AI Case Study
Dorchester Collections personalises guest experience with machine learning analytics
Hotel operator Dorchester Collections analysed its customer reviews using machine learning software, Metis. The software identified that guest were far more interested in breakfast than dinner as a meal, to which hotels tend to focus their investments on in order to differentiate themselves by offering a fine dining experience. As a result, based on the findings and suggestions of Metis, the hotel operator made its breakfast options highly personalised and customisable.
Consumer Goods And Services
Travel And Leisure
Metis, a machine learning software which analyses online customer reviews reported that guests of the Dorchester Collection hotels wrote more about breakfast than dinner in their reviews and seemed to be particularly interested in customising this particular meal.
"It turned out Metis was right: Dorchester kitchens reported that somewhere between 80 and 90% of breakfast orders are modified.
So today, when you sit down to breakfast at the Beverly Hills Hotel (which has 1,019 reviews on TripAdvisor, 298 on Booking.com, 235 on Yelp, and 294 on Expedia), a waiter comes up to you and asks what you want — they've got everything. No menu."
Now, Metis is taking the massive trove of consumer data on customer review sites like TripAdvisor and Booking.com and turning it into market research that will tell businesses what their elite clients want, before they know they want it. It began with a little bit of customer feedback."
According to Ana Brant, the director of guest experience and innovation for the Dorchester Collection, "hotels of this kind throw mountains of money at celebrity chefs to build fine dining destinations. Dinner is the main event. Breakfast is often an afterthought."
Ana Brant reports that customers had a positive reaction to the changes initiated based on the machine learning powered analysis of their reviews
"machine learning software that could look for words and phrases that correlate with important customer service metrics like emotional bond and loyalty."