Good afternoon. I'm Brent Bracelin, the Co-Head of our Tech Research here at Piper Sandler. The next session, we have J. D. Fay, the CFO of Matterport. J. D., welcome to Nashville. Yeah, thanks so much. Great to be here. Absolutely. Thank you. So maybe we'll just start out with a higher level view, the Spatial Data Market, big opportunity, very early. But if I look at kind of performance over the last, you know, couple of years, clearly not materializing as maybe fast as we anticipated, pressured a little bit by some of the macro. Maybe let's start with some of the actions as you think about right-sizing the business model and the investments with the opportunity. Yeah. Yeah, well, you're right, it is a big market. As a refresher, there are 4 billion buildings in the world. There are 20 billion unique spaces within them. That's really our market opportunity. And, while I think we're by far and away the biggest company doing Digital Twins and helping people better manage their buildings this way, we're just scratching the surface with only 11 million Digital Twins so far. But it is growing at 200,000 Digital Twins & Spaces per month, so we continue to grow in all kinds of up and down markets. With the current market climate, you know, we certainly are at a bit different place than we were, when we went public a couple of years ago, which was a big focus on investing for growth. We went public on a plan to make significant investments, and we did that. And we changed the company back then from a profitable company to one that had a significant cash burn. Today, of course, we need to adjust for the climate that we're experiencing, and so we are making changes. In just this quarter, we restructured the business and eliminated a number of our programs and about 30% of our staff to focus in on essentially two areas. Those two areas are property marketing, that includes buying, selling, leasing, homes, buildings, condos, and promoting hotels, restaurants, and other facilities, and operations and construction. These are the other use cases that are more enterprise-oriented around insurance and renovation and construction, engineering, those kinds of things. Each one of those areas is about half of the business. And geographically, we're focusing in on our strongest markets, North America, Western Europe, and Japan. So with that focusing, it allowed us to decrease our investments in other areas while protecting as much growth as possible. And in fact, the subscription revenue growth is, you know, it's been at the top end of our range and outperforming all year, and that's been, that's been great. So that combined with looking at our program spend and reducing our physical footprint a little bit is enabling us to get on a much faster path to profitability. And we brought in that target by a year and said that our goal is to get to cash flow from operations break even by the end of next year. To accelerate this path to profitability, you, you still have a pretty strong balance sheet. Let's maybe double-click into the opportunity. If I think about maybe the property management set, one of the two kind of key areas for you there, spatial data management, adoption in property management, where, where are we at today? And what are some of the new use cases you're starting to see pop up there? Yeah, we do have a strong balance sheet, first, about $440 million on the balance sheet with no debt. And, we've actually decreased our burn rate by 60% year-over-year, and we're on that path to zero, and then to positive. So, we'll continue to have a nice, strong, healthy balance sheet. So I don't have to worry about that, which is great. In facilities management, property management, it's a newer area for us, but combined with the other operations and construction use cases, it is now half of the business on the Subscription Revenue side, which is great. We see a lot of pull in specifically property management around space planning, renovation. This could be renovation or redesign of an office, or redesign of a factory floor to put in a new piece of equipment. There's a lot of compliance involved. There's fire and safety codes, for example, permitting issues. Having a dimensionally accurate Digital Twin that can be collaborated on f rom people all over the world, is incredibly valuable for that. It's very efficient. There are also customers that generate work instructions for factories from remote locations. They've never actually set foot in the factory that they're writing on, and they're doing that all from memory and stories and other text-based tools, whereas now we can give them the actual, perfectly accurate visual representation of the factory that they're writing on to better inform their work. So there are a host of property management use cases that are coming online now with Matterport, as I think our awareness is going up in this operations greater market. How do you, Is it blocking and tackling, you think, over the next couple of years? Are there specific product features that you could add that are gonna kind of maybe help accelerate Adoption or Partnerships? As you think about all that, how do you broaden penetration in that market? Well, one is awareness. Yeah W e're still a small company. Yeah. You know, it takes focus. We have a limited amount of investment dollars to let people know what we can do- Yeah A nd to teach them about alternative ways of managing their