“I stayed in a really old hotel last night,” comedian Steven Wright once quipped. “They sent me a wake-up letter.”
While some companies in the hospitality industry may be less innovative than others, those at the front of the pack are moving at the speed of light. Switched-on hotels use big data and analytics to enhance everything from their revenue to the customer experience. They have to—current challenges make the industry a difficult market to play in.
Yield management is one such challenge. Hotel rooms are a fixed resource, but their prices are highly elastic, varying according to interconnecting criteria like demand, time of year, and weather. If you charge too much, you risk losing revenue to lower-priced competitors; if you charge too little, you leave money on the table. Determining how much to charge is a data-intensive task; thus, it’s a perfect candidate for big data analytics. The more useful data points a hotel can get, the more certainty it can provide about future conditions, leading to better pricing decisions.
Starwood Hotels and Resorts Worldwide has become adept at data-driven yield and revenue optimization. The hotel chain uses big data to determine pricing on rooms over time. The company relies on internal and external data sources that provide information about everything from weather to forthcoming conferences and even competitors’ performance. Even data about customers’ past travel preferences factors into decisions.
Along with optimizing revenue per room, innovative hotels are constantly striving to maximize revenue per customer. That means understanding their characteristics and behaviors, and adjusting amenities to suit. By looking at what customers and their demographics do, it’s possible to distinguish between customers in different segments. One customer may have a high potential spend for a single weekend but is not a frequent visitor. Another may not buy many extras, but nevertheless is more profitable because of regular visits.
This customer segmentation may vary by region and affect what hotels spend on services, even across different groups. For example, one analytics-driven study of the hospitality industry found that a hotel gets between $3.40 and $7.00 in extra customer revenue for every dollar spent on Wi-Fi, and up to $30.00 of extra revenue for providing a single complimentary bottle of water. It also found that exercise rooms, while generating no additional revenue, heavily influence a customer’s decision to return.
Starwood is a company that uses big data for marketing campaigns. It draws on analytics to deliver promotions to guests before and during their stay. It can even watch guests refine their searches to a time and place, and add an incentive to ensure they follow through with a purchase. For these processes, Starwood uses previously gathered data about its customers to determine the most appealing incentives.
InterContinental Hotels Group uses mountains of customer data to determine the interests of its hotels’ customers. Its personalization process refines every time the customer returns. It claims 500,000 possible combinations of travel behaviors and loyalty program interactions.
Because the hospitality industry is often based on time-critical situations, there’s plenty of opportunity for hotels to innovate. Red Roof Inn increased its year-on-year growth by 10 percent partially by drawing on public data feeds to provide historical weather information. This data enabled the hotel chain to better predict where the estimated 2-3 percent of daily canceled flights would occur in the U.S. The hotel could then use targeted search advertising to offer a room to specific stranded customers.
With mobile in the mix, big data marketing takes on yet another dimension. Over at Oceanfront Properties, innovators combined geofencing with highly targeted Facebook advertising to target mobile app users who fit its targeted demographic. If their cellphones showed they were within three miles of its restaurant during a set Friday evening window, the chain offered this target group free valet parking. Executives said the 150-car lot filled up almost instantly.
Some hospitality companies are innovating further by using wearable technology to enhance the customer experience. Disney World’s wearable MagicBand feeds back data on everything from hotel check-ins to ride access and product purchases, creating a river of data that enables the company to offer that personal touch. Armed with these data insights, servers you’ve never met before will greet you by name. Your journey around the park will already be planned, based on your favorite rides, to minimize your wait. What does the company get in return, apart from your loyalty? It has all the data it could want to refine how it markets to future customers.
Big data analytics, well-trained staff, and attention to detail can create a virtuous feedback loop for companies in the hospitality industry. By crunching the numbers, they can not only increase the revenue for each customer but also make it far more likely that the same customer will seek them out in the future.
If you’re ready to reduce your path to purchase in the hospitality field, it’s time to consider predictive analytics.