Meet the five new Mews products transforming how hotels work

We can see that up to a third of messages are never responded to. And even when a response is sent from the hotel, it usually takes eight hours or more to send that response. And that's not because these are bad hoteliers, these are bad people. That's because these messages are coming from a lot of different directions. Maybe there was an email. Maybe they sent a web message. Maybe they called earlier. It's unclear. Did someone respond? Maybe they did. Something comes up, right? Hi, everyone. Welcome back to another Met Talks hospitality. And this is a special episode. I don't do say that all the time, but this really is a special episode because we're doing something different this time. I've brought together three of our product leaders to walk you through everything that we're launching at news, new products, new features, things we've been working on for a very long time. And I think you're going to genuinely like this change that we're bringing to you the workflows of your teams today. We're going to cover a lot of ground. We're going to talk about muse automations, guest messaging, accounts receivable, news business intelligence, and muse revenue management. So a bunch of new products. And to kick that off is Joel. Joel is joining us as the VP product and engineering off the front of house. So really taking care of the guest experience. And we're going to talk about muse automations and guest messaging specifically with Joel. Let's kick off with muse automations. What is this product and what's the problem that you're looking to solve with this? Sure. So I think muse, what we've done over the last decade plus is trying to figure out not just how to digitize hood, hell, workflows, but how to make them go away, how to automate them. And a lot of that work has resulted in us actually building those automations where we thought they applied to everyone. There's lots of business logic in many places. And the more of that we did, the more we realized we should just build the tool to let hoteliers actually build the automations themselves for all the custom bits that your operation has that are different than whatever your other hotel has. So this will basically be a GUI graphic user interface system where a hotelier can go in and actually build custom things. Say that when a guest who is platinum rated comes in, we do ABC and D every time, regardless of who's on shift, regardless of whether someone remembered the system does it for me. Is it like if this then that's tool or is it different in that respect? Different in that perspective. It's really is going to be built based off of the actual triggers, the things that happen that matter in a hotel when someone checks in, when someone goes to the front dust, when someone gets a key, when someone checks out, when someone makes a request of housekeeping. It's basically triggered off of, it can be triggered off of any of the events that would happen inside the PMS, which thankfully is almost all the events, all the ones that really matter. Right. How do I build a workflow? Like what would that look like? Is it difficult or can anyone do it? Super difficult. We don't expect anyone to be able to use this tool. No, I think there's this three ways to think about this. There's the, what I'll call the Power User, which is like, I want to build a million custom flows myself, just give me the tools, I'll build it myself. That will certainly be possible, where you can view drag and drop the giant list of things you can do, tie them together, build them into a giant workflow. And we expect that'll be a minority of users. There's the classic, give me the 10 basic templates, right? Like, hey, I want the loyalty upgrade flow. I want the early check-in flow. I want the late checkout flow. So we'll have some templates that are pre-built for folks who just want to say, "This is the most the oral one. Click." Right. Let me edit two things. And then we'll also have an agentic flow where you can just tell it what you want. Right. You can say, "Hey, here's what I want to happen. Do what you need to do, but please make this happen." Right. And the agent will actually build the flow for you. Amazing. It will then obviously show you what the flow is. And so you can look through, verify it yourself, make any edits you want to make, and then hit go. So can you give maybe like one or two actual use cases, like actual automation flows in a hotel that will make a difference? Yeah, absolutely. I think my favorite is what we call soft loyalty. Right. So obviously if you have a hard loyalty program, meaning you know, you have a three star, five star, seven star guest. You can trigger a vent space thing and make sure you're this guest always gets a cocktail when they arrive, make sure this guest always gets a view, a room with a view. But the more interesting stuff to us, I think is the soft loyalty to say, "Hey, if you have a guest who stayed with us more than five times, in the last two years, give them an upgraded room, and then send them a message, let them know that we're thankful for their return business, and that we upgraded them." Right. So that they know we did a special thing for them. I think it's those types of flows that are super interesting to me. And then similar, you know, you could expand on that in many ways to say like, "Hey, if a guest requests an extra pillow, always follow up with them 15 minutes later to make sure it arrived." Right. Please send like, "Create a ticket for housekeeping," and then always send a follow-up message. And if they say they have, it hasn't arrived, then escalate to the front desk, right. Flow like that to ensure consistency in how your hotel operates are the ones that are top of mind for us. And then there's certainly one-off flows where you can have strange things like, "Hey, if more than five tickets are filed with maintenance for broken ACs, trigger a message to the manager. Let me know that's happening," right. Simple things like that can also be useful. Basically, to just ensure that things that should always be happening always do happen versus that being based on the person who's supposed to do them remembering in the moment. That's so good. I was this morning with a hotelier and this room's division manager said, "I would love for me to use a report with all the VIP rifles so that I can manually check them." And I said, "No, no, no, you're asking for the wrong thing, and I can show you, I'm not allowed to, but I did show her what we built." And she said, "Oh, I don't need the report. I just need that product because that solves my thing because for these VIPs, they're putting these nice welcome gifts in the room." I said, "Yeah, we will create this task for your automatically." So that room surface knows when to deliver those things to the room. That's exactly correct. You don't want a