GAIN Momentum - Lessons from Leaders in Hospitality, Travel, Food Service, & Technology

For our second On The Road episode, Adam went down to New York to attend ILC Cultivate (July 11-12, 2023). In between sessions on how next-generation technologies are impacting hotels, conference delegates were each asked, “What’s the number one way that hotels can deploy artificial intelligence and web3 tools right now?”

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The GAIN Momentum Podcast: focusing on timeless lessons to scale a business in hospitality, travel, and technology-centered around four key questions posed to all guests and hosted by Adam Mogelonsky and Jason Emanis. 
 
For more information about GAIN, head to: https://gainadvisors.com/ 
 
Adam Mogelonsky is a GAIN Advisor and partner at Hotel Mogel Consulting Ltd. (https://www.hotelmogel.com/), focusing on strategy advisory for hotel owners, hotel technology analysis, process innovation, marketing support and finding ways for hotels to profit from the wellness economy. 
 
Jason is the Chief Marketing Officer at GAIN and a GAIN Advisor specializing in growth through marketing for hospitality tech startups, scaleups and SMBs as well as a mentor for the MCEDC Hospitality Technology Accelerator. 
 
Listen to the GAIN Momentum Podcast: 
Apple Podcasts: https://podcasts.apple.com/us/podcast/gain-momentum/id1690033572?uo=4
Spotify: https://open.spotify.com/show/1jfIWt1D92EzgB32yX2fP4

What is GAIN Momentum - Lessons from Leaders in Hospitality, Travel, Food Service, & Technology?

Each episode of GAIN Momentum focuses on timeless lessons to help grow and scale a business in hospitality, travel, and technology. Whether you’re a veteran industry leader looking for some inspiration to guide the next phase of growth or an aspiring executive looking to fast-track the learning process, this podcast is here with key lessons centered around four questions we ask each guest.

​GAIN Momentum episode #8 - | On the Road: ILC Cultivate - Deploying AI Right Now
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Jason Emanis: Welcome to another special episode of the Gain Momentum Podcast on the road here at I L C Cultivate in New York City, July, 2023, where we're focusing on timeless lessons from global industry leaders about how to grow and scale a business and hospitality travel, food service, and technology.

Adam Mogelonsky: The focus of I L C C on. AI and Web three applications for hotels great to talk about and learn about in theory, but on the ground looks very different. Hotel technology architecture is complex, and these AI and Web three tools have to work with what's already there and what's already in use. So we're going around and asking delegates as at this conference, what's the best application right here, right now?

Audio: when I think about, um, AI and content for the hotel industry, there's lots of different ways it can be used. There's some obvious ones like operationally for hotels, um, from a revenue point of view and pricing. But for me, it's all about curating experiences, generating content and recommendations. So what's the content that matters to me most at the right point in my guest journey and how you're gonna get me to commit to a booking and then actually stay in a hotel?

question. I believe that chatbots are a next generation AI contributor to the guest experience. So being able to identify and read up on guest queries and personalizing their messages, and I. Being able to service request orders that come in, uh, directly from those bots.

And then running predictive analytics on the demographics and psychographics off of your guests are gonna really add the cherry on top to your guests and provide that top-notch guest experience. the, the answer to that question actually comes from what types of, um, technologies are you actually working with today?

Is it just a P M Ss and maybe a channel manager? Is it p m S and c r s? I think the point for hotel hoteliers should be that we should be trying to target around 15% of our total spending that we actually have should be on technology. 'cause we should be collecting the data points we should be thinking about.

How to actually kind of work with technology, bring down those costs of those types of interactions, because that's what AI is really, really good for. But I think the first aspect of what we have to, uh, think about is how can we make sure that we are actually measuring every single aspect of our operations?

How can we make sure that we we're actually kind of utilizing upselling tools, that we have the right pss in place, that we have the right. Um, booking engines in place that are actually going to deliver this kind of, this great data lake that we need to then actually look at, look at basically the entire 24 hours of a guest experience and then use AI on all of that information to actually create much better outcomes.

And I think that for me is going to really, really drive the AI revolution. That's going to be kind of from looking at. The experience is the totality of the experience and the totality of the guest experience and the brand experience, and then putting those things together. So I think it's, it's about creating as many of those point solutions I.

Plugging them into a system, making sure that you work with the right tech partner who can actually help you see, you know, what is the best kind of tech cocktail that I need to create my, um, for my property or for my, for my brand. And then it's actually about working together with consultancy in a great.

Team to actually deliver the types of AI that are going to actually kind of make all of those insights. Action. So one of the most important things that I've been hearing from owners recently, uh, in regards to revenue management, um, automation of revenue management and artificial intelligence is, uh, turning from looking at pro, uh, profitability in just hotels, uh, and using the data.

Um, and artificial intelligence to, uh, turning that data into profitability from a larger standpoint. Looking at, uh, you know, total guest profitability, uh, total hotel profitability from different, uh, sides of the business, and leveraging the AI and the data to look at, uh, again, profitability from a, from a larger, larger standpoint.

there. So we are exploring the uses of artificial intelligence AI for a number of different tasks within the context of our business, which is collecting and reporting and analyzing guest feedback for our hospitality operators. So we, our latest endeavor in this area has been using artificial intelligence to go through.

Large quantities of guest comments typed in open-ended guest comments and try to get the, the real insights out of it. Before ai, the way to do that was to just have to sit down and read through them and take notes and try to categorize them and put 'em in a spreadsheet and report 'em back to, to clients.

