This is the year where small subsets of customers, and even individuals, are served up solutions geared specifically to individual desires and pricing thresholds. It’s an extraordinary time reimagining the relationship between customers, hotel brands, and the properties consumers select.
In this article, LodgIQ discusses how technology is transforming the way hoteliers connect with guests, and how guests connect with them.
Big Data Front and Center
Thanks to the internet, everything everyone does online leaves a digital footprint. That footprint is called Big Data; giant, disparate subsets of disparate information. An additional 2.5 exabytes of data are created daily, according to Northeastern University. One exabyte is equivalent to one billion Gigabytes. It’s so much that traditional methodology isn’t powerful enough to find patterns within the data.
When hoteliers utilize the right methodology, they’ll optimize revenue more efficiently, but they must see the intelligent data hidden beyond historical demand and comp sets. Information can be gleaned from categories such as peer-to-peer vacation rentals, room rates of indirect competitors, historical market room rates, market flight capacity, meteorological patterns, local events, website traffic, regrets denials, in-funnel conversions, sentiment, and more.
From these seemingly endless streams of data, more solid intuitive and reactive forecasting can be achieved through sophisticated algorithms and optimization achieved through machine learning.
Computer scientists have made a breakthrough with machine learning. We see it already in places such as Netflix which suggests programs to watch and how Amazon suggests a product you might like to buy.
In the hotel business, machine learning can be used to process the vast amount of data that is constantly created. It uncovers patterns and pricing opportunities by weighing the importance of each bit of data from those aforementioned subsets, then provides rate predictions for a given hotel on a given day.
When machines get to know the target customer’s desires, its better able to suggest to individuals the experiences and opportunities more in line with where they want to go, do, and willing to spend just as Google has done with destination getaways.
But when machine learning is tied to social media outlets and other data points a computer can generate more informed destination, hotel and activity suggestions.
It’s about serving up options immediately resonating with potential customers urging them to book on the spot. This heightened call to action is essential because the way people research travel is morphing.
Planning a trip is no longer completed during a few long research sessions. Rather, customers are gobbling up bite-sized bits of information in sliver-sized moments. They’re researching that getaway while simultaneously working, researching, and entertaining themselves via mobile devices. Google's "Micro-moments" report notes 87% [of users] have their smartphone at their side, day, and night; the average person checks their phone 150 times per day and spends 177 minutes using it. According to eMarketer, U.S. adults spend nearly three hours per day on "non-voice activities on mobile devices."
This behavior shift has created a massive change in how customers interact with hotels, something owners, operators and those in charge of generating revenue have yet to fully grasp. When a trip is approaching, that potential customer is most likely researching travel products in tiny morsels while on the go, perhaps reading hotels reviews, watching social media consumer created content, or exploring local offers pushed directly to their smartphone.
Everything we thought we knew about revenue management has changed. The game, the rules, the players; everything. Now, delivering powerful results means reinventing how the hotelier connects with guests before they become guests.