I recently wrote about incorporating predictive analytics into your strategy. To help you see the power of predictive analytics, today I’d like to explore an example of how predictive analytics can be used in the hospitality industry.
The Business Problem
An independent boutique hotel in Phoenix was looking to increase on-site amenity sales (i.e. spending at their golf course, tennis courts, spa, room service, restaurants and shops) during the off-season. Their data had shown that not only was their occupancy rate lower during the off-season, but on average off-season visitors spent less than on-season visitors as well.
The hotel also knew that increasing on-site amenity sales could also have somewhat of a “halo” effect on their occupancy rates, because guests who use room service or spend time on the golf course or in the spa tend to feel more “taken care of.” And as Gallup’s 2014 Hospitality Industry Study showed, there’s a very strong link between guests’ feelings of well-being and customer engagement…and fully engaged hotel customers will act as brand ambassadors and go out of their way to stay at the brand’s hotels.
Predictive analytics was used to take a deep dive into the hotel’s databases, tie this information in to customer profiles and personas, and understand the patterns of the people who come to the hotel over the course of the year.
Some of the questions that they were able to answer include:
• How much do off-season guests spend on amenities? How does this compare to on-season guests?
• Do certain demographic groups spend more than others, or more on certain types of amenities?
• Do certain demographic groups come to the hotel more frequently?
• Why are off-season guests coming to Phoenix? Are they coming for an event, to escape the cold, to take advantage of off-season rates, or what?
• And more.
They then used this data to create a variety of marketing programs. For example:
• Once they discovered that many guests came to town for the annual Phoenix Open Golf Tournament, they planned a special event: a dinner mixer in their high-end restaurant featuring a popular golf pro as the special guest. They also made it a point to put golf shirts, shoes and balls on sale in their store during this time period.
In addition, guests were offered an incentive to stay for an extra night after the Tournament ended. “Stay an extra day to relax – Get XX% off at the Spa!”
• For those guests who came to Phoenix for spring training, a special offer was created for the restaurant: Bring in a spring training ticket stub and get a free dessert with your dinner. Knowing these guests would be leaving the hotel during the day, they gave these people a good reason to come back in the evening.
• The hotel knew that retirees who were there to escape the cold were more likely to hang out at the hotel and use the amenities. For this group they offered breakfast special and discount packages combining popular golf and spa services.
• For return visitors the hotel offered more of whatever the guests enjoyed on their previous visit.
Predictive analytics helps the hotel identify patterns, segment customers, personalize the marketing and create programs that worked.