Peter, from Olo here. We've got about 25 minutes, so we'll jump into some Q&A, and then leave a couple minutes at the end, for audience questions as well. Do you want to just start, Peter, maybe with a little bit of background on yourself and a quick intro to Olo? Yeah. So Peter Benevides, I'm the CFO here at Olo. Olo is a enterprise software company. We provide a range of solutions, focused on the restaurant vertical. So solutions that address digital ordering and delivery needs, payment processing, and guest engagement. How about a quick, maybe a 30-second earnings recap for us? Yeah. So we reported last week a great quarter for the company, outperformed both top-line and bottom-line numbers, reissued guidance for the full year, top-line guidance in excess of that Q2 beat, so raising the back half of the year. And when we look across the different key metrics, whether it's location count, ARPU, gross profit growth, all of those exceeding our expectations. So, really great quarter, and we hope to continue to build on that momentum. I think a lot of folks are, understandably not terribly familiar with the restaurant tech stack. Can you take us through sort of like day-to-day versus management aspects of a restaurant, front of house versus back of house? W here Olo kind of slots in across those functions in a restaurant? Yeah. I think the front of house, back of house is an interesting distinction. I would maybe extend that to thinking about it from a staff-facing technology perspective versus guest-facing technology. So when you think about staff-facing technology, it's things like the POS, where that's sitting at the front of house, and all of the operational demands of running a restaurant from that front of house working backwards is typically handled by the POS, and that could be things like the kitchen display system and how orders are processed, et cetera. Where Olo comes in is we are everything that is guest-facing, so every sort of pane of glass, whether it's digital ordering, whether it's kiosk, whether it's guest engagement, payment processing, all of the guest-facing technology is where we come in. Many of the POS platforms that folks are familiar with, those are partners of ours. So we integrate into the POS for today for order injection and order processing, and then again, handle everything that is, that is guest-facing. So Olo serves primarily sort of enterprise-type restaurants. Maybe describe how you guys roll up into the broader restaurant IT budget? A nd what some of the more recent priorities are for restaurants when it comes to IT projects. Yeah. So I think it depends on the particular product suite that we are, we are thinking through. So typically, when we are meeting with restaurant operators or restaurant brands to talk about digital ordering, that's usually handled by the CIO or the heads of digital, which is a little different from Olo Pay, where oftentimes that brings us into the office of the CFO or the treasurer to talk about Payment processing. And then, of course, with Engage, at its core, Engage is a guest data platform with a variety of marketing applications that sit on top of that platform to allow you to more effectively engage with your guests. That typically takes us into the chief marketing officer or segment of the brand. So depending on who we're talking to, it's a slightly different kind of positioning in how we think about budgets. What I would say is, there is a, in the kind of current macro environment, a desire for brands to do more with less and find ways to adopt technology to help drive traffic and drive traffic in a profitable way. So much of how we talk about the solutions that we provide is through that lens, and that could be through digital ordering. You can more effectively transact with your guests and do that in a more cost-effective way. With Engage, if you know more about your guests, you can deploy marketing dollars more efficiently, and so on. So I'd say even though we are talking to different constituents within the brand, the common denominator across all of those folks is: How can I drive traffic in a more profitable, more effective way? So you mentioned digital ordering as sort of this concept that you all consider. I think mix of food at home versus away is another way to take that sort of top-down approach. How much do those metrics matter, you know, a percent move in each versus the opportunity to, say, penetrate the 16% or 18% digital ordering total? Yeah. So order volumes do matter in the sense that, with more orders comes more data, with more data comes more orders, and that really helps to feed the flywheel, and through that flywheel, that really helps to support the adoption of multi-products within the Olo suite. So the number of transactions is definitely an important component about in terms of how we ultimately grow the business. I'd say from an industry perspective, what's interesting is, despite kind of what you hear externally around the macro, total industry transactions are actually up year-over-year within the restaurant industry, and digital as a percent of total transactions is up. In fact, this past quarter, digital transactions were about 18% of total industry transactions, which is higher than any period during COVID, which