we're at KeyBanc. We have Peter Benevides here from Olo, CFO. Peter, thank you for, for joining us today. Thanks for having me. We've got about 25 minutes for a fireside chat. We'll do maybe 20 minutes of Q&A, and then open it up to the audience for, some Q&A at the end. Great. Peter, maybe just to start, give us just a quick kind of headline intro to Olo. Yeah, thank you again for, for having us. Olo is a digital ordering and guest engagement platform focused on the restaurant vertical. Today we focus primarily on the enterprise segment of the market, which we define as having greater than five locations per brand. Underneath that, in terms of the platform itself, the digital ordering and delivery platform helps to support both Order and Pay, and Pay being our enabled payments offering, and an Engage suite that allows for things like guest engagement, marketing automation, et cetera. I think there are a couple of other examples of restaurant software in public markets, but just a handful. Maybe give us a lay of the land as it relates to restaurant software, and just kind of give us an understanding of the landscape here. Yeah, in terms of enterprise restaurant software, there are a number of different sort of constituents within that segment. You have kind of traditional POS platforms, payment platforms, marketplace participants, third-party marketplaces as well. In terms of Olo, where we sort of come into play there is, we integrate with all of those different parties. We have over 300 different partnership integrations, and in particular, within the enterprise segment, there tends to be a lot of fragmentation within their existing technology. It's not uncommon for enterprises to have multiple POS systems, multiple payment platforms, et cetera, all within that, that same brand. Where Olo comes in is we create that kind of homogenized experience, that guest experience, by virtue of having all of those integrations, so that brands can, again, create that, that common experience with, with their guests. What do you think drives... You, You, you mentioned some of the disparate systems that exist today when you, you know, approach a customer. What do you think drives some of those decisions that lead to that, that disparate system of? I think what's interesting is, within the enterprise segment, many of the brands grew up through franchising, where, the requirement for unified staff-facing technology did not exist. Franchisors didn't really necessarily care what, what type of technology you chose to run your in-store operations. As a result of that, as brands continued to grow, as a function of franchising, it created a lot of, you know, variability in systems, even within an existing brand. I think that's an interesting dynamic, maybe unique to the enterprise segment. I think as you kind of move down market into more traditional SMB, less fragmentation, but certainly quite a bit of fragmentation within that enterprise segment. You mentioned the, the scope of services offered by Olo, kind of around the ordering experience and, and pay. You also mentioned, I think, 300 integrations and partnerships. There, there's the potential for a lot of handoffs in that process. Mm-hmm. How do you think about the kind of appropriate scope for a restaurant software vendor, over the long term? You know, what should be kind of bundled under one vendor? Yeah, it's a great question. I would say, again, through the enterprise segment or enterprise operators, tend to want to choose the best-of-breed providers across whatever, you know, whatever service that they are trying to implement. It has served us well over the years to be that open platform that can integrate into whichever services they decide to work with. When we think about those 300+ partnerships that we have, it really runs from back of house to front of house, POS, payment, et cetera. We acquired a company in early 2022, which then gave us integrations into back of house operations, inventory management, labor management, et cetera. I think, again, with the enterprise segment, it's important to remain open. Being open has served us well. I think ultimately, that segment will continue to choose the best-of-breed providers versus kind of that all-in-one solution, which is a, a need I think we can, we can meet pretty well. Yeah. Switching gears a little bit to the macro environment, something that everyone wants to talk about. Two questions around that. I guess, first, from a pipeline standpoint or new sales standpoint, when you think about the kind of enterprise restaurant IT spend environment, what are you seeing prioritized? Yeah. I'd say digital transformation is alive and well within the restaurant industry. These are trends that existed, you know, pre-COVID and have continued throughout. The dynamics that we experienced in late 2022, in terms of elongated sales cycles and deployment cycles, that still tends to be the case. I would say, one of the positives that's emerged as a result of the elongation or maybe some of the macro challenges that, that brands are facing is brands desiring to do more with less. Part of that is. What that means is brands are looking to leverage technology to fill the gaps or maybe become more efficient for both on-premise and off-premise ordering occasions. Some examples would be brands implementing kiosk ordering as a solution for maybe not having the staffing levels that they would otherwise like to have, or I'm sure we've all experienced QR code ordering and pay at table. Those are all, you know, experiences that we can power today in, in some of the opportunities we're seeing in the business despite those ongoing macro challenges. Thinking about that kind of off-premise versus on-premise mix, I think the, the off-premise mix has been remarkably resilient, despite the fact that the world is kind of open at this point. Mm-hmm. What's your read as to why that is? Yeah, I, I think, part