Highgate Technology Ventures on the Agentic Hotel Stack
It's a consolidated brain, and it knows you as a customer, not only the property information, but knowing you, what you asked for, how you talked to them, what you got back, were your requests taken care of. Imagine the power of that information. That's the key.
Speaker 2:From Hotel Tech Report, it's Hotel Tech Insider, a show about the future of hotels and the technology that powers them. Today on the show, have KJ, from Highgate Technology Ventures. I'd argue that KJ has the single best seat in all of Hotel Technology. KJ spent fifteen years building Highgate's legendary revenue management practice, ultimately as their Chief Revenue Officer, before launching their technology investment arm about a decade ago. In this episode, KJ explains why every single category of hotel software is up for disruption, which vendors are sugarcoating, what AI actually means for hoteliers, and where the next big winners will get built.
Speaker 2:KJ, thanks so much for coming on the show today.
Speaker 1:Thanks, Jordan. Good to be with you, California boys.
Speaker 2:KJ, I have so many hotel companies that reach out to me and ask me, how should we be playing this? Do we hire like a head of AI? Do we like start building software in house? And most of the time I tell them you should do what Highgate is doing. Should have a separate technology investing arm so that these incentives don't get blurred.
Speaker 2:And you have this great portfolio of assets to test products on and scale and get a good preferential valuation. So since I tell everybody that they should be more like Highgate, I want you to tell everybody what Highgate is and how Highgate Technology Ventures plays into the broader management company thesis.
Speaker 1:No wonder we're getting all these leads coming from all over the place. No, I think it's interesting in terms of the way from Highgate's perspective. Highgate obviously started off as a real estate side, which is the Highgate Capital or investment side of the business. Then we have Highgate Hotels, which is the operating side of the business. And we started HTV, Hyatt Technology Ventures, the technology investment side of the business almost ten years back actually, pretty much a little over ten years ago.
Speaker 1:And actually the rationale at that time was we were clearly seeing even then by 2016, we'd seen a number of companies come through pitch stuff and then go on to become reasonably large in scale, right, even from the OTAs. And so we thought the two ways to do it is two beneficiaries. One is, can we see very good companies that are solving something very important and can drive tremendous value for the hotels, at the same time have a team and the ability and the scale to actually become large and commercially be successful and so on, then we can achieve two things at once, right? We can get the best technologies for the hotels. At the same time, we can achieve great outcomes on the investment.
Speaker 1:Ultimately, the investment TCs and the investment outcome is actually important as a separate thing for HDB. It's not linked categorically to drive more technology to the high yield hotels, but we actually have cross relationships there that they send us over leads and we send them good stuff that we do. And we almost before investing in any company, if it's in the hotel space, we would definitely want Highgate Hotels to diligence it live to see whether they would use the products. Today, the team is in good shape and they would continue forever. So that was probably the birth of HTV.
Speaker 1:But clearly, like you said, we are not investing off a balance sheet and we're not corporate VC for the sake of it. It is absolutely fundamentally a different set of business. HTV operates on its own, not a fund, but partner led investments overall.
Speaker 2:And do you raise in multiple funds or is it evergreen that's coming from the founders of Hyveate or how does the capital structure work at LP Base?
Speaker 1:So the beauty here with HDV or Hygitech Ventures is it's not a fund. So we're not incentivized to deploy capital and earn management fees on that or on big hits that we've made for using other people's money. It's all partner capital money. So all of us have to invest the capital in every single deal. And it's all opportunistic, right?
Speaker 1:So you could do typically, we normally could do maybe two, maybe three at most in a year. So you do two exclusively or it could be cases in 2021, 2022 where we did zero, which was actually pretty good. Or zero or one maybe. And it had to be highly important or so in our thesis, since it's partner led and not a fund, We have to be very prudent in ensuring that it is a success or at least it's not a failure too.
Speaker 2:How has the landscape of investments evolved since 2016 when you guys started? What kind of deals were you looking at then and excited about? And how has that investment profile shifted today?
Speaker 1:I think that's interesting. I think in 2016, when we started, first, there were a few people playing in hospitality and tech. And we've literally seen over the last ten years, we've seen more and more VC, more and more private equity, growth equity come into the space. I think this is the potential realization that travel is 10% of the world's GDP. But maybe at the same time, were a lot more deals and scalable assets in other industries.