when I candidly, when I heard that stat, I was actually surprised. And I think the reason for—in particular, because many other segments that had benefited from COVID, there's been a regression to the mean, in the restaurant vertical, the consumer adoption to digital has been very, very sticky. So again, that sets us up really well when we think about how can digital fuel more orders and fuel more payment transactions. As that data continues to come into the system, that then helps to support the Engage platform. You mentioned macro, and I want to just stay on that for a second. Any sort of observations you'd offer aside from the order growth? And then just when you talk to software investors, to fintech investors, what is—I mean, what's sort of the one-liner to understand about restaurant cyclicality? Yeah. So, in terms of the macro, what's interesting when we look across our platform and we look at order volumes, one of the metrics we track is orders per location per day. And you look at that metric in Q2 of this year relative to Q2 last year, and the total number of orders per location per day have been maintaining. And that is despite much of like the pressures around consumer demand and pricing that you've heard in the market. And I think the reason for that is, and again, this flips back to digital as a percent of total transactions increasing, we're seeing the benefits of that because brands are looking for ways to do more with less and digitize more and more transactions as a way to do that. Kiosks are a great example where we've seen a lot of demand for kiosks as brands look to drive more efficiency and leverage within their business. What's also unique about our customer composition is 2/3 of our customer base would be defined as limited service, so think of like the QSR fast casual concepts, 1/3 or more, full service, so that would be more fine dining and family dining. If you look over history, typically what happens is, as inflation rises and consumers start to trade down, they usually trade down to lower-priced options, and that's where that limited service cohort comes in. So on some level, we feel like we're a little insulated, should that, should that dynamic play out because of our customer composition, which again, gives us a little bit of comfort, should that, should that play out. In the context of who your customers are, I mean, who is Olo competing with? Who are you displacing when you are displacing someone? Why are you winning deals in the way that you are? Yeah. So, so again, we focus predominantly on the enterprise segment of the market, which we define as having five or more locations per brand. And there's a pretty big distinction within the, in the U.S., restaurant market, where there's, of the total number of locations, roughly about 700,000 restaurant locations, half of those would be in that 5+ location per brand, and then half are in that kind of single unit, mom-and-pop, segment. That is a segment we don't address today. We focus again, primarily on the, on the, enterprise segment of the market, which means in most cases, when we're talking about the ordering, capability, we are generally or typically competing against, brands that have built their own grown, their own homegrown technology. And, what we've found success in over time, in fact, over a dozen brands since the IPO, have converted off of homegrown tech onto the Olo platform, is really leaning into the total cost of ownership, as well as time to value arguments as to why using software to address digital ordering and delivery needs, is better than or using SaaS is better than building your own technology. I think what oftentimes, operators get surprised by is not the initial CapEx that it takes to actually build a digital ordering and delivery platform, it's really the OpEx. It's the cost to keep the platform secure, to make sure that, security is great, that it's reliable, et cetera. It's that recurring cost that I think oftentimes catches people by surprise. Again, that's something that they could get for a fraction of the cost, by working with Olo. From a go-to-market standpoint, maybe just quickly touch on the process, what it looks like, and what the entry point is for Olo from a product standpoint. Yeah. So the way the teams are organized today is we have teams that are focused on different segments of the industry. So I talked about the 5+ locations per brand as being defined as enterprise. We go a level deeper where we have what we call emerging enterprise, which is really five to 99 locations per brand, and then kind of the more traditional enterprise of 100+. So the teams are organized on those different segments, and for the most part, when it's a new business conversation, orders- digital ordering is still that initial entry point. And then from there, there's a natural extension into payment processing via Olo Pay. And then once you're collecting all of their y ou're processing all of the digital orders and digital payments, there's a bunch of data that is getting spun off as a result of that, and brands then look for a solution where they can house and analyze and act on that data, and that's when Engage comes in. So there's this natural sequencing of adoption across the three suites. That's typically