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Revenue management: The science of selling

11 April 2007
Revenue management: The science of selling

By analysing historical computer data about yourcustomers it is possible to predict booking patternsand use them to dictate room rates and maximise revenue. Ross Bentley explains

Somewhat of a dark art, yield management, or revenue management (RM) as it is now being termed, is reaching new levels of sophistication thanks to improvements in the technology and a greater understanding of how to get the best from it.

RM technology was pioneered by the airlines in the 1970s when they found themselves in a situation that will be familiar to hoteliers.

They had a number of seats to sell for each flight. Like hotel rooms, these seats were "perishable", and they needed to be resold after each flight. Supply was fixed but demand would fluctuate depending on the time of the flight, the destination and how close to take-off the customer chose to purchase.

Think of a standard booking on the EasyJet website: the earlier you book the flight the cheaper the seat will be, as there are more available. Wait a week before making your purchase and there will be fewer seats, thus more demand, and the cost will have increased. This is RM in action.

According to Delfo Melli, European director of business development at Amadeus's revenue management division, the hotel sector started to exploit this technology fully during the mid-1990s.

Using RM systems such as that supplied by Amadeus they were able to divide their customers into separate buying groups, or micromarkets, such as business travellers, frequent guests and group bookings, and start building a picture of how and when they would make reservations and what kinds of reservations they would typically make.

Likewise, as hotels started selling through different channels, be it internet or phone, they could start to predict the standard lead times coming from each channel.

At the heart of RM systems is sophisticated modelling software, which, over time, allows hotels to start making predictions about what type of bookings they can expect on any given day. Other crucial information on cancellations, no-shows and length of stay is also available.

"From this data hotels can start forecasting what prices they are going to charge certain customers at what time," says Melli.

RM systems also allow hotels to decide whether to take a booking or to hold out for a more profitable booking in the future. For example, a customer might call to book a room for a single night on a Wednesday three weeks ahead. Using historical data - for example, from the past six Wednesdays and from the same date last year and the year before - the system will know that there is likely to be a number of bookings for two and three nights that are more profitable and will tell the assistant there is no availability

At Micros, sales director for hotels Paul Finch says its RM system, part of the Opera suite of products, recalculates information on an hourly basis to enable hotels to react to last-minute peaks or troughs in reservations.

With this level of detail, hotels can combine data on occupancy and room rates to easily calculate their revenue per available room (revpar). Melli says an increasing number of hotels are now starting to factor in costs as well to discover their gross operating profit per available room (goppar).

An RM system's ability to integrate with other IT systems is vital to its success, as it is using data from property management and central reservations systems to make its decisions.

According to Linda Hatfield, vice-president of product management at Ideas, an RM system provider, its system not only has built-in integration with all the major hotel systems, it can also take feeds from five of the leading web rate-shopper systems to incorporate rates from competing hotels in the locality.

Competitors

"But hotels shouldn't base their rates on what their competitors are doing," she warns.

"They should use RM to set the rate that is right for them and then use the system to look at what the competition is doing."

But are RM systems accurate? Are guests so predictable that their buying patterns can be pinpointed and predictions made about what they will do? After all, they are human, not machines.

At the Texas-based Omni hotel chain, corporate director of revenue management Brad Anderson is in no doubt. He has been collecting data on his guests across 40 hotels since 2001 using an RM system from JDA Software.

"Whether it's 30, 14 or seven days out, our system will predict the best combinations of length of stay to book and get it right. You can set your clock by the bookings patterns of our guests," he says.

But where human foibles are an issue is behind the scenes, according to JDA consultant Dominic Beveridge. He says that the people who hotels employ to use RM systems are often not qualified to exploit the technology to the full.

In a lot of cases hotels will promote a front-office person into an RM role, but they might not understand the mathematics behind the technology, he says.

"A combination of skills in IT, accounting and business analysis is the best mix for an RM role. These are the guys who understand how to make money out of RM, and there is no point doing RM unless you are making money from it," says Beveridge.

Case study: Omni Hotels

As corporate director of revenue management for the Omni Hotels chain in the USA, Brad Anderson has one golden rule: it's detrimental to the business to take room bookings in the order in which they come in.

That's because a hotel's first phone call of the day is unlikely to be the property's best potential booking. But if you have already sold a room at a lower price or for a shorter length of stay, then you are not optimising the profitability of that room.

"Here we are with 40 upscale hotels and more reservation requests than we have rooms for," says Anderson, whose typical property is an upmarket hotel with 350-500 bedrooms.

"Obviously, if we have a product that can command the rates we want, we should try to maximise revenue and profitability by making the most prudent decisions in terms of our rates and lengths of stay."

According to Anderson, he and his team are much better placed to do this since they installed an automated revenue management system based on technology from JDA Software in 2001.

Omni has used the system to segment its customers into seven distinctive buying groups. These include guests who will always buy rooms at rack rate at the last minute, local customers who use the hotel all the year round, and internet bookings.

Anderson says each one of these groupings demonstrates a different booking behaviour, which, after tracking their traits for six years, the software is able to predict.

"We have started to unearth the psychology of how and when different groups buy and, from a calendar year out, the system will tell us whether we should take a booking at a certain time for a certain length of stay or hold out for a more profitable reservation, " he says.

As a result, Anderson says, the hotel chain has increased its revenue by 10% over the past year.

"The team are making smarter decisions and looking further out from the reservation date," he says.

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