work. That's one. We do find partnerships pretty important. We have one that I'm particularly excited about with AWS in this operations space. It's with their TwinMaker product, and we're essentially the visualization or digital twin chassis for all the AWS data for a customer site, that the customer then uses to improve their operations and do the remote management. Very excited about that 'cause we're selling together, and we're a part of the AWS Marketplace, and of course, they have a depth and breadth of customers that are pretty unique. So those are a couple of the areas of things that we have to do. Finally, I would say that we are also working with respect to our development, to develop new features and solutions that complete more of the customer's workflow. I think the further we can get through to completing their tasks, the more value we create for them, the stickier our solution is. And that creates pretty meaningful expansion opportunities for us as well in our MRR. And so being able to do more than, say, one step in insurance underwriting and getting all the way through to the actual quote or submission back to the carrier is, that's a good example of how we can do more with our digital twin and get all the way through the workflow and eliminate as many manual steps as possible. Totally makes sense. Let's now double-click on the other side of the business, the residential side. That's really where you kind of really saw this explosion, you know, during the pandemic. As you think about the opportunity, it really felt like strategy was: how do we reduce friction to adoption? Like, let's get as much adoption as possible, had some really high-profile partnerships and relationships, met a really specific need. As we've normalized, maybe level set that residential opportunity and how you're thinking about trying to re-accelerate growth. Yeah. We have seen an up and a down through COVID and post-COVID, with the higher interest rate environment lowering, particularly U.S. residential real estate listings, quite a bit. We've actually grown this cohort and our revenue year-over-year by single-digit%, while the number of U.S. listings has gone down by 18%. So it's a pretty remarkable, I think, outperformance relative to the overall market. We're penetrating more accounts, and we are protecting and growing that revenue. Not as fast as we'd like, not as fast as we saw even pre-COVID, but in a down market, we're still growing, so that's pretty important. Forecast, by the way, for listings in the United States for next year is up 13% from here. So we think that can provide a very good tailwind, just all things being equal, to the residential real estate cohort or segment of our business. But more than that, we're working on new features to add value to the sellers and the buyers of residential homes and condos. And specifically, we've talked about one that's in development, and it's currently in private beta, which is called Property Intelligence. So as you're going through the steps to get ready to sell a home, oftentimes you think about, "What do I need to improve in my home to get the best price, and to ensure I've got a positive ROI on those investments?" And that's a fairly manual, anecdotal process, typically. But with Matterport, because we've got 11 million Digital Twin s and 33 billion sq ft in our Data Library, we can actually tell sellers, "Here's how your house compares to others in the market, in the neighborhood, in the city, in the state. Here's how your kitchen looks compared to others. Here's what features you have and they don't. Here's what features they have that are valuable that you don't have. And so we can provide a very specific list of what to do to best prepare your home for the maximum price at the best cost. So this level of insight is only possible if you've got- The data M illions and millions of homes already in your data set, and you have the ability to understand everything in those homes, every furniture, every table, every counter, every appliance, every material that's used and the state of that material, the height of the ceilings, the size of the rooms. All of that spatial context, nobody else has. So we're training our models now on this data set to be able to provide these kinds of insights to people, not just in the residential real estate market, but also in commercial real estate and other spaces, too. And that will help us, we believe, drive that incremental growth, get us back up to the high growth rates we saw in the past. So talk to me about, like, the monetization of that. So today, let's say I scan my home predominantly for marketing, external marketing. That same scan can be used for Property Intelligence. Hopefully, you know, you're gonna charge for that. Yeah. Or. Okay. Well, yeah. Like, what does that, what does that look like? Yeah. So, What, have you got any insights on what people are willing to pay, $50- Yeah A home? I don't know. home? I don't know. Well, we have, we have this in private beta now. Okay. So we're gathering feedback from customers who are using it now. So nothing to share yet on pricing today. But certainly one of the things that we've done over the last year and a half is re-architect our platform to allow us to charge for these value-added insights. We had traditionally charged pretty much solely based on the number of spaces created that you had in your account. Now, we're