Machine Learning: Buzz Phrase or the Real Deal?
Written by: IDeaS Revenue Solutions
Industry conversations are taking place around the role machine learning plays in revenue management solutions for hotels. The tools in the market that help hotels ensure their product is available on any number of distribution channels are growing as fast as the distribution channels themselves.
Hotels have central reservation systems, channel managers, revenue management systems and OTAs all competing to distribute a price and, in many cases, also determine what that price should be. While options and diversity will keep solutions competitive and innovative,there is clear differentiation in the market when it comes to machine learning.
In order to optimize business to its fullest extent—and maximize not just revenue but also profit—hotels must be able to delineate between the tools that merely hook their wagon to the buzz phrase, and those truly leveraging the efficiency and insights of machine learning.
Thanks to big data, machines now have a lot more to learn from. The question is: Are they learning or are they causing hotels to work harder to decipher all that added data?
Let’s think about a well-established data source that can inform a revenue strategy, such as TravelClick’s Demand360 reporting. Sliced and diced in so many ways, you can look at data by arrival date, channel, source, segment and more.
Several revenue strategy tools bring Demand360 into their system, but few actually leverage the data as part of their optimization process to ensure strategy is also optimized against price and inventory in the market.
Looking beyond that, what do we want a machine to learn from this data?
A high-performance revenue management solution that analytically determines decisions, like pricing and inventory controls, should be able to generate a price that adapts to fluctuations in the market and anticipates them in advance. It should understand the impacts of a particular price in the market and if you raise or lower that price by $10, what the change in actualized revenue will be as a result.
If demand can influence price, and price can influence demand, it should stand to reason a machine-learning tool will also understand that relationship and better optimize pricing to secure the optimal mix of business from the demand.
When demand is only forecasted based on the price you set, you never truly understand what the optimal outcome is or what impact that may have on another rate derived from the price you set (e.g. an advance purchase rate). In this case, your machine is not learning, it’s just a more expensive rate distribution tool.
As hotels consider a solution to help price and optimize business, they must decide if they want a sophisticated machine-learning tool that analytically determines decisions, or a tool that requires manual rules be set to govern the tool.
Revenue managers work hard, and they have enough reports to review and strategies to validate. Is your revenue strategy tool working as hard as you are or are you having to work for it?
Machine learning is not going anywhere and systems will only continue to become more refined with more powerful data. Don’t let your strategy be defined by rules you have to continually set.
With more than 1.5 million rooms priced daily on its advanced systems, IDeaS Revenue Solutions leads the industry with the latest revenue management software solutions and advisory services. Powered by SAS® and with nearly three decades of experience, IDeaS proudly supports more than 9,500 clients in 111 countries and is relentless about providing hoteliers with insightful ways to manage the data behind hotel pricing.
IDeaS empowers clients to build and maintain revenue management cultures – from single entities to world-renowned estates – by focusing on a simple promise: Driving Better Revenue.
IDeaS has the knowledge, expertise and maturity to build upon proven revenue management principles with next-generation analytics for more user-friendly, insightful and profitable revenue opportunities – not just for rooms, but across the entire hotel enterprise. For more information, visit www.ideas.com.