digital checklist. You just want it to be done. Yeah, exactly. Talk to me about guest messaging. Yeah. So I've mentioned it a few times in our conversations that we've had about automations, but messaging, two-way messaging, is critical if you want to actually engage with your guests. And there's lots of great ways to do that, but we've decided that it's really important to have that built into the system, both so that you have one unified place where you can view all the messages happening between you and your guests, whether that's the RSI mess, through WhatsApp, through booking, etc., all the normal channels that your guests communicate through, but also because that two-way communication is critical to your staff's engagement wherever the guest is. And today, most guests live on mobile devices. I don't know if you've heard of those, but most people have cell phones, and that's generally how they communicate. They want that to, in the moment, communication, so we want to meet them where they are. So we're building a unified communications, guest messaging hub somewhere where you can view all these messages compressed into one stream. So if you met where to send me an SMS while you were on a trip somewhere, and then later you switched to WhatsApp, and then later you switched to our web messaging platform, and after that you switched to booking. I still know that Matt is Matt based on certain identifiers. I will combine all those messages from Matt from all those different channels into a single chat thread that your staff can then view in a message center to say, "These are all the messages we've gotten from Matt." And when you respond, you can choose, "Do you want to respond to Matt?" Now WhatsApp, you want to respond through SMS. Obviously, we will default to responding in whatever the latest version Matt is liking to use. But once we can do that two-way communication, not only can we simplify coordination between new and the guests, we can actually make sure you respond to the guests. We have messaging right now in the news, and we can see that up to a third of messages are never responded to. Maybe there was an email, maybe they sent a web message, maybe they called earlier. It's unclear. Did someone respond? Maybe they did. So unifying all those is critical to know, this is the one place we go to look to see if we have messages. And more importantly, somewhere to our automation discussion. Now you don't have to answer because now when every message comes through a unified place, we can make sure that we have intelligence a place to always answer, right? 80% of the time your guests are asking for something that the system already knows the answer to. Like, "Hey, is breakfast included in my reservation? Hey, can I have an extra pillow?" Like, "Hey, do you have parking? What time does the pool open?" Right? "Can I is diving allowed? Are my kids okay to be alone in the dining area?" Right? Those are the types of answers we can take away from the staff so the staff can do the million other jobs they have to do and respond quickly to the guests because when that guest messages your hotel, they expect an answer instantly. Right? They expect that there's someone they're waiting for their message to come through and instantly responding. We can do that for you. And what that also allows us to do is build in all those automations we just talked about. Right? Because now that the guest is giving us input and we can give the guest output back, we can go back and forth. Right? So if that guest can say, "Hey, is breakfast included?" We can say, "No, it's not. Would you like it?" Right? If that guest says, "Hey, my flight landed super early, can I get an upgraded room?" We can check and say, "Hey, you're a loyalty member?" Sure, we were going to upgrade you anyway, but yes, we can accommodate for you. Right. And we can let that guess. now. And then as I said earlier with the automations, even if you were doing stuff in the background, when you do a net positive thing, you want to let that guess know that you did it, right? So that they know that you're doing extra work on their behalf. So if I text you in my Uber on my way to the hotel, I say, can I have, please, I love extra pillows. I need extra pillows on my bed. Our agent can pick up that the guest asks for extra pillows. It can create a task for housekeeping to give those extra pillows to the guest when they clean the room. When the guest arrives and the cleaning is done, the room is ready. The system can then text that guest back to say, your pillows are in the room. Thank you very much. Welcome, right? That closed loop can all happen automatically so that you don't have to remember that, oh, right, Matt, wanted the upgrade with the extra pillow. Let me do that for you now while you're giving me your passport. When I guess arrives, you can just say, welcome, Matt, your extra pillars are already in your room. You're on the fifth floor because we know you like a view. Thank you. Amazing. So what I'm hearing is that this is a messaging service that's embedded into the platform that the employees of the hotel live in, right? So they don't have to have a second tab open. Everything happens in the main platform. We're plugging in more channels. Like right now we have just email, but we're adding in like it sounds like WhatsApp and messaging, I heard you say OTA channel. Right now we will have SMS, we'll have WhatsApp, we'll have booking, we'll have our web browser, we'll very shortly have Expedia email and then we'll keep expanding and adding more and more channels, Airbnb, Instagram, Facebook Messenger, all the basically we want to meet your guests where they are. However, they want to communicate with you. We should let them do that and then unify it on the other side. I think the most interesting thing to me is our ability to tie in our AI agents into these messaging flows because when a guest asks for something that shouldn't always mean a human or your team has to do something. And I think that's the worry that hotels have. They're so worried like, oh, you're plugging in more channels. So I'm getting more volume to my team who I want to focus on the guest in house. But actually what you're saying is, yeah, there's more volume, but the AI agent can handle the majority of all of that. And when it gets stuck, that's when we can very quickly ask like in the same user interface that the employees in to make sure that those messages don't get missed, right? Yeah, that's exactly correct. Like we've made it very easy for the employees to jump in and swap the AI on or off for any given conversation. So humans can jump in, pick up a piece of a conversation and then hand it back off to their AI co-worker to say, all right, I answered that hard part. You keep going now like finish what you had to do. And again, as I said, the key part between automation and messaging is to put them