How AI-Powered Hotel Messaging Helps Fuel the Guest Journey

When a guest uses a hotel’s native app, it becomes that much easier for it to know exactly who that guest is, and to collect and integrate a record of those guest’s messages as part of their profile information.
By HTN Staff - 5.1.2019

Friction is desirable in many circumstances. Land vehicles, for example, need friction in order to accelerate and decelerate. When it comes to guest satisfaction, however, friction is rarely desirable and hotels strive to put the brakes on any friction that may impede or otherwise negatively affect the guest experience. Guests may experience friction in their interactions and transactions with a hotel across all parts of the property, all touchpoints and all phases of the guest journey.

The guest journey is the record of every interaction and transaction, both digital and in-person, that a guest has with the hotel throughout the entire course of their stay. Hoteliers have become increasingly focused on tracking and analyzing the guest journey, from the moment the guest first steps foot in the hotel lobby to the time they check out of the property.

Arguably, the guest journey begins much earlier, at the point when a guest first sets out to research and explore their stay options and on through the booking process. An argument can be made that the guest journey continues even after they check out of the hotel.

By meticulously mapping the guest journey at an individual or narrowly-defined customer segment level, it becomes possible to identify patterns that speak to shortcomings with the current state of the guest experience and pinpoint specific opportunities for improvement. Of course, conducting this exercise is no easy feat.

In fact, until now, performing an in-depth analysis of this intensity, at scale, has been next to impossible given the time, effort and expertise involving advanced analytic modeling techniques and specialized tools.

The good news is that artificial intelligence can help automate the process of sifting through massive amounts of data, making sense of the findings and then meticulously assessing all the different factors that have an important impact on the quality of the guest experience. This means, among other things, dissecting all the drivers of guest satisfaction at a granular level, which may include unexpected sub-attributes of service quality perception.

As machine learning moves from buzzword to functional reality in the hospitality sector, it seems all but certain that it will play an increasingly important role in helping hotel operators hone in on the different elements of the guest journey, monitor and assess performance, and flag shortcomings that need to be addressed. In some cases, it may even resolve issues without the need human intervention and also suggest new innovations to improve guest satisfaction.

According to new research conducted by Starfleet Research in partnership with Oracle Hospitality, 82 percent of hoteliers cite the ability to “capture data from which hoteliers can generate actionable insights for improving business processes and driving innovations that further enhance the guest experience” as a top benefit of an AI technology initiative.

To be sure, hoteliers believe that artificial intelligence is here to stay and that the evolution of related technologies will progressively improve the overall guest experience.

These technologies may be both internal-facing as well as guest-facing solutions, the most important of which may also represent the most simple use case: smartphone messaging apps. Indeed, guests interacting with a hotel via a messaging app on their smartphones has proven to be the most effective way for hotels to stay connected with guests through all phases of the journey.

Let’s face it: A hotel’s only real currency is its relationship with its guests. Ease of communication is key to facilitating that relationship. This explains the groundswell of activity around hotels offering guests the ability to text or message with them through any number of communications channels. These include established messaging channels like WhatsApp and Facebook Messenger (now available to developers) as well through their own proprietary messaging apps and bots — or, in some cases, through other third-party technologies.

Large hotel companies have gravitated toward launching their own proprietary messaging apps. The additional functionality adds value to their native apps, which in many cases offer features like mobile check-in and check-out and keyless room entry.

Importantly, proprietary apps allow hotels to create a more extensive and richer data connection with each individual guest. When a guest uses a hotel’s native app, it becomes that much easier for it to know exactly who that guest is, and to collect and integrate a record of those guest’s messages as part of their profile information.

By being able to tie messaging back to their guest profile, a hotel can know, for example, that a guest has used the spa on each prior visit. It can message the guest to inform him where the spa is located and its opening hours and even send a special promotional offer.

While different approaches to messaging with guests have different advantages and disadvantages, all of them have the same goals: to build guest loyalty, increase guest engagement, and enhance the overall guest experience.

Many hotels send guests an invitation to their messaging app after they book their stay. On an opt-in basis, guests can receive pre-stay notifications and view key reservation details. They can explore neighborhood guides, set their preferences, and communicate with the social care team.

When it comes to the evolution of hotel messaging, the big question has been: to what extent will messaging apps incorporate artificial intelligence? Also: will the conversation between hotels and guests shift from a request-based one to more of a two-way dialogue? As times goes on, it seems clear that the latter will be the case, and, also, that the conversation will be largely enabled by artificial intelligence.