Mark Ross-Smith spoke with Jonathon Wardman, Vice President CRM at Hilton about hotel guest data, how Hilton is leveraging the use of data, and the success of the much publicised Stop Clicking Around campaign. Hilton isn’t known as being on the forefront of big data, so Mark asked Jonathon what was happening under the hood.
Jonathon has been with Hilton for over 10 years in business technology roles. For much of his career, working on projects that design, build or implement revenue management systems. Jonathon took over CRM three years ago with the goal of expanding optimisation, data-driven marketing and personalisation across the customer journey and in all customer channels.
MRS: Hilton collects a lot of guest, hotel and ephemeral data. What challenges do you face in utilising this data?
JW: We are very fortunate in that our guests are willing to engage with our brands more than ever. We are able to find out about our guests’ preferences before, during and even after a stay. In return, our guests expect the most personalised experience possible. Delivering a consistent, timely, and relevant experience for every one of our guests is one of our biggest opportunities and one that we will continue to focus on as we continue on this personalisation journey.
MRS: To what degree is data-driven decision making used to improve the guest experience?
JW: By booking directly with us, we can collect data about our guests’ preferences. Does a guest want a room close to an elevator? Do he/she prefer a high or low floor? Does the guest need extra towels or pillows before check-in? By mining this data, we can anticipate our guests’ needs and consistently deliver a great experience. We also conduct regular qualitative and quantitative research to keep up with our guests’ changing needs and focus on what they care about most. We also analyse our own guest feedback from Hilton’s SALT (Satisfaction and Loyalty Tracking) surveys to learn more. For example, we knew that wifi was the most widely used on-property amenity according to our customer satisfaction data, which is why we made it a complimentary benefit for all guests who book directly with Hilton.
MRS: In 2016, Hilton launched the ‘Stop clicking around’ campaign to promote booking direct at Hilton.com. Can you share some insights and data around the success of the campaign?
JW: The Stop Clicking Around campaign was a huge success, particularly as it relates to Hilton HHonors. We quantified the success of the campaign against our key pillars of measurement (i.e., membership base and satisfaction and tool/benefit usage). In the last year alone, the program gained more than 9 million new Hilton HHonors members. Awareness around the Hilton HHonors app has also surged to an all-time high. The app is now the highest rated travel app in the app store, downloaded once every eight seconds – that’s more than 600 times an hour.
MRS: How important is data-science to Hilton from a strategic viewpoint?
JW: Our commitment to guests in return for sharing data and preferences is used to deliver personalised experiences. Data science is a key capability that enables us to find trends to help get smarter in product design (from where we build hotels, new brands, room design, pricing constructs), marketing (real-time, omni-channel, relevant and timely) and in delivering exceptional customer experiences.
MRS: Data-driven or gut feeling marketing? What is the right balance?
JW: It’s definitely a balance. We work with a lot of data, and the biggest opportunity for us is knowing how to use that data and truly understanding it, especially as it relates back to the guest experience. Factor that in with a great marketing campaign, such as Stop Clicking Around, and you’re able to attract new guests and find out more about our existing guests. Ultimately, it all works together to enable us to provide the best experience to our guests.
MRS: Most hotels have a difficult time in selling premium rooms, and suites. How is Hilton leveraging big data/business intelligence to buck the trend and achieve higher paid occupancy in suites?
JW: Hilton has a set of comprehensive tools to help hotels measure RevPar by room type and to optimally price /revenue manage premium rooms. We are continually reviewing the display and content used to market premium rooms, and we’re currently testing retailing room upsell offers in the online booking path. Our digital check-in platform, which offers Hilton HHonors members detailed floor plans and personal room selection before arrival, is a logical platform on which to expand the retailing of premium rooms.
MRS: ‘Personalisation’ is an industry buzzword currently. Hotels have been on the forefront of providing highly personalised guest experiences for decades, but, moving forward, how do you see technology and the role of big data playing a deeper and more important role in guest personalisation?
JW: People depend on their mobile devices more and more and we’re seeing this in the hospitality industry, as well. By giving Hilton HHonors members the ability to turn their phone into the “remote control” of their stay, members can personalise their stay and take any friction out of the travel experience. For example, members can use the app to view the hotel floor plan and choose their room based on the best view. Or if members want to by-pass the front desk, they can enable Digital Key to go straight to their room. By utilising the app, we are also able to pull these preferences and gain a better understanding of what our guests expect and what they want out of their travel experience.
MRS: What’s the best use of, or most interesting use of big data/data science/BI you have seen in the travel industry?
JW: Hilton recently won the ANA Genius Award for use of data science in matching offers to customers in our email and web channels. From our 13 brands and global regions, we ingest hundreds of offers each month. We employ sophisticated analytics to attribute offers, score customers’ propensities and match the right offer to the right customer. This means computing trillions of possible combinations to find the optimal matches.