how the new business opportunity evolves. In terms of the upsell, cross-sell motion, we have teams that are more specialized across those three product suites to enable those opportunities. Because what we found is, to my earlier point about, depending on what you're selling, you're maybe speaking to different folks at the brand. You need people who can go very deep on a particular topic, whether it's payments or guest engagement, and we found that having a layer of sales engineering and solution consultants that can go really deep on the product, has really helped to create, you know, more efficiency and more effectiveness in the sales process. A couple of notable recent wins, Quiznos, Dutch Bros. What should investors sort of take away from those? And if you can just maybe talk about contribution timing around those, it'd be helpful, too. Yeah, so I think Dutch Bros, in particular, is a great example of brands, again, looking for ways to drive more leverage and drive more efficiency into their concepts by vis-à-vis by adopting digital ordering. So in the case of Dutch Bros, they are a very fast-growing, if folks don't know who they are, coffee concept, and they are they heavily index toward the drive-thru. And digital is they're looking to digital as a way to, one, form more lasting and better relationships with their guests, but also find ways to drive more efficiency through the drive-thru. And I think why that particular use case is interesting is because if you look across total industry transactions today, still over a third of those transactions go through the drive-thru, and all of those transactions are inherently non-digital, right? We're still using the same process and technology that we've used for 40 years in the drive-thru and go- pulling up and speaking to a voice box. I think that there's a lot of experimentation happening right now, whether it's through voice AI, whether it's through using digital ordering to enable drive-thru lanes or you know, order ahead and pickup, that I think could really help to unlock a pretty big segment of the industry from a transaction standpoint, and Dutch Bros seems like they're a bit ahead of the curve on that front. I want to talk a little bit about or a lot about Olo Pay, but let's maybe start the conversation with how you guys think about the partner versus buy versus build equation. Yeah. So I think whenever it comes to product ideation, we think about it through that like build by partner lens. And, oftentimes, when we decide to build or buy, it really comes down to the strategic importance of that particular product to the overall, the vision and mission for the company. So pay is a great example where initially, if I go back many years ago, we would integrate into, I don't know, two, two-plus dozen traditional payment processors, and Olo was not the, the payment processor for that digital transaction. And what we heard from our brands was that, one, the experience was subpar because of, you know, performance metrics like authorization rates and chargeback rates were not where they wanted them to be, so that was a problem to be solved. And then, two, because of the inability of the processors to identify who that guest was, either, throughout the brand or at a specific location, that became a problem for the brands as they wanted to aggregate that data and build out those guest data profiles, and wanted Olo to try to solve for that guest data challenge. And that's ultimately what Olo Pay sort of the evolution of how we came to Olo Pay, and that was really solving, again, those kind of tactical performance challenges, while at the same time, building the capability to more effectively identify your guest data and then use that information to drive business decisions. You guys started with card-not-present initially. Maybe just sticking with that card-not-present application, talk about some of the early learnings from that. Yeah. So today, Olo Pay is predominantly serving the card-not-present transaction, and you can think of that as being analogous to a digital transaction. We do have some customers who are using Olo Pay for card-present processing, but that is only to the extent the transaction is happening at the kiosk. We're doing the work today to enable card present at the POS as well, but for today, or currently, we're only able to support card present at the kiosk. And what's interesting about that are in terms of, like, the opportunity size, so this past year, we processed $1 billion of GPV through the Olo Pay platform, and again, that represents just the digital, just the card-not-present transaction, against a backdrop of $26 billion of GMV on the platform. So from a- just from a digital standpoint, fairly underpenetrated. But if you think about the $26 billion of GMV as being digital GMV, that means our install base has six times more GMV that is occurring on-premise that would be addressable with a card-present offering. So there's, there's a huge financial opportunity there, but I think one of the things that we are working towards as part of enabling card-present processing is, again, extending the value prop of how do I identify my guest and then use that information to inform our business decisions? That's how we're thinking about