Speaker 1:For some odd reason, I don't think it's an odd reason actually, it's because of the fragmentation of our industry. It's very difficult to see scalable assets unlike other industries, whether it be healthcare or finance or insurance. It's more scalable assets. So that's where you see more of that venture and growth equity PE money flowing into. And because of the lack of scale assets, probably this wasn't as attractive for people.
Speaker 1:But we've seen in the last ten years that changed dramatically. And I still remember how I've also seen the multiples change. Mean, when we were in '16, we were paying five, six times revenue for companies that were growing 50% to 100%. And then suddenly became ten, twelve times revenue before COVID and then right after the big phase there. And then now when you go over the AI world, now those multiples are starting to adjust again and it's a readjustment of like, it's no longer the rule of 40 for you to be getting good multiples, it's like the rule of 60, right, if you're performing.
Speaker 1:So we're seeing that change over a lot. But one thing I can say is I've dramatically seen a lot of good capital come into the space, even if people might not be happy about it. But you can clearly see where are some of the scale companies that you see today outside of Opera or I mean Oracle or Amadeus or Sabre or any of these players, you've seen a lot more new folks who were not big five, ten years ago, which is great.
Speaker 2:And as you think about where the opportunities are in the market, obviously multiples for traditional SaaS are compressing a little bit with SaaSpocalypse. What's your view on the state of the market today on SaaSpocalypse, everything that went down from that Citroen Research article in January that we all love? How do you view the market on a go forward basis? And how do you think about the market in terms of how you approach investments differently today than maybe had I asked you just a year ago?
Speaker 1:Yeah, I think we've all seen if you look at the market by itself, it swings way more up, like to the left or the right. You could see post 2020 market skyrocket and everything else. And then 2021, 2022 is disaster the other way around. And then it adjusted off that. But the market's right in a way, right?
Speaker 1:So the market's gonna be right in saying, based on what we see today, companies that are SaaS based that are just gonna be selling software tools to help users be more efficient. And people say per seat and they're focused on per seat and per user and all that stuff. It's fine. I mean, that's just the concept, right? That's the payment mechanism.
Speaker 1:But it's like the underlying thesis is software companies or software helping people be more efficient in their job. What AI has changed to say, no, want to take out the inefficiency, which is the humans. As crazy as it sounds, I'm gonna say it. The AI based companies are not saying, I need to make you be better. They're saying, I think I can do what you're doing better.
Speaker 1:But a lot of our tech companies, every one of our tech companies, including probably some of ours, are sugarcoating and saying, oh, no, no, no, no, you're in the driver's seat. We're helping you do better. We're just there to help you. Don't fall for that trap. That's clearly the first phase.
Speaker 1:But ultimately, we all know the capabilities of AI. And people say, yeah, it's not as good today. It's going to be that's true, but it's getting better every single day. Go back to when ChatGPT launched, what, twenty twenty three November? It's so different from what you see from then, right?
Speaker 1:Where we've got agents doing stuff for us, we've been people writing codes, all that's changing. So I think if you look at what's happening is at that point of time or the point of time, I think that within the SaaS companies, there are going to be huge winners and losers. The winners are going to be those same SaaS companies that adapt and move into an AI based structure where everything they do is AI. It's not just the products that they use, but including their whole operations and how they run it. And that's called AI native.
Speaker 1:AI native is just not a product. AI first is everything about what you do is done that way. And I think they're going to be successful because they're to have low cost structures. They're to have highly efficient products that are meant to reduce inefficiencies of human beings and perform those better. And so, thus, humans will be better.
Speaker 1:And in some cases, I can argue and say, yes, the humans will become the really good human, like the people can also elevate because they can become more strategic. The ones that want to do the same mundane work that somebody else is doing, they will fail. So the same way in the SaaS companies as the successful ones we've talked about. The failures are the ones that don't adapt, don't adopt that. And then the other thing is you see about AI first companies which are coming out of the woodworks.
Speaker 1:Like every day there are like five of them coming out like mushrooms. And say, what are they doing? They're just like, I'll connect your data. I'll give you all the information. They're just taking GPT or Claude or Open Source Model, put a wrapper in it and say, they're trying to make a fool out of like, oh, years or wow, this is so good.
Speaker 1:But what they don't have is they don't have the core foundational infrastructure of what some of these software companies have built. So in my opinion, if I classify it into three categories, is AI native first companies who haven't built integrations enough, haven't built the pipeline of flow of information. Yes, I know it's easier to build integrations today, there's still the complexity around people who won't give you that access easily. Yes, you can use robotic process automation, you can do all of that stuff. And then there's the other structure of SaaS companies which have great in-depth built this over the years.
