Lodging AI can help travel agencies improve hotel attachment rates, creating additional revenue opportunities and providing travellers with more personalised lodging options. Using Sabre Travel AI machine learning models, the new lodging capability analyses property attributes, customer trip segmentation, and traveller and agency preferences to generate custom lodging options and serve up properties that are most likely to be booked.

 “Artificial intelligence combined with data and insights, such as profiles and preferences, is a very powerful tool in removing friction from the travel booking process,” said Garry Wiseman, chief product officer, Sabre. “As the next evolution of intelligent retailing capabilities supported through our strategic partnership with Google, Lodging AI brings more personalized results to enable agents to be more efficient in their workflows and to ensure travellers obtain the most relevant options available.”

 The first two micro-services of Lodging AI are now available, with additional use cases to be added in the future.

• Alternate properties: During the shopping phase, if a specifically requested property is not available, this micro-service of Lodging AI facilitates lodging bookings by presenting up to 20 relevant options with similar characteristics.​
• Cross-sell: This micro-service identifies appropriate air bookings or itineraries without lodging attached and presents suitable lodging options to complete the trip.