together, right? To have that messaging agent understand this customer is asking me to do this. But like it's even the thread, right? So when you confirm to the customer saying, you know, through the automation, we just say, hey, by the way, we upgraded you nicely and you send a message. But then they can respond to that message is not a no reply number. They can instantly start to communicate backwards and forwards. And that is communication that would normally happen under reception desk. We've just taken care of it. And I think that's the really exciting bit how all of these ecosystem products work together really well. Really well. Absolutely. And as we have that communication, we also deepen our knowledge of that customer. And within the Muse profile, we also improve our smart tips and smart suggestions, right? Based on what that customer is asked for in the past. So this all really ties together into the Muse ecosystem to provide a recurring faster, better experience for the guests, which should also be a faster, better experience for you and your employees as I'll tell you. Great. Joel, thank you so much for sharing this. Absolutely. So that was Joel. Joel focuses on the front of house. So what happens be, you know, at the reception desk and all of the guest flows. As we continue this episode, we'll talk about the two products that sit right at the heart of how hotels make revenue decisions, Muse business intelligence and the Muse RMS. I've got Connor Winders, Connor Winders, Winders. I never know if Winders, sorry, Irish, VP of product engineering at Muse covering the back office. So what happens behind that door where people hide in the back and make all of these big business decisions? Let's kickstart with Muse BI and tell me because we used to have a product called Muse Analytics. And today we've launched a new product, which is Muse BI. And how do those two compare? And this is a real departure from what we used to have. Yeah. So we've had Muse Analytics for a while. And I think it's done a good job, a possible job for a lot of our customers. But more and more, we really believed we could do a lot better. And when we really spoke to our customers and really tried to understand how they were using Muse Analytics and some of the difficulties they were running into, there was a lot of signals there that, you know, the product that we that we were offering wasn't doing what we believe were capable of doing. And so some of the things that we would see and some of the problems that we would hear is Muse Analytics could be slower times, very, very hard to customize to get, you know, the actual data that you wanted to see at a point in time. The data itself is not always up to date. It wouldn't necessarily always be the freshest data that you were looking at. And so when you combine those sorts of things, what we would hear and what we would observe with customers is they start to lose faith in the numbers. And when you've got a data product and you question the numbers, you know, you've got that, that's a real, real challenge for our customers. And so, you know, there was a lot of signals there that we could that we could be doing better, even even beyond that, you know, Muse Analytics struggled in a multi property sort of setup. And a lot of our customers are managing multiple, multiple properties at once. The other thing that we saw a lot of was customers actually going into Muse Analytics exporting data into Excel or Google Sheets or something else, manipulating it in there, maybe adding a couple of other data sources, adding some macros and formies and things like that to try and find the answers that they were that they were looking for. And ultimately spending hours just managing the data as opposed to acting on the data and getting insights to act on the data. And so Muse BI has really been built from the ground up to like avoid those problems and provide a much, much better slick or richer experience from the start. So some of those things that I talked about like the data of freshness and Muse Analytics and the speed, like Muse BI is lightning fast in terms of how it renders the dashboards, how it renders the reports for you. The data that you get in there is that most going to be two hours old. We have it refreshing constantly. Every two hours new fresh data is pumped in there. So you're always able to trust that you're looking at the most up to date and relevant data for your product. It's also multi property by default. So out of the box, it's going to be able to handle multiple properties as opposed to trying to stitch together different views like what would happen in Muse Analytics. We've also added like some really really nice things in there that you couldn't do in Analytics. So you can upload your own data with giving the ability to add your own budgets, forecasts, add your own historical data and things like that. And I'm sure we'll get into it too, but actually now starting to connect to third-party sources. So Muse BI is amazing at showing you the data that lives inside the Muse ecosystem, but also the ability to start to pull other data in there as well. So we can avoid people needing to actually download anything to it to a spreadsheet. So ultimately, they're very, very different products. Muse BI is built on a whole new foundation, read to solve a lot of the pain that we saw our customers were having with Muse Analytics. And you started talking about the data and in the old product, the data wasn't always trustworthy, whereas now we build it on a new infrastructure. But can you maybe talk through the challenges of rebuilding our data from the ground up so that it's trustworthy today? Yeah, I think like ultimately in building a data product, like I said, like one of the most important, actually the most important thing is like the definition of the data needs to be the same across the platform. You can't have one interpretation in one screen of what 80 or is and the different interpretation in a different screen. And that is true, like across all of the metrics that are important in a data product. And what we've tried to do with Muse BI is it is built for hospitality from day one. So we've spent a lot of time, a lot of investment in really defining the semantics and what these different metrics mean in a hospitality world. So you'll see there's a common definition of occupancy, rev power, 80 or pick up, pacing, all of these things that are very, very specific to hospitality are defined in great detail under the hood in Muse BI. So you don't have people trying to come up with their own interpretation of their own formative from one report to the next or one screen to the next. The system itself understands these things out of the box. And that's probably being the biggest investment that we've made over the last couple of years. A lot, a lot of work has gone into building out those semantics so that we