AI's Potential Impacts on Hotels and Loyalty Programs

With more companies using artificial intelligence to enhance their travel websites, AI could become the industry norm.

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Ed Stanley: Welcome to Thoughts on the Market. I'm Ed Stanley, Head of Thematic Research in Europe. And along with my colleagues bringing you a variety of perspectives, today we'll be taking deep dive into the ways A.I can revolutionize the travel and booking experience. It's Friday, September the 15th at 3 p.m. in London. 

Ed Stanley: A.I and the company's most advantaged and likely disrupted have been the hot topic of 2023 for equity markets so far. However, the long term impacts and downstream winners and challenged companies remain fairly ambiguous for some sectors, and travel, hotels, OTAs certainly sit in that more hotly debated camp. We also have on the line our US gaming, lodging and leisure analyst Stephen Grambling with Brian Nowak, US head of Internet research. So Brian, if we could start with you to set the scene a little bit. Investors have been wondering about disrupting online travel for years. What does the hotel booking experience of the future look like, do you think? And what does that mean for travel agencies? And then, Stephen, if you want to follow up with your thoughts on the booking evolution and how that looks. So, Brian, first, please. 

Brian Nowak: Yeah, artificial intelligence, I think, is going to really change the overall online travel experience. I think it's going to become a lot more conversational, interactive, personalized and visual, and probably even video based in nature. You know, I think that right now you think about the travel research process where you might be looking for a hotel in Miami the week of the holidays in December that will sleep four people that has access to a beach and a golf course. That experience, the search for that right now is pretty low quality and requires a lot of multiple searches and tabs and apps, and it takes a while. You know, with the way in which these large language models and applications on top of these large language models can search through unstructured data, I think that these online travel agencies and other emerging A.I travel apps are going to really leverage these capabilities and actually just make the entire travel research process much faster, more interactive and more comprehensive. The other thing I would say on the interactive point is I think we are going to move toward having A.I powered online travel agents. Where if I am looking for that one example of a place to stay in Miami the week of the holidays today, but there are no hotels that fit my criteria, two weeks from now and inventory becomes available I may have an A.I travel agent say, Brian, are you still looking to travel in December? Look at the inventory that popped up. So I would just expect the overall travel research and booking process to become much more conversational, efficient and just high quality for all users, which should drive conversion higher and pull a larger share of wallets from offline to online. I don't know, Stephen, how do you think about the potential impacts on the brands from that? 

Stephen Grambling: I think to set the stage there, the most sizable place consumers start their booking process has been historically by researching hotels across price, amenities, location, etc. From the brand's perspective, the key was how do you get a consumer to book with you direct, even if the research was done via another channel? And that is what bore out the stop clicking around campaigns that started in 2016. The brands all launched marketing to tell consumers to stop price comparison all over and leverage loyalty to get the cheapest rate plus certain benefits that they could only get if they booked direct. So what happened? In some ways, the jury is still out due to the pandemic. Where do we go from here? I think, as you described, A.I has the ability to perhaps magnify some of the unique aspects of these brand loyalty programs that were so important to that direct booking campaign, that they can harness both business and consumer travel data that tends to have higher frequency, even if they have lower breadth relative to the OTAs. And as we look right now at the current landscape, when you do these queries that Brian was describing, booking channels are still effectively leveraging whatever the output was from search engine optimization, SEO. And so I think that the opportunity there is if you can train these large language models, either from the consumer dictating it via their preferences, whether it's for loyalty, the amenities they want, the experience they want, or the brands can train them by using the data that they have that's differentiated across both business and leisure. That's where they have an opportunity to actually move a little bit up in the funnel. 

Ed Stanley: Perfect. And you touched on marketing there, you gave some great color on the booking process of the future. Where do you think A.I could have other impacts across the PNL for your names? 

Stephen Grambling: So we outlined five areas A.I can impact hotels. First is obviously personalization of content, whether that's the room food, amenities being offered via video or otherwise. Second is the marketing efficiencies as offers could be more targeted based on feedback. The third is enhanced engagement during and post trip, as you continually interact with these effectively personal assistants throughout the process, not just travel planning but engagement throughout. Fourth is automated customer service, essentially chatbots and virtual assistants. And the fifth is yield and revenue management, where hotels can maximize price and occupancy by better predicting demand patterns using various sources of data. And based on other industries' success in some of these areas, we think that they could add up to hundreds of millions of dollars in benefits to the branded hotel systems across various levels of the PNL. 

Ed Stanley: Perfect. And one of the other things you mentioned with loyalty programs, which are pretty important, you also want to use loyalty programs for your airline hotels. Can you tell us how these work from a consumer brand perspective and why they're so important? 

Stephen Grambling: A number of studies suggest both business and leisure customers pick loyalty programs primarily for the perceived points value. But this is then followed by personalized experience and partnerships, that's what the consumer values when they're picking a loyalty program. A.I has the opportunity to really differentiate beyond just points back or a coupon by leveraging, as I said, the unique data that they have across both that business travel and then leisure to drive again, tailored offers experiences. These loyalty programs importantly are essentially pools of funds across all the owners of hotels deployed by the brands. And so when they're investing in A.I, the same kind of thing will happen where they'll be spreading across all of their owners. At the same time, the brands can leverage partners such as credit card companies, in the past they've also done other travel partners, to subsidize these funds and drive even greater scale. And another thing is that they can also get some fees  from these loyalty programs that they charge back to these partners. And currently that can represent over 10% of the EBITDA, these companies, as we think about co-brand credit card fees alone. 

Ed Stanley: Brian, you've done an AlphaWise survey or two maybe, what of the high level survey findings shown you on travel particularly? 

Brian Nowak: We are already seeing travel leisure research migrating over to these new platforms where, you know, something around 20% of people we think are already researching leisure travel and using those tools to research travel. So to me, it's interesting, it is an encouraging early signal for the tech companies that you are seeing this user behavior move from the traditional search products over to the next generation A.I power tools. 

Ed Stanley: Then just to round things off. From a topics order of preference perspective, after all the work you've done, the winners and the more challenge names you think they come out of this piece of work. 

Stephen Grambling: So we think about this across both the scale of the system and then their investment already in technology and we see in the cross-section there, probably the best position would be folks who have effectively already spent on a connected room. So they have the tech ability and they also have the scale. Folks who are smaller scale are just not going to have quite as much data to work with, and they're not going to have the same system size and system funds that they can invest in the technology behind it. 

Ed Stanley: Stephen, Brian, that's been really insightful. Thank you for taking the time to talk. 

Ed Stanley: And thanks for listening. If you enjoy Thoughts on the Market, please be sure to rate and review us on the Apple Podcast app. It helps more people find the show.