the payments opportunity in addition to, again, the, the financial opportunity, but really about how do I con- how can I more effectively identify that guest? And maybe just go one layer deeper and talk about how you guys sort of unlock that card-present opportunity with Point of Sale integrations and things like that. Yeah, so we, we've announced three point-of-sale partnerships to date, NCR, Qu, and PAR, as our kind of initial POS partners. And again, this is to enable both the ability to process payments at the POS, but also the ability to understand the data that resides on the POS. And if you think about that, for a moment, like, that is a, that is a pretty differentiated value proposition. What we're then saying is, we are going to be able to see 100% of your orders and process 100% of your payments, and therefore, give you that full omni-channel 360 view of your guest, whether they're ordering digitally or not. So that's really the, the strategy and the focus, and I will say the brands are really excited about that proposition and what that could mean for, again, driving business outcomes and more effective marketing, and that's, you know, that's what we're, what we're working towards. There's a great case study on your website, Honeygrow. Any sort of highlights from that that you'd- Yeah, it's a great case study. So in the case of Honeygrow, they are using Olo Pay card-present processing for the kiosk. And in their case, they're unique in that the kiosk is really the only way to order inside the four walls of Honeygrow. So in many ways, the kiosk is sort of a proxy for the POS. And in that situation, we are earning six times the amount of gross profit per unit than we're earning today, as a platform average, which aligns to the 18% digital going up to 100% of transactions. It's that 6x multiple, and we're seeing that play out in the Honeygrow example. So it's really scaling that opportunity into the 82,000 locations that are on the platform today, that can really help to fuel a re-acceleration in gross profit. We're sort of talking around TAM expansion in a way, the catering opportunity. Can you sort of expand on what that represents? Yeah. So really, the kind of fundamental building blocks of how we grow the business is adding more locations to the platform or increasing ARPU, the amount of revenue we earn per location. How we increase ARPU is through multi-product adoption, so having customers subscribe to more and more products, pretty simple. Catering is one of those newer products that brands are have been adopting in part driven by kind of the macro and the desire to find ways to increase revenue per square foot, which is an important metric to them. So if you're a restaurant operator, you may have times of day where you have you know you have employees and inventory that are not being fully utilized. That's a great time to run a catering program and use those time slots to fulfill catering orders. We're seeing a lot of demand for catering. What's interesting about catering is that you can think of it in some ways as an entirely new digital ordering instance, in that everything that we've developed for the digital ordering use case, whether it's delivery, marketplace enablement, payments, all of that is applicable to the catering use case as well. I think the more and more success we have for catering, that's gonna set us up for, you know, a second and third bite at the apple with all the other products that we've developed. The other thing that I would mention on catering is that we're finding it to be an interesting entry point into top 25 brand conversations. Many of the top 25 brands that are out there have built their own technology, and how we think about working with that segment of the industry is by trying to find ways that they can use the technology that we built to augment the thing that they built. So maybe it's not an entire rip and replace, but there's things that we can do to help them reach their goals faster, and catering is one of those things where, again, maybe they built their mealtime or their on-demand digital ordering internally, but they could look externally to fulfill that catering need. Just maybe jumping over to some model-related questions. Take a metric like net revenue retention. Can you sort of disaggregate that for us for Olo and what it looks like? I mean, you've talked about ARPU expansion, but I'm sure there's some other elements to it as well. Yeah, so in terms of NRR, again, two key drivers there, multi-module adoption, in particular, Pay, because of the outsized impact that can have on revenue, and then the sustainability of digital ordering. There is a component of our, of our monetization model that is usage-based, so, you know, as digital grows, that will help to drive, ARPU and help to drive NRR. We've now, I believe it's been two sequential quarters now, where NRR has been in excess of 120. And, I think as we continue to have success in multi-module adoption, that will help to drive NRR, ARPU, gross profit, operating profit, and so on. Olo Pay, I mean, it's a big... It could be a big contribution to that formula. Maybe start with expectations for Olo Pay contribution this year, and then dive into some of the unit economics of Olo Pay and sort of what