developing... or we have the ability to charge based on these value-added services. So that was a platforming re-architecture activity we had to go through over the last year and a half. We did that. It's done. Now, we're working on those features themselves that we can use as value-added upsells or add-ons that customers can add to their subscription. And so today, you went from number of spaces to, is it like a platform fee and then add-on fees, or? It could be like that, and it will probably vary based on the type of use and the type of user- Okay. Whether it's a consumer or a real estate agent versus an enterprise. In today, with enterprises, we're already bundling different features and creating a solution based on use cases. Okay. And we are seeing ARPA go up in that cohort, which is great. But we can imagine back on residential real estate that not only can we provide insights about how your house compares to others, we can also allow you to reimagine your house. And so this is like a visual ChatGPT versus a text-based one. And we showed this in our last earnings call, in a static slide, but we have working in the lab demos where you can enter in what you'd like your space to be reimagined to be, and that Digital Twin will be recreated in that way. So if you have this room we're in right now, you could say, "Remove all the tables and chairs and turn this into a trading floor." And our engine can deliver the desks and the monitors and the chairs that are appropriate, and tell you how many people can fit into that trading floor in this room, and it can all be dimensionally accurate. Or you could go further and say, "Here's my digital twin of the floor of this hotel we're in. Take out all the walls and just reimagine this as condos." And our engines are training to do that now. So the reimagining of your space with visual search and visual results, I think can be very powerful for interior design, for architecture, for space planning, and it can really accelerate all of this work, which is largely manual today. What do you think is gonna be a higher value add-on: Property Intelligence or the reimagining renovation spaces, or is that not the right way to think about it as a different cohort of user? It's hard to say. It's pretty early to know where the- The value- Yeah, the uptake and the nuances of the different value propositions will be. What I do know is that in the commercial space, moving around equipment and office furniture is a big expense. And so, you might have fewer customers in that space, but that could be a very high-value activity to allow, not just space planning, with virtual staging, but also having the AI engines do it for you. Again, that could be very valuable to them. So you're kind of entering next year with some new features that we're gonna monetize the add-ons. You potentially have listings going from negative to positive, which would be certainly a tailwind. Today, the subscription business is at $80 million run rate. What would have to go right for that to get back to a 25%-30% kind of growing business? Yeah, by the way, is our goal. I mean, we are very- Yeah, sure F ocused on getting it up into those rates again. So you're right on residential real estate, both property intelligence add-ons as well as, listing growth will help. The operations and constructions side of the business is growing at those rates. So continuing to drive penetration there brings up the average, of course. So that's very positive, that that business, in today's climate, is doing that kind of growth. And it's now half of the business. In addition, we've done price increases. This, for the first time in our history, we completed that process in July. So the entire population is seeing a 7%-10% price increase. And, that's for all monthly subscribers, and then for any annual subscribers, there are negotiations when, renewals occur. So that will help. As we touched on briefly, some of the partnerships that we have going on, not just with AWS, but also with our resellers, as we're expanding what they can sell to sell our total solution, including our SaaS, are all tactics that are in the mix that we're implementing to get back to this higher growth rate of SaaS. As you think about the implication of the price increases, we're well down that path, any change, like in the churn characteristics, maybe? What have you learned maybe around retention? Obviously, it's different probably by enterprise versus, you know, consumer, but what, what, what are the learnings on the- Yeah P rice increase so far? Yeah, so I think about this as, as sort of two cohorts of, of customer size. The enterprises are generally on contracts, and so, we don't see a lot of, churn activity or anything unique there with price increase because they're, they're working through one, two, three, even five-year contracts. But on the SMB side, where there are, tens of thousands of subscribers, we expected to see a little bit of churn, with the price increase. We've modeled that in and put that into our guidance. We did see that as expected. Yep. Nothing unusual there. That churn has moderated. Okay. We also offered an annual contract promotion when we did this. We've seen an uptick in demand for that promotion, so that helps decrease the volatility a little bit more in the MRR, because we have more customers on annual plans than ever before. And that's creating a bigger deferred revenue backlog. It's