunities to greatly enhance your pricing strategy.

TAGS: hotel | IDeaS
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