it looks like once it's blended into the model. Yeah. So, in terms of revenue contribution, when we entered the year, we were targeting $60 million of total revenue related to Pay. That was an increase of 100% year-over-year. Last year, we did $30 million on Pay. We've now raised that to mid $60 million based on the first half of the year performance and outperforming our expectations. And when you think about. You know, one of the questions we get is when the trade-off between Pay growth and gross margin, right? So as Pay continues to scale, gross margins on a blended basis have come down, which again, that is by design. We view that as a good thing. That means that the payments opportunity is scaling, and really what we're focused on is gross profit and how do we drive faster gross profit growth by virtue of the payments opportunity as well as other product modules. The thing about payments that we find really attractive is that as you continue to scale payments, at a certain point, it becomes very accretive from a gross profit and operating profit perspective. In other words, if you look at a pure software business that generates 80% gross margins and 20% operating margins, that means there's a big portion of that gross profit that gets reinvested in R&D, and you have to do that to remain competitive and innovate and so on. When it comes to payments companies, oftentimes you'll see much lower gross margins, call it 20%, but you'll see EBITDA margins that are in the 70%-80% as a percent of gross profit. Because all of the leverage when it comes to payments resides in R&D, and it's sort of the inverse versus the software business. So when we look at those different drivers, we try not to get too hung up on the dilution of gross margin as a result of pay, and we really look at it in terms of how do we drive more and more gross profit per unit? How does that then reaccelerate the business and add to operating profit? And Honeygrow is a great example of that. Sure. Yeah, go ahead. [audio distortion] Can you talk more about the onboarding timeline for both new customers and new products? Like you obviously said, if you're adding Peter, maybe, you know, is that, how, what's the timeline of rolling that out and adoption, as well as kind of new Dutch Bros, and how long do you see before you kind of scale this to more franchises that are starting to sample size. Yeah, so the question is around implementation timelines, either new business or kind of the upsell motion. If you asked me that question years ago, I would have said that it takes a couple quarters for us to stand up an implementation because there's you know, typically some integration work that is Olo dependent. Either it's a new POS integration, a new payment integration, and so on. That's no longer the case 'cause we've, over the years, we've built up a library of integrations from POS, payment, loyalty, and so on, where we're at a point now where we can move as fast as a brand wants to, wants to move. We have examples where very complex, hundreds of location brand concepts that we've gotten out in under 90 days, but we are always somewhat gated by the brand's, you know, ability or willingness to move at the pace we want to move. In the case of Dutch Bros, the plan is to roll out Dutch Bros in the back half of this year. There are some locations that have come on in the first half of the year. I think they have about 850 locations within their ecosystem, and the plan is to bring on those 850 in the back half of this year. [audio distortion] when you look through the history of payment businesses that are ramping, what's the scale that they need to get to that 14, 15, 16, or 15% EBITDA margins? If you kind of spell that out as, as being where you get scale. Yeah, that's a great question. I would say for Olo, that is more in the future as card present comes online just because of that, like, sheer magnitude of transactions. So I think that will take some time to get there. I do feel from an investment perspective, we're at a more stable level right now, R&D specific to the pay opportunity. There's work we need to do on the POS integration to enable the card-present processing, but once that investment cycle is done, I think we're at a point where R&D specific to pay becomes more stable, and then every incremental dollar that we process for payments is effectively accretive to the bottom line. I guess I'm just trying to get a sense for, just, again, not Olo-specific, history. Do you need to be $500 million to get to 15%, or do you just need a billion? Just like [audio distortion] I think that's tough to say because there's all sorts of factors unique. I would guess on some of those payment processors, whether or not they're expanding into new markets, where they are in product dev. It's hard to say. I'll just say, again, specific to Olo, when I think about the investment levels, specific to the pay business, we're getting to a point where those dollars on an absolute basis are pretty stable, such that all of the incremental revenue or gross profit that we can derive from the payments business can be more accretive to the bottom line. Any final questions? Okay, great. Well, thanks, everyone, for joining. Peter, thank you for joining us. Thanks for having me.