In our blog on big data, we learned what it is, how it is sourced and how hoteliers can utilize its insights to improve their revenue strategy. Those important, revenue-improving insights wouldn’t be possible without the predictive capabilities of machine learning.
What is machine learning?
In its simplest form, machine learning gives computers the ability to learn from data sets without being programmed to do so. Data scientists build algorithms which are applied to sample data sets to train the computer on what to look for within live data sets. These algorithms learn from historical relationships and trends within the data to produce reliable, predictive analytics.
How is it applied to the hospitality industry?
The process of buying and selling rooms is entirely fluid today. The myriad data sources being used to dynamically determine rates is greater than even the most-seasoned revenue manager could compute on their own. Revenue management systems utilizing machine learning evaluate high-volume, disparate data sets in real time. As more data is ingested, the system instantly evaluates it, tailoring pricing predictions with surprising accuracy and detail.
In addition to dynamic pricing, sentiment algorithms analyze signals from user reviews and social media interactions to improve guest experiences. Demand algorithms strengthen your comp set with insights into weather, events, and nearest neighbors, with longer lead times than traditional methods. Machine learning also evaluates consumer buying behaviors and booking patterns to create fluid segmentation. Right rate, rate room, right customer, right channel, in glorious, granular detail.
Will machine learning replace humans?
It is understandable that some revenue managers would feel a bit threatened. For all the benefits we’ve experienced from technological advancement, one can’t help but recognize the ways it has replaced certain functions of our jobs. Despite what Hollywood wants us believe, machines cannot learn on their own. Revenue managers should embrace machine learning as an enhancement to their knowledge, a powerful resource to bolster their revenue strategy. At the very least, see it as a tool to gain back some valuable free time.
Have questions about machine learning? Ask us in the comments or email us at firstname.lastname@example.org.
For a deeper dive into machine learning, check out this two-part series at bigdata-madesimple.com.