Halldis finds the ideal stay using Oracle Cloud

Halldis uses Oracle’s Autonomous Database, Analytics, and IoT Cloud to help pair travelers with rental properties that match their interests and budgets.

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Because we don’t have an IT department in our company, we chose Oracle Autonomous Database and Oracle Analytics to manage all of our data, run our algorithms, and help our sales and finance people choose the right apartments for our clients.

Francesco IarloriHead of Innovation and Revenue, Halldis

Business challenges

Halldis uses advanced technology to personalize the guest service experience. With more than 1,850 apartments, they provide accommodations tailored to travelers in the leading tourism cities in Italy, as well as in London, Paris, and Brussels. When a vacationer or business traveler inquires about booking a rental property, Halldis matches the traveler’s age, interests, trip purpose, and budget with the properties and types of activities that most closely correlate to those personal characteristics.

To maximize occupancy, the company’s sales and marketing staff can also dynamically adjust pricing based on seasonal demand and inventory availability. During busy holidays or dreary weather, Halldis may advertise on popular booking and search engines, incurring commission costs instead of relying on direct bookings, which cost them less. All of the property matching, pricing, and advertising decisions are made on a daily basis and require multiple data points to be connected and fed into algorithms to help management act quickly.

Why Halldis Chose Oracle?

Halldis doesn’t have an IT department to pull data and produce personalized recommendations for guests. The cloud-based Oracle Autonomous Database handles those tasks, using machine learning to automate database updates and management, so there’s no need for IT teams to do maintenance and no opportunity for human error.

Results

Oracle Autonomous Data Warehouse and Oracle Analytics, running on Oracle Cloud Infrastructure, have helped automate the Halldis property recommendation engine. The company relies on machine learning to help sales and marketing teams deliver guests personalized accommodations, guide advertising decisions, and increase repeat bookings. 

With an API running from Oracle’s JD Edwards EnterpriseOne to Oracle Cloud Infrastructure, Halldis’ finance department can submit invoices faster and more accurately and better control maintenance costs and other expenses, ultimately improving cash flow.

To help determine the types of properties and services to offer its clients—and at what prices—Halldis uses Oracle IoT Asset Monitoring Cloud to remotely analyze sensor data from each of its rental properties. It factors in a client’s typical energy usage, room temperature, occupancy status, and more by remotely monitoring each property. By tracking that data, Halldis knows the variable and fixed costs associated with renting its properties and can offer personalized pricing that improves profitability and enhances the travel experience.

Published:May 27, 2020