Speaker 1:The ones that have that foundational stuff that actually build and move to an AI based approach first will win and they will have that moat.
Speaker 2:Are there any categories in particular that you think are easiest to disrupt? I've always kind of said, I feel and I know you may have some skin in the game on some of this, but I felt like the CRM space, it still feels like this fancy database with an email marketing wrapper like SendGrid on top of it. And it's just now it doesn't feel like it's evolved as much as it could in AI. I feel like that's one category that's pretty ripe for disruption. Are there any other areas where you feel like the legacy vendors haven't adopted AI enough that you feel like there's this opening to have a wedge for an AI native startup?
Speaker 1:Yeah, yeah. No, I think for one is I can start with the final with the other end, the financial side. Absolutely can't be disrupted because AI is very good at math. And you've given all the content information, you will see a lot of that coming in. And whether it's going to be horizontal players coming into hospitality and driving that financial side of reporting.
Speaker 1:And the financial side, mean, the reporting side is one part. I think that's totally disruptive. I think if you see the other side being a pure yeah, you would CRM absolutely. I mean, imagine sending monthly emails from a hotel anymore. It's no longer the case.
Speaker 1:AIs can be personalized knowing when to send, who to send, what to send, how to send, all of that stuff is the key. That's a whole different. And all CRM companies are doing the same shitty job today of like, oh, we give you the option to send once a month. And I'm sure if you build AI models around it to understand the business, then understand the guest profiles that you have, understand the guest experience, understand the scenario. It's going to do the planning, the content creation, the execution, the distribution, everything for you.
Speaker 1:I mean, absolutely that's a disruption place for the CRM perspective. I think we're seeing more and more of which I think is, do we need the CRS in the end, right? It was a question when we had a lot of the PMSs connecting the channel managers. Do we need the channel managers in the edge? Why do we need channel managers?
Speaker 1:Why can you do agent integrations or agentic write and read between one system and the other? Yes, people talk about MCP is one, not everybody will be on that, right? There'll be people who won't do that.
Speaker 2:Yeah, it's almost faster to have a direct integration from the PMS to the channels and then programmatically, booking.com updates a feature, just automatically do that versus rely on an intermediary to plan it into their roadmap.
Speaker 1:Correct, correct. RMS is purely by itself, absolutely disruptive. I mean, it should be. And they say that the CRS piece, what does the CRS do? It does rate management and then it pushes those rates.
Speaker 1:The pushing of the rate as a channel manager. The rate management, if it's doing intelligently, can be done by an RMS which moves into both running pricing as well as driving the distribution mix together. Why do you need two different systems for that? So then you eliminate one and then you have another one which is just a pipe for sending information to different sources, right? So that's that.
Speaker 1:You talked about, I think the PMS is going to be disrupted too. Because what is a PMS today? Why do we need to have a human being press a key to say, I check you in, Jordan Holinda. Why couldn't it be like, you've completed your formality, you've gone ahead, you've got an email or text message, hey, you're coming in tomorrow, this is you, we've got everything confirmed for you. Can you just clarify information, just a quick snapshot of your picture to confirm your identity?
Speaker 1:Yes, we have all your payment details on file, can we charge this for you if you want Just it can either charge for you or we can charge when you check out, but you just wanna verify something here. Verify you take care of that. You go to the hotel, everything is taken care of. Why then should I go to a PMS and have a human being check it in? It's a trigger right then, does the check-in for you, agentically is done.
Speaker 1:In fact, agentically the rumor side must be done. So then you're starting to mix the whole digital experience with agentic operations from when a guest has booked to when a guest has left or checked out?
Speaker 2:I think the PMS is going into all these different categories as kind of an implicit admission that they think that everything's up for disruption. And so I think what they're trying to do is basically provide as many of those agentic workflows on top of the database so that they're so important to their customers that if the PMS,
Speaker 1:the core
Speaker 2:database functionality becomes commoditized that they could say, hey, we increased your RevPAR by this through our revenue management system and we drove this many And people
Speaker 1:you know where I think an agentic first company will work here? Is run all the workflows and get a database and sell it for one fifth the cost. And then this industry is gonna be, it's gonna be good for hotels. So I mean, think about it. I think that's where an AI first company would do okay.
