Olo Inc. (OLO) Earnings Call Transcript & Summary

Perfect. Good morning again. I'm Dennis Geiger, restaurants analyst at UBS. Pat Ennis, our payments analyst, is also up here on stage with me. We are pleased to welcome and excited to have with us on stage Noah Glass, Founder, CEO and Director of Olo; and Pete Benevides, CFO at Olo. Olo is a leading restaurant technology provider in the U.S. helping more than 750 brands and 86,000 restaurants, processing $29 billion of GMV and about $2.8 billion in gross payment volume in 2024. Olo offers a differentiated technology platform or platforms to help restaurants increase orders, streamline operations and improve guest experience. And with that, Noah and Peter, thanks so much for being here with us today.

Dennis and Pat, thank you for having us.

Really appreciate it. So maybe, Noah, we start out for investors, members of the audience and those listening on the webcast that are less familiar with the Olo story perhaps. If you could kind of give us a brief overview of the business and where you guys are now on your growth journey.

Yes. We talk about our mission at Olo as hospitality at scale for enterprise restaurants. And we deliver on that with an open and a modular platform that serves what we call emerging enterprise restaurants that's 5 to 99 locations, 100-plus unit restaurants, what we call enterprise and then even top 25 restaurant brands. When you think about what we offer, we have 3 different product suites, Order, Pay and Engage, and I'll get to each of those. But Order is really how we started almost 20 years ago now in 2005 here in New York City, enabling guests to order and pay and get food faster at coffee shops and restaurants. And then that grew over time to also include delivery and helping restaurant brands do first-party delivery and third-party delivery through aggregators and marketplaces. Those are the components really or the major components of the order platform. Pay is an embedded payments offering within the digital ordering platform. And then more recently, it's also payments for the in-restaurant experience. So with Pay, brands can enable their guests to have a delightful payment experience using things like Apple Pay and Google Pay for faster payments, higher authorization rate, lower fraud and just a better payment experience all around on the Olo platform. And we can get into why that's so important for also harnessing the power of guest data. And those 2 things, Order and Pay, together enable us to use all the guest data that we're able to see through the digital orders and through those payments to pull it into a guest data platform. That's kind of the foundation of the third part, which is our Engage suite. That enables a brand to collate all of the transactional data they have behind each guest and then really personalize the guest experience using our Engage suite to send communications to that guest and personalize their experience inside the 4 walls of the restaurant. So together, those 3 things, Order, Pay and Engage, are what we refer to as the Olo guest data flywheel. It's really all about harvesting guest data with the guest permission and using that to personalize the guest experience in an effort to drive profitable traffic. And that's very differentiated than driving traffic in an unprofitable way, which happens all around the industry. Just for a sense of scale, you already covered off on some of the metrics, but 750-plus restaurants that we work with, restaurant brands we work with, they represent about 86,000 individual restaurants, U.S. and Canada. We see about 95 million guests every year. And from a GMV perspective or the sales going through our platform, last year in 2024, we had $29 billion of gross merchandise volume. And just to put that in perspective, if Olo were a restaurant brand, $29 billion puts us now just ahead of Starbucks, I believe they're at around $28 billion, and behind only McDonald's as the largest platform out there. And I think that's just relevant to mention because it shows just how much is coming through our platform, how many -- all of those are digital transactions. So how current we are on what is new and fresh in the digital space and helping our brands to get further along their digital journey.

That's terrific. And maybe let's talk about, if we could, some of the benefits that you're offering your clients as it relates to growing sales profitably, as you mentioned, benefits to check growth, to customer satisfaction, to consumer satisfaction, all of that. If we could just kind of touch a lot around those benefits.

Yes. I think the biggest thing around digital ordering itself is enabling that guest to get into a state where their favorite orders are right there in their account and they can place an order, pay for that order, be done with that experience faster and know they're having a faster experience at the restaurant. So some of the things that I know, Dennis, we've talked about for over a decade in terms of the digital ordering value proposition on the guest side is getting into a faster pickup experience at the restaurant, a better delivery experience, if they're enjoying a meal at home. What that leads to is a higher average ticket we see than when they're ordering in restaurants and importantly, greater visit frequency. So that's taking the guesswork out of, what is this experience going to be like and knowing I can order and pay, I can schedule what time I want to collect the order. It will be ready and fresh at that time or delivered to me at that time. That's a great win-win for the guest and for the operator. We're very focused now with the Engage platform on, again, how do we use this data, the transactional data that we can see and tie back to that guest to increase their visit frequency, to maybe have them explore more parts of the menu they've never explored before by making data-driven recommendations to that guest. So if I know that you, Dennis, really like product A and other guests like you really also like product A and product B, we might want to recommend product B to you in the same way that we've all experienced with things like Netflix and Spotify and other collaborative filtering used in other industries. This is now possible to do in the restaurant industry really for the first time now that we can see every transaction tied back to a guest and use the power of a look-alike audience to make a data-driven recommendation to you. So things like that are ways in which we can help restaurant brands really personalize how they communicate and get guests not just coming back more frequently for the same thing, but trying more things on the menu and having new cravings of the restaurants that they love, really growing their lifetime value for the brand.