can produce data that makes sense. And that is consistent across across the whole product. Love that. And basically you can build your own dashboards from the ground up. Why have we decided to make a few predefined dashboards for us at ease? Yeah, so out of the box, you're going to get, I think it's like 18 dashboards at the moment and we're continuing to add to that. So there's a lot of dashboards in there that answer questions that our customers want to answer whether it's every day or every week, but they want to answer them quickly. They want within a couple of clicks to get an answer in 10 seconds and 15 seconds and so on and so forth. So again, the things that I was talking about like your pacing dashboard, your pick up dashboards, things like that that we know our customers want to quickly readily available access to. And rather than having our customers needing to define those and build those themselves, we decided to just give them out of the box. And it's all about removing friction from the whole system so that this is a quick and easy to use product. Data products can get very complex, very, very quickly. We want to take as much of that complexity out as we can for the things that we know our customers want. And then at the same time, we also know that some of our customers, some of our power users, they really want to go much, much deeper. And so we have also built the ability to build your own dashboards. But in even doing that, we've tried to make that as simple as we possibly can. So it is literally like a drag and drop interface where you can start to pull in the metric. that you're interested in, configure the metrics that you're interested in, and create the sorts of deep inside for dashboards that are very specific to your business. So, trying to cater for the best of both worlds, that's very, very quick answer the question that you always want answered, and then that kind of deep work you can build your own dashboards for as well. And then I saw we added this AI summary at the top of the report. What does what does that do? Yeah, the AI summary is something that I really love in the product because it's not something we start it out with doing. We actually started out trying to solve a different problem. And I think a lot of like what makes a great product is you start out with something, and in a way you fail because you realize what you're trying to do is not solving the problem the customer actually has, and you pivot and you iterate and ultimately land on a solution that really does solve a problem for customers. And that's kind of what happened with this AI summary where we started out down one direction of what we thought would be valuable to our customers. Well, what do we think was valuable? And I got actually a little bit of an example. So, really what we thought our customers would want as technology people was the ability to talk to your data, to actually ask questions of your data and have some sort of AI go off, figure out the answer to those questions, and push it back to. And as we showed this technology to our customers, as a tech demo, they loved it that this is really, really cool. But in terms of the practicalities, the same feedback came over and over. I wouldn't use that. I need to be able to get my data and get answers out of glance. And if I want to do deeper work, then I'm going to sit down. I'm going to do deeper work. And so from a technology perspective, what we saw was we could get good answers, but the friction involved in talking to the data wasn't solving the problem that our customers actually had. And so where we landed on then was using the same technology, but to produce these executive summaries. So now what happens is when you open MUSEBI, the first thing that you're going to see is a small summary that really highlights the things that you need to know about your data. So you don't need to ask the question. We asked the question first. We rendered that right away. We really, in doing some of these AI summary type products, it's a delicate balance and it's a really interesting design challenge to solve as well. So on the one hand, you can summarize everything. You can summarize 20 curated dashboards, 50 custom dashboards and have this massive big wall of text. And that doesn't solve a problem. Customers become immune to that. They just skip past us. And it doesn't actually highlight anything to them. On the other hand, you can go way too summarized and only show like really small bits of information that don't add value either. So we spent a lot of time working with customers trying to find what is the balance between you need to have a level of comfort that your business is working as you expect it to, but you also need to be signed posted to the things to the anomalies in the data where you need to dig deeper. And so you'll see what these AI summaries when you open them up. They'll give you that reassurance in a couple of lines, but then they'll highlight the things that hey, when we look at your data, we think something interesting is happening here and you should dive in and look a little bit deeper. So we're not necessarily trying to replace all the analysis that goes into it, but do more of that sign posting to give you the reassurance, but also give you the knowledge towards where we think there's something interesting to look at. That's pretty great. This week I went for a cross exposure at one of our customers. Then they are a hotel chain never like a 12 different hotels. And I sat around a table with like the GM and the front office manager and their systems director and normally I walk away from a day like that with like a huge list of feature requests. And often it's about reporting. They want the manager reports to be slightly different decalculated or they want reports to be exported in PDF file or they want a VIP report that's slightly different. It was so nice to be able to just open up the eye and just say, yeah, when that's built it together. And I'll show you how to do this yourself. And my list was significantly shorter, but even like the you know, the GM saying, I must have it in PDF because actually next cell file won't pass my order. I'm like, great, it's there. It's it made my life really easy in that conversation with our telly and at some point I even said actually, you know, with what we just learned from Joel, with the automation hub, I don't think you need a report because the automation app can ultimate because they were looking for a VIP report. It's like you can build it in BI where it can tell you the VIPs and kind of what amenities they should get. But actually we should remove that report entirely by automating it through the automation hub. So it's the interplay of all these different that become really powerful. Yeah, I think what's really interesting and you'll see more and more in the coming months and the coming quarters as we