of it is just the, the frequency in which we all eat, right? Like, we all got to eat multiple times per day, and because of that, the habits that were formed through COVID, through the, the, the digital ordering experience, have persisted. Relatively speaking, as compared to e-commerce, some of those gains have been given back because, you know, you, you only need so many pairs of shoes, right? versus, versus ordering food is something you do three times a day, or eating food. That's definitely been a, been a positive. The other thing that's interesting is the way that we sort of think about things now is, is less so of off-premise and on, and more so digital versus non-digital. The, the lines are sort of blurring there because many of the, many of the digital type of interactions that restaurant operators embraced during COVID as a means to interact with their guests, again, things like kiosks, things like QR code ordering, have continued even post, post-COVID, and those are all digital transactions in nature. If you look at today, 15% of industry transactions are digital, about 1% of those are on-premise digital, and those are things like kiosks and QR code ordering, where historically, that's been 0. I think over time, our belief is the industry continues to move towards a 100% digital. All of that can be done on, on the Olo platform today, which is exciting. Yeah, that was my next question as to what's the kind of long-term thesis around that mix, but 100% in some form or fashion is, is kind of how you operate. Yeah. I mean, there, there are plenty of examples today of brands that are 100% digital. Again, they've embraced things like QR code ordering or kiosk ordering, where there is no server that you're interacting with when you go on-premise. You're interacting with a kiosk, or you can order from your mobile phone on-premise. I think brands look at that not only as a way to be more efficient in the way in which they serve guests, but it also allows them to really drive better hospitality because you now know more about that guest, because you are collecting data in a more enriched way than you would normally collect that data by just ordering through the POS. Sure. Lastly, on macro, maybe just kind of give us a sense of all these factors that we're discussing here, how that kind of shows up in the Olo model. Yeah. We learned a lot during the 2007-2009 timeframe, in terms of how the industry was impacted during the Great Recession. One of the things that we saw play out, which is a pretty obvious comment, consumers traded down, where in lieu of maybe a better burger concept, they traded down to a more affordable burger. What's interesting about that is, if you look at the composition of the customers on our platform today, 2/3 of those customers are limited-service restaurants, which would be considered kind of that lower price alternative. To some extent, we feel like we are in a way, insulated to the extent that trading down dynamic plays out. You know, that's one of the learnings that we've had, and, and, and again, think we're in a pretty good position. You clearly defined the, kind of the enterprise customers, as you all see it earlier, you know, more than five locations. When you think about the competitive set for you all within that. Mm-hmm ... that enterprise segmentation, how should we think about the competitive set there? Yeah, I'd say the most common thing that sort of comes up in the sales process in terms of competition is the build versus buy decision, where many enterprises are still debating: Do I leverage a scaled SaaS provider, or do I embark on not only building the software but maintaining it? I think that last piece, in particular, is the piece that is most underestimated when thinking about building your own digital ordering and delivery capabilities. The cost to maintain, to make sure it's reliable, secure, et cetera, I think is always underestimated. That tends to be what we're up against most often. What's interesting is, if you look at, the wins post-IPO, the trend has actually gone in the other way, where we've had several customers cut off of homegrown technology, again, in part, wanting to do more with less, and then moving over to, moving over to the Olo platform. So I'd say that's, that's probably the most common, use case. Maybe just as an extension of that, when you have conversations with customers, how are they kind of evaluating the, the return on, on spend for Olo? Yeah. It, it depends on the offering. Again, if I just look at sort of the, the different verticals, Order, Pay, and Engage, I think on the Order front, depending on how you think about that, they're looking at, maybe they're spending some amount of money supporting something they've built already internally and saying, "Well, if I were to forgo the cost of building and maintaining, I could actually move over to Olo, where it's much more cost-effective, much more secure, reliable," and that ROI equation makes a lot of sense. Then, in the case of payments, we think about it in a couple different ways. There's obviously just the, the pure cost to acquire that we have to compete against, but then we also layer on things like the ability to capture guest data. Platform innovations like Borderless, which we announced a few quarters ago, which creates a platform-level identification, such that as you're checking out on Olo Pay-enabled locations, you're checking out with a single-factor authentication versus the incumbent processor, where you're, you know, entering and reentering your credit card information each time. I think making payments more of a strategic kind of guest data capture- Mm-hmm. perspective, I, I think then helps to helps the ROI equation versus just, you know, talking about the cost of acquiring. Yeah, and I, I think that last point kind of transcends the restaurant space. Yeah. There's a lot of other applications with respect to some