Hotels continue to invest in analytics so they're in a better position to optimize revenue, deliver better customer experiences and improve operations. Like other organizations, hotels realize they can improve their competitive position using data and analytics more effectively than others. To do that, they need to integrate data coming from different functional areas and connect internal data with external data to make material improvements across the board.
Hotels are moving past historical data and current bookings to maximize room occupancy and profitability. To improve their effectiveness, they're using competitive data, weather data, event data, predictive capabilities, and more. Starwood Resorts is experimenting with machine learning and neural networks to change pricing dynamically, rather than twice or three times per day or seasonally.
The goal is to optimize the profitability of each room, not just hotels at large.
Customer loyalty programs have evolved with data analytics capabilities to provide guests with better, albeit different, experiences. For example, some guests care more about the quality of concierge services than Wi-Fi. Hotels must understand such differences to understand a guest's preferences and cater to those preferences. After all, every customer has an individual expectation of what a "good" hotel experience is, not just the Premier or Platinum members. While the most profitable and loyal customers deserve exclusive benefits, catering to them should not be done at the expense of other guests.
To provide better experiences at all levels, hotels are attempting to understand their customers more holistically than they have in the past to provide a relevant experience. Having a "special requests" textbox in a booking application yields some information, so are customer requests and feedback recorded at the front desk. Another way to understand customer preferences is to slice and dice room offerings based on non-traditional amenities, such as allergen-filtering, in addition to the usual size, price, category and smoking/no smoking designations. Tracking a customer's preferences over time, helps too in an effort to anticipate guests needs and desires.
These days, loyalty isn't something that kicks in at check-in. Hotels are using search, online bookings, social media, call center data, front desk data and surveys to better understand customer journeys and what people want.
Moving up a level or two, some are targeting Millennials, which included Pokemons in the pool and on beds at Marriott hotels, clearly a non-traditional "benefit," though an attractive benefit for those caught up in the Pokemon Go craze. The campaign happened to be a very smart marketing move from a social media point of view -- free advertising.
The relationship among marketing, customer loyalty and revenue optimization enables a continuous feedback loop where insights from one bucket inform the others. And that's not all.
Third party data can be very valuable from a predictive point of view when it impacts hotel occupancy and profitability. Weather and event data are two examples. Here in Sedona, Ariz., wildfires and heavy monsoon rains can cause massive hotel room cancellations. In other cities, popular concerts, sports games and flight cancellations cause a spike in demand. While those things may seem intuitive, actual data feeds can help hotels plan for the dips and spikes more accurately, so they can right size things like staff on hand and supply orders.
From an internal perspective, hotels need to monitor and constantly improve the efficiency of individual functions such as housekeeping, not only to reduce costs, but to keep up with competitors' improvements. Some operational information is used to craft marketing messages such as Starwood Hotel's "Smart check-in."
Analytics is also providing insight into age-old issues such as sluggish room service. Is the problem too many simultaneous orders, too few members of the kitchen staff, poor kitchen management, something else or a combination of things? Operational analytics provides some insight as will guests' social media posts, survey data, call center data, front desk data, etc.
Hotel chains have mobile apps that give them even more insight into customer behavior, especially as they expand out from reservations made using a mobile device to keyless entry (using a smartphone), mobile food orders and more.
Some hotels are adopting "mobile first" strategies given the popularity of the devices and the fact that more hotel customers are using mobile devices instead of laptops to book rooms.
Hotels face many of the same problems enterprises face generally, not the least of which is connecting dots in a way that is valuable to their organizations and customers.