release products like the automation hub and as we continue to improve what BI is capable of doing is as we ask the question of our customers, why do you need that report? Why do you need that data? It's what are you going to do with it next? And I think we can move further and further into helping our customers by doing that or automating more and more as opposed to we can produce the report. But if you're doing something with that report, we want to know what you're doing with that report because I think we can help you with that as well. And the technology is moving so fast and as you say, things like the news automation hub, it's really going to be mind-blowing what we're capable of doing and how we're able to help our customers by pulling these systems together. So speaking of putting systems together, the person that probably uses BI the most will be the revenue manager because they're trying to figure out what's happening in the business. There's a new product that we're also launching, which is called the Muse RMS or the Muse Revenue Management System. Didn't we already buy a revenue management system? What's different with this one? Yeah, we did. So last year we spoke a lot about Adamise, which is a product we're incredibly proud of and a product that actually does amazing things for our customers, it does amazing things from use as well. More and more as we see the results our customers get with Adamise. I mean, there's very verifiable data on 80 or improvements, rev power improvements and occupancy improvements and things like that. It became clear to us that the potential in this product is so much greater when it is part of the Muse ecosystem. And if you looked at yesterday, it's part of the Muse ecosystem in a way in that it looks and it feels a bit like Muse and you can log into it from inside a Muse, but ultimately you're taking to what is a different experience and a different tab. And in there you have things that kind of look familiar like you're setting some pricing there, you're setting some rules there, you're setting some pricing and you're pricing great in Muse and some rules there as well. And ultimately there is friction or there was friction between those two things. So what we've been doing a lot, investing a lot in over the last month or the last month, the last year, obviously we've been improving the engine that powers all of the pricing and Adamise as well. Our machine learning in there is continued to get better and better and that's driving really, really great results. We've also looked at where can we take friction, effort for our actual users and every friction point that existed was one that was up for challenge. So is it enough that you can click a link and Muse and get taken into Adamise? Sure, that's good, but no, that's not enough. You need to be able to operate the Adamise infrastructure inside of Muse. Is it enough that it looks a bit like Muse? No, that's not enough. It needs to be the same UI components, the same patterns, the same navigation. Anything that we were doing that was breaking the experience or breaking the mental load became something that we got very relentless around. Let's remove that. To the point that the entirety of the Adamise capabilities now lives inside of Muse, not bolted on, not integrated to Muse, but literally inside of Muse, sharing the same data model. So there's no question of when I go from this tab to that tab, will the integration have synced on time? Will the data have made it over on time? Should I question that? Should I not question that? It is the same data model. It is the same data layer. Everything that you had to think about before and whether these things were in sync is gone. There's one pricing experience in there. You're able to configure your Adamise, configure the the government and the guardrails around Adamise, but it all runs from one place. As I say, that's something that has been getting improved over and over throughout the year, but now the whole experience lives in one place. I think that unlocks a whole new way of working where you're able to actually look at and managing all of my revenue in one place. I'm also able to dive deep into the revenue metrics deep into my business inside of Muse BI and I'm able to see everything that's happening from one place. You can close that kind of optimization loop, make it much, much tighter inside of inside of one product. It's something that we're super excited about. I went in last weekend and I spent my Sunday, I had a little different life than most people. I spent my day learning the system because I don't really like to read the manual. I just like to click around and figure out how it works, but I could figure it out very fast and I had misconfigured some of my OTAs and I could just remap them myself. It was such a delight and I could very quickly from BI see what was happening with the pickup and then see if Adamise or the Muse RMS had picked up on that in the algorithm and it was so smooth that I can imagine myself back into the revenue manager role in a hotel knowing how many Excel sheets we were running and doing so much analysis on paper and it was just so painful and suddenly all of it sits in one place where you can adjust availability or accept all of these price recommendations. It was it was the light I have to say. Yeah and I think like there's a lot that you can do today, but it also starts to open up all of these new sorts of opportunities. I think I mentioned earlier the ability to connect to different data sources to Muse BI. I think it is a really, really interesting one especially when you consider something like Google Ads data which we can now feed into into Muse BI and what you can do the sorts of questions you can ask. Maybe you could ask these questions before but answering them were very, very difficult before. So the sorts of questions you can answer now is based on what I'm spending on my ads over here, what is that actually turning to in actual revenue in the property but not just book revenue when a guest is actually on site, where are they spending their time and where are they actually spending money as well? Are they in my bar, are they in my restaurant? I'm being able to actually tie all of that all the way through your revenue strategy to your marketing strategy in one place becomes incredibly powerful and again starts to unlock a different way of optimizing your business that is more and optimizing for the guest. Yeah, I am an optimizing for the guest experience as part of that as well. Then I think was ever possible before when these were disconnected systems. And how do you feel about co-pilot versus ultipilot? because we have both modes, but which is the better mode? - I have an opinion, but I think what's nice about the Muse Oramis is you can choose, right? It is very difficult on day one to say, I'm just gonna turn on autopilot and this job