of those payments, efficiencies, and, and learning. Maybe just expand for us the go-to-market strategy, kind of how do you, how do you sell into these customers? Yeah. We've been at, been at this for a while, you know, from a, from a brand recognition standpoint, really well known in the space. I'd say, again, depending on the, depending on the product suite, there's different constituents that we're talking to at the brand. Historically, many of our interactions were with the heads of digital or the CIOs at the brands. Now, those conversations have moved into the office of the CFO with, with payments product, and then with our Engage suite, maybe the marketing organization as well. From a motion standpoint, we're still predominantly direct sales. We have, you know, enterprise and emerging enterprise sellers that, that look to engage with, with prospects. We've started to build out more of an inside sales function as we've moved into that emerging enterprise segment, and then we have a team that's focused on upsell and cross-sell. Continuing with that thought of, of upsell and cross-sell, when you look across those kind of three segments of product, Order, Engage, and Pay, where do you generally see customers gravitate initially, and how does that expansion opportunity look over the life cycle of a customer? Yeah, for this year, Pay has seen a lot of momentum in terms of adoption. I think, in particular, because the incumbent kind of experience is subpar, and brands are looking for a better experience, and they want to collect guest data, which Olo Pay more effectively enables versus the incumbent processors. We've seen a lot of momentum in Engage adoption, and Engage is ramping, and, you know, aligned with what we planned at the top of the year. That's really great to see. I think what's really exciting about Pay, in particular, and this idea of software with payments within vertical software, is that it, over time, can be very profit accretive. What we're doing in, in essence, is leveraging those existing relationships and going deeper into those relationships, and in doing so, driving ARPU and driving profitability, and if we can replicate that with the adoption of Pay and with the adoption of Engage, that will help to drive profit over the long term. With respect to, to Pay, I think it's, it's still kind of early in the journey when you measure it against the kind of, you know, total GMV across the Olo platform. I mean, how do you think about that, that penetration curve and, kind of what it takes internally to, to get to the end state, whatever that might be over the long term? Yeah. To date, we've been very pleased with the adoption of Olo Pay. It's exceeding our expectations, hence why we've increased our guidance for the year. I mentioned earlier that 15% of industry transactions are digital, 85% of it are non-digital. That's somewhat synonymous in thinking about card not present and card present processing. Yeah. Today, Olo Pay is only servicing the 15% digital opportunity because Olo Pay is only card not present processing. This past quarter, we announced a new partnership with Adyen that's gonna allow us to now service the card present opportunity, and why that matters is because there are 6x more transactions industry-wide that are card present obtainable. If you reconcile that with the amount of GMV we process over the platform today, which is north of $20 billion of GMV, that then means we have a 6x opportunity just within our install base once card-present processing is available. Really, that's, that's how we think about the, the near-term opportunity, and the progress we've had to date is what gives us confidence that that, that that adoption curve will, will continue to go in the right direction. I have two more kind of product-related questions. First, I think I have to ask about AI, just kind of understand how it fits into your product strategy... Yeah ... where you see it as appropriate versus maybe less relevant- Yeah within the, the workflow. Yeah. Yeah, great question. We had an announcement last quarter on a couple, a couple AI use cases from a product standpoint. We announced something called Order Ready AI, which is, at its core, machine learning that allows us to better predict the make time for orders being placed at an individual restaurant location. What that means is that because we're able to see all of the activity happening at that location, in addition to orders that are happening via third-party marketplaces, we can then predict, based on that throughput of that location, what the appropriate quote time for that order is. Why that matters is, obviously, from a guest experience perspective, you don't want to show up at the restaurant or, you know, and, and the food not be ready or delivery take longer than expected because the quote time was inaccurate. In addition to that, it helps all of the ecosystem participants, because if you're a delivery service provider, you're now going to pick up the food at the right time, versus having to hang out in the restaurant and wait for the food to be prepared, which obviously impacts their economics. That, that's one example. We also announced some AI features within our Engage suite. We have an integration now with ChatGPT that helps with the creation of automated emails, and all of the kind of content that gets developed in those emails. We're gonna continue to build upon that, and, and really across all of the different suites, and, it's really, really exciting to think about. Yeah, with respect to some of those announcements, I guess, and leading into my next question around pricing, does that feel like the type of solution that gets added and pricing is reflected, so? Yeah. today we're not- there's no explicit, you know. Mm-hmm ... incremental charge as a result of, utilizing some of the AI features that we've rolled out. I, I would say, I think, for example, the Order Ready