Speaker 2:Where do you see the commercial model of hotel software going? I mean, there's the token side, there's percentage of transaction volume, which obviously was the legacy model. Then there's the SaaS model that kind of sits in between. And it feels like pendulum swinging between those three models. Are there any other models that you think could work in this space?
Speaker 1:I think the best model is clearly the subscription based SaaS model structure, which a recurring revenue coming through everything. The difference is not the payment model. The key in SaaS is not it was easy to blame the model and say it's per user, so it's going get disrupted. I go back to the same thing. It's if you choose to try to improve the efficiency of the worker versus improving the efficiency of what the job needs to be done or executed, that's the key.
Speaker 1:So it's almost like AI based outcomes with SaaS pricing. For me is like as an investor, you know, you think about it and you say, hey, because I don't think people are ready no matter what they say. Can you share the value that is being created by AI between you and the software. I mean, you can pitch that. In my opinion, you're going get some success.
Speaker 1:And I think nothing wrong with transactional pricing for a while. You're right. But the industry always liked safety and security knowing that you are getting this no matter what, up or down. And so there was always a premium price to that. And just going back to payments, actually payments is a valuable business.
Speaker 1:I don't know where it came up saying it wasn't. After you take the difference between what is processed through you versus what's your net revenue, right? And then on top of that, yes, you have to obviously pay credit card providers, which is why they're talking about your 50%, whatever. But the difference with payments is, once you connect a pipe, it's the same thing as as more and more goes to that pipe, you're just gonna keep taking a toll on it. So the concept of the toll stuff is really, really good.
Speaker 1:Like who wouldn't take toll based pricing anywhere else? It's like one of the most attractive markets.
Speaker 2:As far as companies that you're excited about at scale today or you think are having really interesting strategies, one of the themes that I think is really interesting, still super early in terms of how it plays out, is this idea of having a data set and having a software. And so two examples that come to mind are Duetto buying Hot Stats is really interesting because now you have full P and L benchmarking data and then Actable with Profit Sword and Alice. And so it's like, oh, you could change your housekeeping schedule and now see how it impacts your housekeeping line in your cost per occupied room. Those kinds of solving a problem and then measuring it in the P and L kind of plays are really interesting. Are there any scaled companies that you've just seen a move where you're just like, okay, I don't know if this is gonna work.
Speaker 2:I don't know if you're gonna be the one to execute.
Speaker 1:But there again, Jordan, I don't think you actually need to buy the company. So you could buy between profit sold and the housekeeping or do it all in hot stats. Imagine if you did one core thing well, and then you were able to interact with the others around it, then the addressable market is far larger, right? So I think a classic case. I think two companies of ours, one really scale as Lighthouse, which has obviously brought all this the bridge shopping, the business intelligence.
Speaker 1:They did all that stuff for people. And now they're bringing it all together and also probably interacting with other potential providers out there. We don't need to buy everything, but then they become this whole commercial platform, AIB's commercial platform that is there, that's available and obviously the launch of Earnest that they're there, which is actually saying, I can do all this for you to the user. So they're getting into that AI based stuff. That's scale in the front way.
Speaker 1:Another company not scale of ours Logic on the other side is RMS, but it's actually moving the other way and say, hey, we'll take all the data from whether it's from Amadeus, SDR, from marketing, from CRM, all the stuff that's there, sales, all of it together, connect it all together and say, hey, we can solve the commercial structure with you because we can connect all the stuff easily and bring it to you. And then we have non ROH is another classic example financial side of it to start doing the group level automation, move from group level automation to actually handling the payments for groups saying, hey, we're automating all this for you. These are classic work stuff done. And then moving from there to actually saying, let's look at the entire ledger, the financial side and saying, are you posting correctly? Are you collecting correctly?
Speaker 1:Are you doing all of that stuff? So making sure all of that stuff is done, including the point of handling AP and AR later on if we need to, that point in time. So it becomes a whole financial structural layer that's there. I'll give you a classic example today. Today, there are companies that have mushroomed across the world, across the country, which says, we will reconcile how much you have got paid by OTAs or others and what you should have got paid.
Speaker 1:What you should have got and what you got. And if there's a difference, we'll go collect that from you. And then we will share in that. But do you know why that happens in the first place? The reason why it happens is because you were supposed to check-in today and you don't check-in today and you check-in tomorrow.