that I've been doing that I really understand deeply, I'm just gonna hand it over to this engine to run it for me. And so I love the fact that actually in there on day one, I can go in and I can say to Muse Oramis, start giving me recommendations and it will give me recommendations with an explanation. So I'll start to understand how it's thinking about setting pricing and why it's thinking about it. And as I start to get more comfortable with it, I can accept or I can reject. And I think what we see is over time, more and more people start to accept. And when you get that level of comfort that actually this system, it is optimizing in a way, maybe not always the way I would have, but I understand why it's doing it. And I can see the results from it. That ability to turn on autopilot becomes very, very powerful. And so when I say I have an opinion, my opinion is autopilot is absolutely the way to run this system, but I understand it takes time. You have to build that trust and you have to see the results from it. What's amazing is we are seeing the results from it. We see in our data that customers who turn on autopilot are legitimately more successful than customers who are manually overriding or manually accepting prices inside of the system. >> I had a conversation with Richard who runs our data teams and I was deeply questioning, why is it? Why is it that when you put switch to also pilot and you start to get the results, the results are so much better. And we ended up saying, well, it's because you let the algorithm learn and it's doing these constant price experiments. And it doesn't have to wait for a human to come in on Monday morning at 9 AM to accept the price changes. It does it throughout the weekend. And it learns like, right, this price was too much. So let me pull it down a little bit. And it's the constant price experiment. So yes, there is a level of trust that the revenue manager needs to have in the algorithm. But once you let it roam free, the results really start to stack up. It gets several months of experience because it really starts to learn your seasonality. It gets really, really exciting. >> Yeah. When you look at how it's actually working under the hood, so you touch on a thermal, like the price recommendations are being generated around the clock, like all day, every day. And it will experiment pretty much down to a five minutes interval. It will try to optimize based on the signals that it sees, based on the demand that it sees, based on everything that it sees happening. Should it tweak it up, should it tweak it down. And when you have something that's doing that, like, five, every five minutes all through the day, I mean, across the news customer base, this algorithm is learning from hundreds of millions of experiments constantly and what's working and what's not working. And the reality is, despite any of the institutional knowledge that any of us have, it's just not possible to experiment at that race, the way that autopilot is able to do it. And it makes sense that if you're able to learn from your experiments at that sort of scale, you will get better results over time. If a human could click the button that often, they would get better results over time, but it's just not, it's just not possible. Yeah. Any insight you can give to what the future robot will look like, because right now it's still, you know, pricing up rooms overnight. Is there any further functionality that we're adding that really differentiated from other revenue management systems? Yeah, there's a lot. And again, especially when you think about having all of these systems in one place, on the kind of news operating system, where we're able to have this common data layer, and data model to work off. And some of the things I'm most excited about are really, how do we optimize around the guest, as opposed to optimizing around the room? And how do we look completely into end-of-the-type of segment that we're able to attract? What does that guest, you know, what sort of price will they buy at? What sort of experience will they want when they're on-site? Where will they spend time and money when they're on-site? And starting to tune a much more personalized set of pricing recommendations that goes beyond just the room. So we may sell the room at some price, but what about an allowance that comes alongside that? How can we test with things like allowances to have somebody spend more time in the restaurant? How can we test with allowances to have somebody spend more time in the bar? And all of these sorts of different strategies that you can have very, very personalized, like hyper-personalized experiences and pricing for individual guests, based on everything that we learn about who comes to your hotel. That's very much where we're heading. I think that future is much, much closer than it has ever seen in the past. So moving away from this idea of revenue per room to revenue per guest, I think is what you'll see a lot more of from the news or MS on the whole outbreak system. And it sounds like a lot of the pieces of the ecosystem are really coming together now. Where we see all the outlets. We know these are about a customer what they spend last time. And then we can connect the communications hub. We can create special offers down the line. And I think it's this real benefit of the amount of data that we're collecting about customers. Not an aclypio, but actually in a really exciting way where we get to know them. Because they are living with us. And all of the systems are connected together. And then you can have AI or the RMS create these really special offers. And this is the thing that gets me the most excited about the releases that we're doing at Unfold. It's just that whole ecosystem story is coming together really powerfully. Like at the end of the day, there's one way to look at the which is that all it's creepy we're collecting this data about a guest. The other way to look at those is put yourself in the guest shoes. And if we can create amazing experiences for guests, then it's a win win for everybody. And I think what you see more and more with what we're releasing on fold and in the coming months is we can help our customers create amazing experiences for guests. And the guests will be happier. They will come back more and they will spend more on everybody wins in this scenario. It's not like we're creating data or we're we're capturing data for no reason. You're now able to see how we can use that data to actually provide really really meaningful experiences. I think that's incredibly exciting. I don't want to you know be coming into hotels carrying a carrying my luggage and trudging up to the front desk to have somebody staring at a monitor and asking why I'm there. You know, these are the sorts of experiences that exist in the yesterday. The sorts of experiences that exist in the future are you know, the