AI, if that results in higher cart conversion, that higher cart conversion, when coupled with our transactional SaaS revenue model, will naturally lead to higher transactions and higher revenue. So that's the, the lens in which we're thinking through it. Yeah. I, I think you, you answered my next question a little bit, but I'm going to ask it anyways in case you want to expand a bit. I think pricing has received a lot of attention in the last month or so, across the restaurant software space. Can you just kind of describe for us your, your pricing philosophy at Olo? Yeah, we have what we call a transactional SaaS revenue model, and that has both subscription and transactional elements. The model comes in two forms. You have what we call a service addition fee, which is a fee you pay per month, per location, regardless of order volumes. That varies depending on the amount of the platform that you're using. For example, if you need multiple POS integrations, multiple payment integrations, that scales up. In addition to that, we have a usage-based element that is tied to the amount of orders that are processed over the platform, and the net effective fee per order goes down as volumes go up. In many ways, sort of self-correcting as we continue to drive more value to our, to our customers. No plans to really change that, that philosophy, to date, given that it does have that, that kind of self-correcting mechanism. Sure. Okay. I want to pause here. Just any audience questions? Okay, maybe, one for you on the model. I think you've had some nice ARPU tailwinds recently. When you think about the kind of midterm, longer-term model, how much of a factor is, is ARPU growth? Yeah, it's a really important factor. One of the things you've probably heard us talk about is our 100x opportunity, which we define as 4x more locations, 6x more transactions, 4x more revenue per transaction. Those last two drivers, more transactions and more revenue per transaction, combined, are about a 25x opportunity. That's what shows up in the expansion of ARPU versus 4x opportunity on the location front. ARPU in the near term will certainly be a bigger driver of growth than location, location growth. Part of that is because both Olo Pay and the Engage suite are so underpenetrated. We've had the Engage suite for a little over a year now. Same with Olo Pay, and we're just getting started with those adoption curves. Just to, to round that out, you, you mentioned something around, location growth and how that factors into the, the top-line equation. Maybe just run that back for us and, and how you see that. Yeah. In the U.S., there are about 300,000 enterprise, what we would define as, enterprise restaurant locations. We have 77,000 on the platform today, about a 4x opportunity to expand from, from where we are today. We've shared from a, from a goal perspective this year to add about 6,000 locations to the platform. We're on pace to, to do that. Again, when you think about that 4x opportunity relative to the 25x opportunity, there's just huge, huge opportunity to expand ARPU, just, even just within our, our install base. Sure. In the, the context of revenue growth versus profitability, I think a lot of companies are looking to, to strike the right balance right now. Yep. I'd be curious for your perspective on what you view as that right balance is for Olo. Yeah. I think, you know, we've been profitable now, I think 13 on a non-GAAP basis, for 13 consecutive quarters now, I think is the, the count. That's just something that's core to our DNA. We think that we can balance both the ability to grow at levels we want to grow, at the same time, be able to maintain or even expand profitability. There's a lot of investment that went into the business over the past year and a half to build out Pay, to build out Engage features. A lot of that is behind us now, and we hope to increase margins as we move throughout the coming quarters and strike that balance between both growth and profitability. Maybe just to. We've got about a minute left, wrapping up around capital allocation. I think maybe I'll, I'll first ask specifically about M&A. You have a lot of integrations and partnerships. You mentioned 300. There's obviously a, you know, a preference in some cases to partner. Yep. You also mentioned a, a transaction in 2022. Maybe just kind of update us on how you're thinking about M&A right now. Yeah. M&A, how we think about the kind of build, partner, buy decision really comes down to how strategic we think that particular product or service is to kind of the core vision of, of where we'd like Olo to go over time. When we went through that analysis back at the end of 2021, felt that Wisely and their guest engagement capabilities was core to delivering on this idea of, of hospitality at scale within the restaurant industry. Ultimately, we, we acquired Wisely, which has now grown into the, into the Engage suite. In terms of capital allocation, we have a buyback that's been, been ongoing, which I think is, is helpful. We'll continue to monitor M&A activities to the extent, you know, there's something that can help accelerate that product roadmap, but don't have anything specific to share today. Okay. I think we're about out of time, so... Do you have one question? Just quick around payments, right? Yeah, yeah, great question. The question was around how the payments revenue stream flows through the model. We record payments on a gross basis. What we shared from a gross take rate is 2.5%, is a reasonable estimate. From a gross margin perspective, we see the ability to get to 20% gross margins over time. Admittedly, we're not there yet. There's, you know, some scale that's, that will get us there, as well as card-present being part of the mix, but see the ability to get to 20% over time. Any final questions from the audience? Okay. Peter, thank you so much for joining us. Thanks for having me. Thanks, everyone.