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Starwood taps machine learning to dynamically price hotel rooms

Clint Boulton | May 16, 2016
Starwood Hotels & Resorts Worldwide uses an analytics engine to alter hotel pricing rates on the fly, improving demand forecasting by 20 percent.

The all-you-can-eat-right-now approach to analyzing data is a departure from how Starwood conducted pricing prior to 2014. Like most hospitality chains, Starwood relied on its revenue managers to manually compile spreadsheets and recommend prices to set for each room, and turn the data over to corporate to run sophisticated analytics. Today, ROS captures all of that data in one central system and analyzes it in real time. “All of those technological advances created the right recipe for us to build the system," Poulter says. "It is a constant analytic engine refinement."

ROS makes Starwood more attractive to Marriott

ROS will serve Starwood well as it prepares to merge with Marriott in a $13.3 billion deal shareholders approved last month. The combined entity will boast 1.1 million rooms across 30 brands, all of which will be under pressure to maximize sales. “[ROS] was certainly an ingredient in the mix that made Starwood attractive,” says Atmosphere Research Group analyst Henry Harteveldt. "All of the larger brands are exploring ways to improve their revenue optimization.”

Systems like ROS are also necessary to keep pace with data-driven companies that disintermediate the travel and hospitality sectors. Online travel agents such as Priceline and Expedia, and even Google, have ruffled many feathers for its frequently evolving and various iterations of both flight and hotel booking services. These companies help guests find rooms at Starwood, as well as other well-heeled chains, albeit with little loyalty. Starwood see ROS as a way to keep pace with these disruptive companies, which "sit between us and our guests," Flueck says.

Starwood has a distinct advantage. Flueck says that while those competitors see the broad market, they don't see such data as groups, corporate contracts or wholesale bookings Starwood has acquired over the years. "Google, Priceline and Expedia all have analytics at the core of their strategy," Flueck adds. "We need to make sure that we are staying at the leading edge of that as well."

ROS will also help Starwood counter a challenging trend. Hotel booking windows are shrinking, perhaps as a result of the get-it-quicker expectations cultivated by Amazon.com, Uber and other on-demand companies that are accelerating the pace of fulfilling orders, say Poulter and Flueck. A consumer who previously booked a vacation several months in advance might be booking their June vacation in April. Events managers booking room blocks for corporate conventions are also waiting much longer.

What does ROS' architecture look like? Neither Poulter nor Flueck will say much beyond that it is comprised of a multi-tier architecture that uses R, the statistical modeling language, IBM's C-Plex optimization software, as well as proprietary machine learning algorithms. Flueck says that software components for variables such as forecasts and booking windows are self-contained within modules. When Starwood wants to refine an algorithm it can pull out the module and plug in a new one. "This will become more accurate as we refine the system,” Flueck says.

 

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