Mobile devices and the on-demand economy have changed the hospitality game. Consumers now expect convenience, personalization and almost-instantaneous service. Businesses, like hotels, are now equipped with a trove of data that informs them how they’ve performed in the past, how they’re performing currently and how they may potentially perform in the future. Notably, the data that the hotel industry turns to isn’t gleaned from surveys dispatched by the hotels themselves. The data comes from any and every possible touch point including online review platforms and social media channels.
As of April 18, 2017, 48 percent of the reviews left for the predictive analytics software category on G2 Crowd are attributed to enterprise users. According to all reviews, 64 percent of users agree that predictive analytics tools are going in the right direction, despite the majority of them only having one-to-three years of experience with the products.
This is a significant statistic, considering that predictive analytics evolved into existence specifically to merge the gap between data scientists and front-end users who are less familiar with how to translate and grapple with collected business metrics. The software itself is a disruptive piece of technology, and hotels seem to be using it to fight back at a disruptive force in the industry—Airbnb—to keep up with the escalating need to please customers.
In response, hotel giant Marriott is “rolling out many tech-driven amenities,” reported the The Wall Street Journal. If the convenience of the Airbnb mobile application has proven anything, it’s that end users respond well to the ability to merge their proclivity for tech and their mobile devices. Hotels are taking that knowledge and consciously integrating and deploying new technology to update hotel operations.
According to BizTech Magazine, a CDW editorial that explores technology and business issues, “Technology is no longer just solving backend business problems or allowing guests to connect their devices to the Internet.” Rather, the data derived from that technology “can also be used to power predictive analytics, enabling a hospitality provider to make accurate, financially beneficial predictions about a wide range of future events.”
Great timing, since we’re actively in “the age of the customer,” according to CMSWire. What that means for businesses is that they can apply technology like predictive analytics and machine learning software to captured customer data to ultimately align themselves to the customer-centric “mantra of the day.”
Below are the ways predictive analytics can innovate and sustain the hotel industry:
Business intelligence (BI) platform GoodData, which received a Leader badge in the Winter 2017 BI Platforms Grid℠ Report, explained that “predictive analytics aren’t simply a fancy new tool, available to only a fortunate few in the travel and hospitality industry. It’s our view that they should be—and will be—available to everyone. With predictive analytics in place, the travel and hospitality industry is poised to reach a new level of efficiency and productivity.”
However, analytics can only achieve those new levels when disparate sets of data are gathered into one place. After all, for analytics to find the relationships that will increase revenue, margin and share, they need to run through consolidated data.
Departments that align with each other can help consolidate that data. Sales, marketing and support must share data and insight with the departments that deal daily with customers and transactions. Then, predictive analytics can do the heavy lifting of sifting through all that consolidated data as well as creating visualizations and models that will inform businesses of the steps they will need to take to keep customers satisfied and their operations running smoothly, without unexpected hurdles.
Increasing Customer Satisfaction
Speaking about customer satisfaction, the impact of personalization cannot be underestimated. Existing businesses in all industries already know this: Why invest in an email marketing software or marketing automation software if not to better manage and deploy hyper-personalization efforts?
Hospitality Technology, an online resource for hospitality operators who want to understand the relationship between technology, intelligence and business operations, explained that with predictive analytics, hotels can anticipate guests’ behaviors instead of merely replicating it. This is an important part in moving the hospitality industry “toward greater sophistication and personalization. The loyalty program of the future won’t just ask travelers what they want, it will divine unanticipated and even unarticulated needs.”
Understanding and meeting customers are various touch points—beyond the obligatory check-in, check-out and interactions with the concierge—allows hotels to plug into an individual’s customer journey as a whole. Hoteliers can apply the forward-looking solution of predictive analytics, of building decision models to plan for the best possible outcome and identify potential risks and opportunities for a company, to their business operations.
Planning for the Long Term
In the same way the taxi services dealt with how Uber (so obviously) disrupted the industry, hotels must come to terms with the competitive disruption Airbnb has wrought. Proactive decision making is key here, which is why predictive analytics are so invaluable for things like optimizing pricing, efficiently booking of staff members and managing fluctuating shifts in demand. The forecasting ability of predictive analytics empowers hotels to make that move.