Machine learning is one of the hottest buzzwords in hospitality today. Property owners and revenue managers are eagerly anticipating how machine learning will help them gain valuable insights and predictions about their customers, instead of just collecting and reporting data. However, it’s not fully understood exactly how machine learning will impact and improve specific processes of hotel revenue management. Developing a pricing strategy is a challenging endeavor that machine learning is well-equipped to support. Here are a few of the ways that industry experts believe machine learning will optimize your pricing strategy.
1. It Will Help You Understand Your Guests
Machine learning is already being used to better understand the consumer’s buying preferences and behaviors. An innumerable amount of data points are being created by consumers and collected from internet sources and used to create predictive algorithms. For example, Netflix and Amazon have been collecting their customer data and using it to make suggestions for future purchases or content recommendations.
The hospitality industry can use machine learning to gather and parse out guest data for more targeted pricing and revenue generating opportunities. You’ll be able to gather and interpret the enormous amount of data that guests create and determine patterns and predictions, plus assign a level of importance to each category of data that you receive. It will even collect social media and hotel review site data and analyze it on sentiment to make suggestions for improvements based on those patterns.
2. It Will Improve Forecasting
Analytics-based forecasting tools are already in existence. Once machine learning is fully implemented within those technologies, forecasting will be more precise than ever before. Dan Skodol, Vice President of Revenue Analytics at Rainmaker, says that “Machine learning will play a huge role in forecasting and forecasting accuracy. You’ll be able to constantly fine-tune your forecast, plus use it to refine your strategy and automate most processes.” Machine learning will enable current predictive analytic systems to include hundreds of more factors from a much wider variety of sources than what’s currently available at a faster rate.
You’ll also have more insights into demand with machine learning. Early revenue management solutions had a limited view of demand based mostly on historical data. Machine learning will analyze historical data, plus real-time demand statistics and other market demand signals so that revenue generating opportunities aren’t missed.
3. It Will Pinpoint Price Elasticity
Machine learning will dramatically change the way we monitor demand and price elasticity. Machine learning will be able to monitor your historical demand plus the occupancy of your comp set and automatically raise or lower rates so that each guest receives the optimal price, all without any intervening by you or your revenue management team. Having a more comprehensive picture of market demand and your comp set will allow you to dynamically price with greater accuracy and less effort.
True optimization isn’t just about making faster decisions. It’s making the right ones. Machine learning is destined to improve pricing strategy development by helping hoteliers determine which specific factors generate the maximum output. We’re already seen massive technological advances in revenue management, not to mention how it’s transformed how we travel in general. As technology continues to improve, it’s important that your property has an RMS that can keep up with future developments.
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