Or if you were a hotel operator yourself, you'd have to do it yourself. Now you can actually have AI like chat, G B T. Go through the comments and provide summaries for you. Find areas that might need to be prioritized in terms of up updates to your hotel, um, and just things like that. Things like, uh, housekeeping issues.

It might, it might detect patterns in the. Comments where, you know, th 3% of the comments mentioned some sort of housekeeping issue. 3% may be a big number or a small number depending on the property, but it doesn't, we don't need human beings to actually read through all the comments. Now, artificial intelligence can do this for us, and I think that this is just.

The first step in a lot of things that AI can do in our business. Uh, we'll go into more things about actually writing surveys and adapting surveys based, based on, uh, particular clients, uh, or particular guests of certain hotels based on how they are answering questions. But that's a little bit down the road.

For now, we think the lowest hanging fruit is, is processing text, processing large quantities of text, getting the insights out of them very quickly so that hotels can quickly react to them. I mean, sometimes now it, it may take 2, 3, 4 weeks to get through the previous months. All the comments, uh, that guests are leaving for a hotel, this can be done in a matter of seconds Now, And so if there is a housekeeping issue, for instance, it can be addressed the same day that we're, that we're running, running this algorithm, running the text through the algorithm instead of having people go through it, read it and take notes and then make recommendations and go for, so it's incredible.

It's incredible what it can do. So I would say that's the the first use case in our business. Okay. I think hoteliers are using AA technology to save time. And responding to guest requests, guest chat, and also for reviews. So, uh, at Inspire, we just launched Inspire One, which is allowing the AI technology to respond to guests through chat.

And then also, um, through guest reviews. Sentiment, respond to those reviews and then allowing the Hotelier to then check that information coming from the AI and then send that out directly. But I think, uh, currently it's the ability to save time and using that AI technology to respond to guests directly.

I'm very hopeful of the fact that analytics, right now, we've already looked at how large language models are being used for improving processes around marketing, reducing the lead time to pushing content out.

But I believe there is a huge opportunity around revenue management and how pricing itself is done right. Today, the way the revenue management tools are working, they have certain predefined inputs based on which the algorithms are churning out, and AI here can perform the task of. Mass personalization for a user, right?

Think about what, how pricing impact from a user perspective. There are two specific, uh, areas to look at. One are extraneous. What are the events that are happening, what's the competition selling at? And another is very specific to that specific user, which our traveler, where the traveler, does he like premium property?

Does he like luxury property? Can use, add a specific attribute as a default to his purchase behavior. And dynamically based on extraneous and the internal factors arrive at what sort of pricing is going to appeal to this particular customer. Right? And it's been used for in the, uh, consumer markets, which is basically your F M C G industry and retail industry for quite some time now, where it is called segment of one, right?

Where you create a certain proposition specifically for one particular traveler. And that, I believe is the time for hospitality industry to really change the way. How pricing is done, how revenue management is looked at. we are hearing a lot these days about Jet G P T and, and bots like that, and they're pretty amazing, but those really focus on what's called generative ai.

Uh, which is something a little different from what we do. And so that brings me to what I think the most important and impactful, uh, use of AI in the hotel industry today is conversational ai, which is what we do with Annette, the virtual hotel agent. We work with a company from Cambridge, England called Poly ai that's developed a new kind of conversational AI that understands the question from the guest.

Better than ever before, and implementations where we put this in 98% of the time, our bot understands what the guest is asking, and when you understand what the guest is asking, the answer, of course, you've already predetermined. So situation like this, with this type of powerful conversational AI can save thousands of dollars in labor and guests get the answer that they're looking for.

There's a recent Oracle study post covid that over 70% of people traveling would rather deal with some kind of an automated bot to get the answer they want, uh, rather than wait to speak to someone, um, in person about it. And of course, our, our bot will always transfer to someone if they really wanna speak to somebody.

But implement implemented correctly our technology and we call it a net. The virtual hotel agent can work wonders to help the prop property achieve, uh, an increase in net operating income. as I think about LLMs and kinda leveraging AI and leveraging all the different aspects of.

Intelligence that can help hoteliers. Um, the first thing that kind of comes, that does come to mind is recognizing it's a tool to enable, and that is how I would define the most practical application. It's not placing anything, but it's helping team members that are currently in place do their jobs better.

Whether that's, uh, marketing coordinator, figuring out. Who can I prospect to you to sell in group sales, whether it's kind of operations team members, instead of having to talk to every guest with every request using, uh, text and chat tools to engage with guests more seamlessly, whether it's business leaders being able to analyze across their organization, whether it's a hotel or portfolio, hotels, where are the biggest gaps?

Where are the opportunities? What are the insights that are gonna drive my overarching or holistic business forward? Serving those up so that they're really using it kind of top of mind versus having to bury through the data and find it on your own. So that's how I think it's gonna be applied across the industry.

And you can take each one of those three examples and blow them out across every department, every team. But the way I think about it, it's these insights that're gonna make, tells more successful, enable 'em to do their jobs better, enable 'em to be more fulfilled in their roles. Um, and that's how I see the future of AI coming to life in our business.

The top application of AI for the hospitality industry is being proactive with customers, answering their questions before they even ask them, and then helping your team provide a higher level of care by answering questions or proactively answering questions and needs before they even happen. So my biggest kind of near term that I see AI adding to the hospitality technology stack. Is to be able to bring the hospitality and the guest arrival profiles back to the interaction with the front office and the service staff, because unless you're staying at a multi-thousand dollar a night room hotel, it's all transactional. But that can be solved with ai.