as large as it's ever been. If you include deferred revenue and RPO, it's about $82 million. So that bodes well for future growth. So overall, I would say the price increases were very well received. I think people understand that, prices do go up as more value's been delivered. Feedback's been positive, and we've provided folks a way to essentially right-size their plans for their activity and be more—in being more flexible in that way, I think, the customers have responded well to it. Perfect. Before we kind of pivot to the AI conversation, which I think is important, we're all having it for every company, let's just talk about the Spatial Data Market. Because maybe it hasn't materialized as fast as expected, you are prioritizing in a couple of areas, which totally makes sense. And but that also does suggest other spatial data companies might try to do some fringe things. Longer term, does that create maybe more of a buy consolidate opportunity if some of these niche areas of spatial data start to percolate, you can then buy some of those? And just thinking through the long-term vision as you... The consequences of a focus, which is good on profitability, but like- Yeah C apturing a bigger swath of opportunity. Yeah. How to address that? Yeah, well, we try to be very thoughtful about where we focus so that we aren't leaving, you know, real market opportunities on the table for others. Yeah. So that's one. You know, so we have that experience from our past lives to make sure we target restructurings well. We've not exited any markets, so fortunately, the product is a standard platform with vertical market-specific add-ons and workflows. And so a customer from any vertical can come into any of our channels or our direct sales and still get the Matterport solution. And so that's also a part of the strategy, is to make sure that we capture all the demand that comes from those other areas, too. You know, we're also—we've been active as an acquirer in the past. I will tell you that, you know, it's we still think we're leading the space in terms of scale and technology advancements. So, you know, I don't presently see a lot of M&A opportunities out there. But, you know, I do keep my eyes and ears open for those kinds of things, you know, if they materialize. But right now, I feel like, you know, we're pretty well positioned as the sort of Democratizer of Digital Twin Creation and the platform on which you can then move to datafication of the built world, which is kind of our vision for how we leverage the value of the Data Library we have. Last two questions on AI. One, how are you thinking about leveraging AI internally to lower cost and improve automation? Have you had any wins so far? And then two, you have in the past, sold data, right? And data feeds a lot of these things. What's the revenue opportunity? Do you wanna be the data source that feeds others? Do you see that as a viable business, or would you rather take your own data and create your own apps on top of that data and not necessarily sell just the data? Yeah. Yeah, so in terms of internal work with respect to AI, well, first, you know, we've been using AI generally for 12 years, our whole history, to create these dimensionally accurate Digital Twins. They had to have the technology, the software has to have been trained on something then to begin with, to be able to solve problems in the data capture, like occlusions, where the camera didn't capture the back of the table. Somehow the digital, the software has to figure out how to solve that problem of what does the back of the table look like, and what is the size of that table? So we've been using AI since inception. In fact, we can now create three-dimensional accurate Digital Twins from two dimensions, from photographs, because we have so much data and the network's been trained for so long on ground truth data, we can do that. So the expansion into generative AI and LLMs is kind of like a natural extension for us. It is sort of the embodiment in some ways of what we planned to do all along with the datafication of the built world. We planned from inception to deliver insights based on mining the data in not just your building or home, but all of them. So our internal use is largely focused on how we can develop insights for our customers a round AI. We're doing a little bit of work experimenting with AI in terms of how we can consume it in our operations. Yeah. But most of our focus is on being a provider- Got it O f solutions to customers. So that's kind of the first piece. In terms of how we might best monetize- Yeah, the data our Data Library. Build apps on top of the data, not sharing the data. Yeah. Yeah. I mean, today, I feel that, you know, this is extremely valuable data set based on the original data licensing you mentioned we did years ago. Yeah. It's a multi, multi-billion dollar library, and that was one that was much, much smaller. We're growing at 2.5-3 million Digital Twins per year. I think today, we're focused on creating applications that are using this proprietary data set that no one else can train on and delivering those to our customers. You know, you never say never, but we think that is kind of the pathway to monetization and a unique, defensible product set that our customers will value. Totally makes sense. Well, J.D., thank you so much for sharing insights here, and enjoy your time in Nashville. Thank you so much.