hotel knows who I am before I even arrive. And they greet me with a personalized message and they hand me a little d'assah whiskey because they know that I like a glass of whiskey. And they don't ask me am I there to check in when it's blatantly obvious that I'm there to check in. I love it. Did you get a glass of whiskey and I'll tell that you're staying in today or not? No. No, but they're not in use customer. That's not a music. Thank you so much for joining. I was actually really excellent. No problem. Thank you for having me. Next on this episode accounts receivable and it's an important category because often accountants are hidden in the back office and we don't really think deeply about the pain that they go through. But if you've ever worked with accounts receivable in a hotel, you know the pain. You have open bank statements on one screen. You've got the pms on another and possibly an accounting system and everyone is figuring out which wire transfer matches with which invoice. So I invited Yael to join me today. She's the VP of FinTech on the product and engineering teams from use and she's here to talk about how she is helping fix that particular problem. Yael, thank you for joining me. Talk to me about accounts receivable. Is it is it's really so painful? Oh, well, you know what it is when we speak to some of our customers, the scenarios that they tell us about are crazy and I actually got to live through one of it sort of myself. I was organizing an event for my team at news and so I reached out to one of our hotels and we made a group booking for the people who are coming to the event. And so my event was two days, but some of my team wanted to come in ahead of time and maybe spend a couple days in the city, you know, on their on their own dime and maybe a few others wanted to stay two days later. So my one booking with the hotel of let's say 15 rooms became 15 rooms with 17 or 18 different reservations attached to them that's starting a different, you know, time and end in different time. Get paid by different people some of them use paid some of them the employee you know picks up for their own time and so the hotel has one customer here that's mues, but that entire event generated maybe 18 19 different voices. And then when people come and go every time they check in they check out those invoices need to be raised. They some of them need to be sent to me because I'm the one paying some of them are actually sent to the employees who are paying their own stay and if you're the accountant what you see is others in event it's worth I don't know 10,000 euros, but there's 18 invoices against it that will be paid at different times that you don't know exactly when because maybe they're not paid by credit card made it paid by a wire I mean use the company is going to pay by a wire the employees might pay by credit card you're there holding this bucket. And you have no tool you're watching your bank account and you're seeing money land in the bank account and you have to say this amount I need to correlate to the reservation by news so their amount owing is now deducted by this much but there's still an amount owing when is that coming I don't know now some other amount landed basically they're doing this like you said bank account pms invoices sometimes. The company that sends them payment is not going to say news whatever it's going to say whatever we call our company you know and that's the problem we're trying to solve we had hotels tell us it takes a 20 minutes for an individual in the accounting department to fully reconcile an invoice 20 minutes that this yes person spends on one invoice that one invoice can be worth 100,000 euros or 100 euros so how do you prioritize your time and the biggest problem for hotels is sometimes because they need to prioritize. They will accept that some of their lower amount invoices are maybe not reconciling and maybe they're taking a loss they're writing them off why should they have to write off revenue is the price so the problem is real and like and like your example real like broken to many hotels and I often asked them about what what the counter can I speak to them and like what you described is a real genuine pain. So what have we built? So we have built a product which fully automizes end-to-end the process of raising the invoice to reconciling it in your accounts receivable ledger. And the way it works is, as a guest, checks out of your hotel or an event is wrapped up, you're closing a bill, basically. We will automatically raise the invoice for you and we'll send it to the payer. When the payer receives the invoice, the payment that they will make will use either, they'll use a credit card, so they use our payment processing or they'll use an iBand that is on that invoice and that iBand is mapped to them personally. So when I use an iBand to pay that with a buyer or a bank transfer, when the money lands in the hotel bank account, Muse will know exactly who the payer is because there's only one payer that can pay sure that iBand, that the iBand. And when we see that money land in the account, we will then automatically go to the city ledger of the hotel and we will say this invoice has been paid. That's end-to-end the journey. Now there are gonna be other scenarios, what if it was underpaid or overpaid? What if the company paid a number of like, they added a bunch of invoices that were owed and they paid them at once. So now a single payment is either reconciling or not reconciling over an underpayment or maybe we need to say, attribute this to a number of invoices. So we are actually building a reconciliation agent. It's gonna be driven by an AI bot. It's gonna look at the amount and it's gonna find these scenarios for you and make the recommendations. It'll say, you know, this amount fully reconciles to these five invoices. Therefore, you can mark them as reconciled and paid or this amount is underpaid. You know, the invoice is underpaid. We've collected money for you, but you have money owing and you need to send a reminder. And our system will actually automatically send the invoice reminders as well. So the idea is to really absolve them from having to manage all these exception scenarios and think about, will I get paid? Will I not get paid? They will see exactly what's getting paid, exactly when and they'll have the confidence that their cash flow is sound. - And like cash is king, if you're a hotelier. - Take it exactly. - You know that we are in a fickle business, unfortunately, and if you're not reconciling, you don't know which ones are chases, which time and in hotels, honestly, cash is king. So this is, well, it seems like a really small thing. This is actually a massive thing because invoices are usually the largest amount. You have to collect. They're four large events and large group businesses. So having accounts receivable, completely automated, so