A LOOK BACK AND A PATH FORWARD: DIGITAL TRANSFORMATION AND HOSPITALITY

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If we look back over the past 15-20 years, things have changed dramatically in the area of hospitality technology. The explosion of devices is evolving how we interact with our guests, a phenomenon referred to in various industries as digital transformation. Digital transformation is the evolution of business models and processes through technology. According to the IDC FutureScape: Worldwide IT Industry 2016 Predictions — Leading Digital Transformation to Scale study, by 2018, support 1,000 to 10,000 times as many customer touch points.

When you think about how our guest interactions have changed over time, the nature of hospitality is being challenged. Traditionally, the concept of hospitality was built on one-on-one guest interactions. Back in the 80s and early 90s, when a guest booking was made, it was made on the phone with a reservation agent. This team member was a skilled sales person who represented the first point of contact that a guest or their travel agent or their corporate booker had with the hotel. Relationships were made, and impressions gained from this personalized service.

As the industry developed a more automated approach to the booking process and Global Distribution Systems (GDS) and Central Reservation Systems (CRS) were put in place, guests, travel agents and corporate bookers were able to make reservations without interacting directly with a reservation agent. And with the entry of online travel agents into the booking space, a guest booking could be made without contact with anyone from the hotel company at all.

Along with the changes in how reservations were made, came changes in how we managed them. Revenue Management Systems (RMS) of the early 90s determined which rates to open and close, and how many rooms to sell through the GDS and CRS channels. With single image inventory, a hotel’s availability was relatively transparent. Later, RMS would come up with a price to display through online channels. Availability transparency became price transparency, and it was easy for customers and competitors to understand what prices a hotel company had on offer.

Around 2010, the proliferation of ratings and review sites meant that not only was availability and price transparency a factor in the decision making process, but guests and competitors gained an understanding of the value for their money. With value transparency, RMS systems were charged with factoring the influence of ratings and reviews in price calculations. Revenue Management processes and analytics had become increasingly more sophisticated.

Now, as an industry we are faced with a new challenge in the form of digital transformation. Mobile devices enabled with remote check-in capabilities mean that a guest is able to book, arrive and access their room without connecting with a single hotel employee. Our understanding of our guest’s behavior and intent can theoretically be derived solely from digital data. We cannot rely on team members alone to manage the myriad interaction points between us and our guests. What is needed is an integrated approach to revenue management, marketing and service operations. Great hospitality can no longer be driven by the team members that you have interacting with your guests (although your team is of course an important part of this process!). Great hospitality needs to be driven by data and analytics.

Let’s start with the data we have on our guests. Unlike many of our competitors, we actually have a lot of data about our guests and what they do in our properties. If you think of an online travel agent, they collect a lot of information about the booking experience. They know what the guest has looked at, the choices they have been presented, and the selection they made, including arrival and departure dates. They may even have additional information about how the guest will get to the hotel, and whether they are using a rental car while they are staying. Even competitors that are disruptors such as Airbnb, onefinestay and Home Away have access to data about the search and booking process.

If you compare this to the data a hospitality company has on its guests, you can see the opportunity that data can afford you to understand your guests better. If the guest books directly with the hotel or in the brand.com website, you also have information about the guests search and booking choices. The opportunity (and to some extent the challenge) from a data and analytics perspective is in all of the data we collect about the guest’s stay experience. It’s here that you can truly begin to understand your guest’s intent, behavior and preferences.

Once a guest checks-in, perhaps they go for dinner in the restaurant. In the morning they may go to the gym and eat breakfast in the Lobby Café. During the day they have booked a meeting room, and after their meeting they use the spa. If you add this information to the data that you collected on the guest during the booking process, you can start to flesh out a more complete picture of that guest. Not only can you understand how they like to interact with you, via your mobile app, on your website, or in person, but you can also understand your guest’s behavior and intent.

Using this data along with analytics, you can better personalize your guest experience to your guest’s expressed (and inferred) needs and preferences. Let’s explore how this could work across the entire guest journey for Ann Roberts, a guest who is a frequent flyer and hotel loyalty program member.

Booking Process

Ann is looking for a weekend getaway at a downtown hotel. She finds a property with a spa close to the local theater district and goes ahead and books the hotel. During the booking process, web data from Ann’s search is used to update her guest profile.

Pre-Trip

In the lead up to her getaway, Ann uses the hotel’s mobile app to review the spa operating hours and reviews the various massage services available. Ann also browses through photos of different suites.

Data from Ann’s use of the mobile app is used to update customer preferences in her profile.

Arrival

Once Ann arrives at the hotel, she is offered a reasonably priced upgrade to a suite, which she accepts. The front desk agent also offers to make a spa appointment for Ann during her stay. The preferences that we learned about Ann are matched to room type and spa availability, and an appropriate offer is highlighted for the front desk agent to give to Ann.

Mid-Stay

Ann completes her massage appointment, which she enjoys. After the massage, Ann inquires with the Concierge about tickets to local theatre. Ann attends the theatre and tweets afterward, “Awesome show tonight at Theatre Y.” Social media monitoring flags the tweet from Ann for a response, and real-time decision manager identifies the next action to take with Ann. The hotel team picks up Ann’s tweet and messages her with an invitation to an exclusive after-party at the hotel. Ann joins the party and has a great experience interacting with the cast of the show.

Post Departure

Ann checks out after an enjoyable weekend away. A few days later she receives an offer for a week-long getaway to one of the hotel chain’s destination resorts, which she is planning to redeem. Ann’s customer profile was updated with her latest stay information, and her customer lifetime value calculation was re-scored, which drives the next email offer to Ann.

Any company in the service business needs to be focused on its customers. However, hotel guests are interacting with hotels via many more channels, and the larger the organization, the more the touch points – not only on property, but also via the web, mobile apps and call center. Each contact a hotel operation has with their guests is an opportunity to nurture guest loyalty, leading to increased stays and on-property spend. Each of these contact points also generates data about your guests. How can hospitality operations harness that data and make it work for them to deliver consistent and personalized service?

The benefits of solid data management do not stop with data. Once you have a 360-degree view of guests, descriptive and predictive analytics can be applied to the data to help gain better outcomes. Consolidated information about guests allows hotel companies to understand a guest’s total current and potential value, helping them to evaluate and optimize the offers they make to guests. Predictive analytics, such as forecasting and optimization, have been used in revenue management applications in hospitality companies for many years. However, as hospitality companies are in the business of selling an experience, they should also focus analytic efforts on the relationship they maintain with their guests.

Natalie Osborne is senior industry consultant for SAS Institute’s Hospitality and Travel practice, and an 18+ year veteran of hospitality and hospitality technology solutions development, specializing in analytics and revenue management. Prior to joining SAS, Natalie was the director, product marketing for Minneapolis-based IDeaS Revenue Solutions, where she worked from 2000 to 2011. She is a frequent contributor to industry publications, speaker at industry conferences and is coauthor of the SAS and Cornell Center for Hospitality Research blog, “The Analytic Hospitality Executive.”

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