Speaker 1:Now, the hotel for some reason, it's a prepaid reservation. European Expedia are booking. They post it from tomorrow onwards and they forget tonight's rate. And it sits there and somebody does a reconciliation later. The key is posting that revenue then.
Speaker 1:And now all of that is possible here with AI. So you're handling the entire structure here to make it more efficient while collecting the right revenue. So that's why I was talking about like the first one I was saying commercial. We feel that commercial agentic operations or commercial structure that's going to move in a way that can handle we're going to see a lot more coming together, revenue, sales, marketing, all of that stuff. In some cases, it doesn't have to be together as a one company, but it could be working together very, very well to get that infrastructure done.
Speaker 1:And then we have the financial infrastructure side, which is ROE, which is moving totally into saying, hey, in financial and payments, we can handle it. And obviously, Muse is doing its payments and that stuff. But this could handle it across any different platform. And it's just not limited to that single structure. It's not just payment, but it's the handle of financial infrastructure for you, which including agentic execution layers, right, that's there.
Speaker 1:And then I told you about that's one side. I think for the marketing side, we're definitely going to see that's 100% disrupted. I'm still surprised that we haven't seen any fast level launch of any major AI based stuff on the marketing front. I'm yet to see something there, which could be really good. And then we have Insider is actually a company that we have looked at very clearly.
Speaker 1:It's owning the entire operational layer from booking to checkout. And it has a brain. That brain is where all the information of the property sits. All the information of the guests comes in, whether they text, they WhatsApp, whether they call by AI voice, whether they do all of those are just communication points of view. They all come in a single brain and then it guides the customer from the time of booking to check-in to insisting and say, I have a problem with my towels.
Speaker 1:It sends it to task management system. I have an issue on my light bulb, this center of engineering. It controls that entire stuff for the guests ready to check out. Hey, here it is, link pay, you're out. Then you say, you know the guest has had a great experience.
Speaker 1:You post that review. You say, hey, post this review for me. And it's controlling that experience. So that's another area. Yeah, yeah, yeah, yeah.
Speaker 1:They've moved. And so they can now it was based out of Sweden. We just got in earlier. But they were in the TV business before when they did apps. So now they're got Inspire One.
Speaker 1:And people talk about the concierge. But the concierge is just the outer self AI concierge. But it's the brain that controls everything else today. And people are saying, oh, I'll do AI voice, then I'll do guest messaging. But then what's the point of two brains?
Speaker 1:One brain for guest messaging, AI voice. And that doesn't make sense. You call in, you're going to get a different thing from the AI voice and then you text it, you're going to get it from the different messaging. So this one says it's a consolidated brain and it knows you as a customer, not only the property information but knowing you, what you asked for, how you talk to them, what you got back, were your requests taken care of. Imagine the power of that information.
Speaker 1:That's the key. So we're seeing all this stuff. So we're seeing literally across the space that there is movement happening across our companies. Hotel Trader again is another company I think you know of this. They're in the B2B distribution space.
Speaker 1:Now they're perfect for being optimized distribution and saying, hey, this is how you're going to drive optimized level of distribution to your thing at the highest profitable basis because of when you need it or when you don't need it the most. So at a high level outside the portfolio companies, we are super interested across and we see dislocation happening all across. It's almost like a moving board that's happening. And it's the race from everybody running together. And you're going to see a lot of AI first companies coming in, coming very quickly to the market.
Speaker 1:Some raising lots of capital, some just raising a little bit and building fast. And then we're to see movements happening of existing companies moving from one space to the other, not just through acquisitions, but because innovation. And then we're going to see some level of consolidation happening. So I think there's going be a lot of consolidation happening in the industry pretty quickly overall.
Speaker 2:And how do you think about the nature of that? It's more like consolidation? PMS starts building all these other features like we're talking about or is it M and A or all of the above?
Speaker 1:I think PMS is definitely a couple of the PMS are actually going to build a lot of these features. The thing is they're spread two things because I think it's impossible to say I can do all of the stuff on operations and get it packed down. I mean, PMSS today has not even solved room assignment for God's sake. It's the number one thing. You solve room assignment, you've taken care of a huge amount of time spent on figuring out which room to give to who, where.
Speaker 1:That's the reason why check-in takes so long is because they're hunting for that very room. So literally, they don't know which room to give you. But imagine all of that taking channels, but it's chasing the money, right? They say, easy money. I can just chase distribution and put a channel stuff and connect using that.