that even if transactions come in the weekend, it's instantly reconciled instead of, you know, Monday, midday, once the account and gets to opening their backstabings and starts to reconcil some of these transactions. - Exactly. - So is the reconciliation a.i.agents or how does that work? How does it know to match it to the right transactions? - So like you said, when we start from assigning a unique pair ID to every pair. So that is the, let's say, the kickoff point of we know who is paying this money, right? So now, you know, who's paying? And if you know all of, let's say, the amounts or the invoices that are due by despair, 'cause it might be more than one, like we said, you can apply intelligence to say, well, if they're not matching the amount matches or doesn't match, you know, what I'm expecting? Well, what is the exception over under, or maybe there's multiple amounts that are still due and I can apply, you know, I can start applying to each individual amount and see where I end up, does it fully reconciler? Is there still an amount owing or overpaying? So that is what the reconciliation agent will do. It will basically consider all these scenarios. It will make recommendations. And what we're hoping for, obviously, that in the future, the accountants will be so confident with this agent that they will just basically let it take decisions to say, I'm closing these three invoices, but the fourth one will remain open because there's an amount that still do. But I think there's also a world in which the agent acts as like your assistant to say, I'm recommending that all of these be closed and this one remain open do you accept? And then the accountant can confidently say yes. And what happens if we get a payments or we can't attach it to an account, like if we don't know what events it links to, will that be lost in some way? - No, I think that is where we will kick off into a manual workflow. So this is where you raise the exception to the accountate and you say we've been unable to identify, maybe someone made a mistake, like maybe they, you know, we give them the VIP and to pay, but maybe they use the wrong one somehow, I don't know. And so money landed in the account and now you really cannot match it. So hopefully we will cover as many of the, you know, the workflows that are automatable. I guess in any automation workflow, you want the human to only deal with the problems that humans alone can solve. Maybe you do need to pick up the phone. I don't know. Maybe something, let's say, is overdue way too long. And at this point, it's like, that doesn't matter how many reminders you send, it's just not getting paid, you need to kick off into collection, you know? That's a process where maybe that's the point where human intervenes and hopefully they only intervene where they need to because everything else is being taken care of. So we started as a PMS 13 years ago, 14 years ago. Today, you know, we have a full payments platform. We launched business intelligence, we have a musenbed of RMS, we're launching accounts receivables, all happening inside the same platform. From a fintech perspective, what does it mean for hotel to have all their functionality running from the same system as their operations? Yeah, we've been thinking through that, we've been given so much attention and advantage to departments in hotels like Farnabhaos and Back of House and we've not really yet taken care of the accounting or finance department. In the finance department, of course, they all day long, like you said, cash is thing and they're looking at their cash flow and then you predictability and accuracy. And because all of the hotels, data and reservations and decision making already flows through the PMS, everything that has a financial impact is already there for them to leverage. So the thought process for us is, can we take all of this data, everything that we know about your operation, cross-reference it with everything that we know about your finances because we collect the payments for you and we're now collecting invoices for you and maybe we can extend this so that you can actually even do your payables through us. And now that if you're, we see the incoming funds and your outgoing funds and we see all of your liabilities also through deposits and city ledger, we can help you really understand your financial standing. We can help you understand your cash flow and forecast and maybe we can give you services that other actors in let's say financial services, especially let's talk about lending, where some banks will be hesitant to lend to hotels because they don't know hotel operations so much and it's a risky business like you said. It's a future delivery of products so a lot of risk element to it and maybe the conditions at which hotels will get loans from banks are not so good, but we are in a position to maybe help connect you to a lender that does understand hospitality and weaken with our data that we have helped you secure loans or maybe we can actually extend some sort of cash advance to you as well. And now it's tied to your actual cash flow of the business. So you know exactly what your risk level is, how much you need to cover for, for what period. I think we just know that we're so well positioned to help hoteliers, especially the smaller ones, especially ones where it's not a 50 people accounting department, it's not a large brand with many, you know, many properties. It maybe is a two, three, four property hotel, maybe it's even a smaller one where you have like five people on the staff and one is the basically finance person. It does every, he does, or she does everything from like, you know, accounting to treasury and all of that stuff. Those are the teams that we really want to enable to be better, to be more competitive even. - I know, I love the vision for it. Like it sounds like today we've launched accounts receivable, but there's so much work going on behind the scenes because we genuinely want to be the one-stop shop for everyone in the hotel that touches money or revenue in some way and we need to make sure that their lives get easier. - Yeah, exactly. I think no one's doing that for hoteliers yet. - Yeah, we will be the first, hopefully, if that full end to an experience. - Yeah. - I thank you very much. - Thank you. - So that is the end of the episode. We've covered news automations, guest messaging, newsBI, newsRMS and news accounts receivable. So there's a lot to take in that we've announced at unfolds last week, but make sure that if you, you know, if we were too fast that you go back and you listen to some of the pieces, but as always, if you want to see more of this, go to our website news.com, request a demo, our team will be very happy to show you around through some of these amazing features of the music system. I thank you all and hopefully I'll see you all soon. (upbeat music) (gentle music)