From Static Hotel Brochures to Dynamic Guest Experiences: How AI Will Drive the Evolution of Hotel Websites

Unveiled a year ago today as a “low-key research preview,” and quickly emerging as the poster child of the AI revolution with over 100 million users accessing its website in the first two months of its launch, ChatGPT remains foremost on our minds and numerous hoteliers already see the value in how this technology will scale their businesses in the near future. But what underpins ChatGPT is what’s called machine learning (ML) and there are several companies that have been in weeds with it for long before this became a buzz term. Namely, using ML we can now reorder and rewrite website content on the fly to adapt to the customer at any stage of the guest journey.

This idea of adaptable hotel websites with automated personalization and integrated booking engines (IBEs) that have memory represents a paradigm shift that will serve to unlock substantial new economic value for brands and independent properties. In order to explain this concept without getting too abstract or heady, we interviewed Frank Reeves, Chief Evangelist at SHR Group, to discuss the company’s next-generation website and IBE platform called allora.ai. Reeves is also the co-founder and CEO of Avvio (the developer of allora.ai) which was acquired by SHR in late 2022.

When we talk about rejigging content automatically to fit the customer journey, the word to remember is ‘context’. The more contextual data and interactive feedback a system has – as derived from the entirety of guests accessing websites or going through a hotel’s IBE – the more a platform learns what a guest might want. The outcome here is that the ML can better predict the optimized orientation of a website’s content in order to achieve a specific goal, such as boosting reservation conversion rate.

As Reeves puts it, our current websites are ‘static digital brochures’. A customer enters, and while tracking mechanism like pixels may tell the analytics platform where this user came from (IP address, mobile versus desktop, organic versus paid ad and so on), the website doesn’t react or A/B test how the information is presented in order to better fit the context of the customer.

How might it look like if an AI is able to learn and reconfigure content based on each time the same guest accesses the same website URL over time? Consider the following:

• Interaction #1 (discovery): the AI can recognize the country where a customer is searching from and, if it’s overseas, rewrite the content to state, “Enjoy our spa after a long-haul flight.”
• Interaction #2 (early prebooking): with the initial clicks acting as a profiling baseline of interests, the AI can showcase a review of the hotel’s dining outlet from someone in the user’s country
• Interaction #3 (early prebooking): now with an expression of intent around dining and spa based on user clicks and country of origin, the AI can bring to the top the “Food and Spa LOS” package
• Interaction #4 (late prebooking): now with the intended travel dates plugged into the IBE, the AI can highlight guestroom and suite reviews from past guests in the user’s source country
• Interaction #5 (late prebooking): bringing together every interaction and learning about the prospect, the AI can reorient the rates and packages to create a hyper-personalized experience

The value that AI-powered websites will add to the prebooking phase is by itself remarkable because of how it can help brands to micro-segment customers within the sales funnel, so much so that marketers can now accurately separate the upper funnel from the lower funnel or even the ‘upper-upper funnel’ with specific insights at each partial phase on what motivates guests to move in the right direction.

But, an AI-powered website can also significantly boost ancillary spend (TRevPAR) or keep the relationship going after departure. “Take a London hotel that we work with, for example,” commented Reeves. “We observed from both past guest behavior on this brand’s website and from the totality of interactions across all hotels using the allora.ai platform that travelers who had already made a direct booking and who originated from the United States have vastly different needs leading up to arrival over those travelers coming in locally from within the United Kingdom. Monetarily speaking, past US travelers highly favored F&B content, so prioritizing the display of various dining options for incoming guests from the US resulted in more prearrival F&B revenue per guest and more on-premises utilization.”

Such a blend of macro and micro opens a wholly novel website functionality: reducing cancellations. Because the system knows who is more likely to cancel a reservation during the prearrival phase based on past cancellation data from all travelers at all properties on the platforms, managers can use this information to proactively send out cheerful reminders in the days leading up to arrival or even send out additional incentives to those ‘risky’ guests such as F&B vouchers.

With this, we can now map out beyond just prearrival and see how an adaptable website can add economic value to the entirety of the customer journey. To close, consider the following:

1. Discovery: apply learnings from past website visitors and systemwide patterns to make a better first impression with a new user, encouraging them to revisit versus book through an OTA
2. Early Prebooking: rearranging content based on dream phase interaction and use ML to deduce what content best optimizes for continued engagement and conversions
3. Late Prebooking: further personalize website and IBE content, possibly adding a booking incentive to further encourage a direct sales versus one made through a third party
4. Early Prearrival: optimize the display of add-ons based on what’s known about a guest in order to maximize revenue on the books, which also helps with staff scheduling
5. Late Prearrival: defend against possible cancellations through website personalization that accentuates how great the onsite experience will be combined with other one-to-one offers
6. Onsite: act as a virtual concierge to relieve onsite teams by displaying most relevant information as well as show the most relevant add-ons to further amplify more property usage and TRevPAR
7. Early Post-Departure: show a thank you note and other departure information to amplify how the onsite experience was perceived, meaning higher guest satisfaction and better reviews
8. Extended Loyalty: after some time has passed, entice return visits by highlighting what’s new onsite in relation to the context of the guest’s past stay

Once you compute all these possibilities for added value, your website can now truly become a gamechanger beyond just being a static brochure.

Together, Adam and Larry Mogelonsky represent one of the world’s most published writing teams in hospitality, with over a decade’s worth of material online. As the partners of Hotel Mogel Consulting Limited, a Toronto-based consulting practice, Larry focuses on asset management, sales and operations while Adam specializes in hotel technology and marketing. Their experience encompasses properties around the world, both branded and independent, and ranging from luxury and boutique to select-service. Their work includes seven books: “In Vino Veritas: A Guide for Hoteliers and Restaurateurs to Sell More Wine” (2022), “More Hotel Mogel” (2020), “The Hotel Mogel” (2018), “The Llama is Inn” (2017), “Hotel Llama” (2015), “Llamas Rule” (2013) and “Are You an Ostrich or a Llama?” (2012). You can reach Larry at [email protected] or Adam at [email protected] to discuss hotel business challenges or to book speaking engagements.

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