Speaker 1:That's easy stuff. So and I know, like as an investor, I was the same thing, I'd say, where are we gonna make the fastest buck, the biggest one sooner than later? And each of those are too big to be ignored till but I think you're gonna start seeing something very good in different areas. You're gonna have excellent operating platforms. You're gonna have excellent distribution platforms, excellent marketing platforms.
Speaker 1:So I think you're going to see consolidation of all which will be fine in its ease of use. Have one platform, I can just choose it. But I think you're going to also see excellent choice of best in breeds. Not the way we had before of 30 different systems or 20 different systems, but probably four or five. So that's what I think is going to happen.
Speaker 1:And it could also happen, I think the best of breeds through M and A could be something super interesting, which could create a massive winner on scale too.
Speaker 2:There was a lot of hardware excitement, I feel like in the last few years, especially with AI. Some people say hardware is more defensible. I've seen motion sensing cameras in the ceilings of lobbies that have data platforms. I know you guys invested in a smoke detector company that charges when there's smoke. Are there any interesting hardware plays that you see in hotels right now?
Speaker 2:And have any been particularly successful that you've seen?
Speaker 1:Yeah, actually there was one because I can't remember the name when I saw it in High-tech was actually interesting. First of all, actually with this one, you're right. REST is a smoke sensing device. It's a simple thing. There is no way any housekeeper, security manager, anybody can detect smoking happening in hotel.
Speaker 1:Putting a $500 placard in a room type saying you will be charged this much for smoking and not doing anything about it, it doesn't make sense. This one works for you 20 fourseven. It's linked there twenty four hours a day, literally there. And they use data science to figure out exactly what's happened and trigger an event. And data science is a form of AI anyway.
Speaker 1:So that's working really, really well. So automate. This company is actually pretty cool. I met the guy earlier and they were doing a lot of image and camera stuff that they were doing for certain governments and saying for security reasons and other things they said that they would turn all the cameras in a hotel whether it be in the corridor, at the pool area, on the lobby, all of that stuff. They would take that and bring that data into a localized server because it's too expensive to take it and put it into the cloud.
Speaker 1:And then from that localized server, they would run AI queries or AI based pattern recognition. And they would figure out like, if for example, a tray was left next to Room 914 and the first time the housekeeper just passes by. But this tray was left, the camera detects it, then you send a messaging back to somebody saying next to 9114 tray left. It goes into the FMB system or whoever's or pick this tray. That messaging is sent out and that gets picked up.
Speaker 1:Then it doesn't sit there all day long. Towel sitting where it shouldn't be sitting, picks it up using the messaging sense. So it converts now real life stuff that's happening into a task that needs to be executed by somebody human, but it's all task managed through AI or pattern recognition. That was actually interesting. Very, very simple use case.
Speaker 2:And is that through their own proprietary cameras? Do you remember or is it?
Speaker 1:No. No. No. It's basically taking use of an asset that's on prem and reutilizing or utilizing it using which is actually brilliant.
Speaker 2:Was thinking about those. I remember I mean, it's still lot of hotels have these little buttons that you put on your room service to get it taken away. This kind of technology could do away with that category. Exactly. It replaces all those microchips that
Speaker 1:you have to put everywhere, all those chips that you have to put on the bloody tray. You don't need any of that stuff and use your own camera stuff too. And then it controls from security point of view, controls everything.
Speaker 2:Thanks so much for coming on, KJ. This conversation has been awesome, and I know our audience is gonna love it.
Speaker 1:Thank you, Jordan. Loved it. It was always great to talk to you and hopefully see you in LA or New York next time.
Speaker 2:That's all for today's episode. Thanks for listening to Hotel Tech Insider produced by hoteltechreport.com. Our goal with this podcast is to show you how the best in the business are leveraging technology to grow their properties and outperform the concept by using innovative digital tools and strategies. I encourage all of our listeners to go try at least one of these strategies or tools that you learned from today's episode. Successful digital transformation is all about consistent small experiments over a long period of time, so don't wait until tomorrow to try something new.
Speaker 1:Do you
Speaker 2:know a hotelier who would be great to feature on this show, or do you think that your story would bring a lot of value to our audience? Reach out to me directly on LinkedIn by searching for Jordan Hollander. For more episodes like this, follow Hotel Tech Insider on all major streaming platforms like Spotify and Apple Music.
