Revenue managers may be excited about the ever-growing number of data sources available to them. But they should exercise caution in incorporating every last bit of data into their models. More data can simply mean more noise. At a certain point, there are bound to be diminishing returns.
In fact, new data that may seem highly relevant at first glance may, in fact, create integration headaches while failing to move the needle on forecasting accuracy. The volume and depth of clean historical data related to occupancy, rate and revenue figures (including bookings dates, rate codes, arrival dates, departure dates and revenue by day) provide the strongest basis for forecasting accuracy. All this data should reside in the Property Management System (PMS).
The greater the number of years for which a hotel has data, the more accurate the forecast is likely to be. Market-level data, including competitive pricing, future flight demand, weather reports and geographical information (where guests are arriving from), may also be used for forecasting purposes. Web shopping data (the number of consumers booking rooms and at what price, as well as the percentage of visitors abandoning the hotel website) may also provide some insights into current and future room demand as well as price sensitivity. The number of website visitors tends to correlate to the frequency of last-minute arrivals.
Forecasting demand for available rooms — and dynamically pricing room rates based on demand and capacity as well as competitor activity — needs to happen in a near-real-time manner.
According to The 2016 Smart Decision Guide to Hospitality Revenue Management (now available for complimentary access), intelligent pricing means making decisions for how to maximize room occupancy at the best possible price while factoring in all the related revenue questions in a real-time or near real-time manner.
These questions include: What is the optimal price to charge in order to maximize revenue, accounting for the fact that demand will change as the price changes? What is the best possible rate the hotel can hope to get for a guest room, taking into account the type of room as well as the length of stay? How can a hotel ensure that discounted price promotions won't dilute revenue and profits in the long run? Intelligent pricing addresses these questions by analyzing demand forecasts, competitor rates, price sensitivities and various other inputs and factors, including demand drivers like seasonality, day-of-week differences and market dynamics.
Here it's worth noting that, until recently, the standard approach to pricing strategy has been a fixed-tier approach based on one overall best available rate (BAR) for each room and also on the expected supply and demand of rooms for a particular date. Ideally, when pricing multiple products, solutions should account for different room types and also for the impact of multiple public products on one another –e.g. advanced purchase versus BAR.
Some hotels and resorts are now adopting a pricing strategy based on the idea is that different prospective guests should be offered different rates depending on which guest segment they fall into as well as which channel they're using for booking their reservation. As technology innovation makes it possible for hotels to price their room types, channels and dates independently of each other, the approach would seem to hold promise.
To read The 2016 Smart Decison Guide to Hospitality Revenue Management, please click here.
To read The 2015 Smart Decison Guide to Hotel Property Management Systems, please click here.
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Jeff Zabin is Research Director at Starfleet Research, the IT market research arm of Starfleet Media, which benchmarks best practices in hospitality technology and publishes the popular Smart Decision Guides on hotel-related topic areas. He also serves as managing editor of Hotel Technology News (hoteltechnologynews.com) and as Uhrverkäufer at HotelClocks.com, authorized distributor of the world's most exquisit timepieces to luxury hotels and resorts.