And those are great insights there. And I want to maybe just double-click on that customer engagement a bit more. We're asking a lot of the restaurants on stage this week about that. But given you've got, I think, better perspective than anyone, kind of what inning are we there with that customer engagement? You kind of mentioned it seems relatively early. And where that goes, I assume, for the restaurants, it's a home run. And for you guys, it's a home run. Just a little more on where we are, how that evolves, do you think, as it relates to that engagement, the customer data and what you can do with that.

Yes. Well, we're very early, I agree with the last presenters on that point, very early innings. As I like to say, we're just getting out of the dugout really. A couple of data points that I think are really important to share on this topic that illustrate the point that we're very early. Number one is that across the industry, 70% of first-time guests never return to a restaurant and that the top 30% of guests in restaurants typically drive about 60% of overall sales. Most restaurants don't know who those 30% are. And so they treat every guest the exact same way without any personalization, without making them feel special and like a regular. But they can't differentiate between first-time guests or their regulars. And most of those people who are in that 30% camp, they are not in a loyalty program. Some of them will be. But a lot of loyalty program members are just doing it for a discount at sign-up or some sort of offer. They're not really what we would consider the high-lifetime-value guests that drive a disproportionate percentage of the sales. So fundamentally, just restaurants being able to figure out, is this person a first-time guest or is this one of my regulars? And if they are one of my regulars, how do I speak to them differently based on what I know about them? That's a brand-new thought for this industry. And we can look at these little slivers, whether it's the digital ordering guests that are about 18% of total or loyalty, which is, at best, usually like 15% of total, but there is a massive blind spot of the other 80% or the other 85%. And now for the first time, brands are able to see every guest. And that's the big unlock of something that we just announced in a partnership for Olo Pay going from card-not-present, digital-only into card-present and all of those transactions that are happening inside the restaurant that have traditionally just been anonymous, nameless, faceless transactions.

That's terrific. How about if we shift just kind of over to the cost side of things? And I always feel like the cost savings potential, we're probably not seeing just yet. But how do you think about the cost savings to your corporate clients, to the brands, including any kind of potential labor savings maybe that you've observed thus far or maybe more so the potential labor savings if the brands kind of ultimately lean in on the headcount side of things, et cetera?

I think there are cost savings really at 2 levels. Let me address the sort of inside the 4 walls cost savings first. But then really importantly, I want to talk about the savings at the brand level. So within the 4 walls, clearly, like when the guest is doing more of the work, when they are placing the order, when they are paying for the order and you don't have to have a human taking their order, entering it in, perhaps making a manual order entry error, taking payment, making change, that clearly is a labor savings. What's been interesting to witness is what do brands do with that labor savings. And I think it was maybe best captured in an illustration of this. We had Danny Meyer, who's been a long-time Olo Board member and investor, as a speaker at our customer conference about a year ago. And he was talking about Shake Shack and how Shake Shack, in deploying kiosks, which are running through the Olo platform, was able to rethink labor. And what he said was, we used to have, pre-kiosks, 3 cashiers. And what we were able to do when we put kiosks in, we kept one cashier. We took another one of those cashiers. We put them out with the guests, sort of -- I think they call them hospitality coaches or hospitality champions or something like that. But they're out there teaching folks how to use the kiosks. And then the other role, we didn't need anymore. So there was in part, labor savings. And in part, we redeployed that labor for a higher purpose in delivering on Shake Shack's brand promise of hospitality. And I think the best brands are thinking about it in that way. There is clearly labor savings. It doesn't mean that you should just cut that all and take it to the bottom line. You can then repurpose some of those people to elevate the guest experience. The second thing I want to mention is there is absolutely labor savings for brands in getting off of a homegrown platform and moving on to a platform like Olo. And we've seen that play out. I think when we first met, I remember doing a road show with you and Keith Siegner, I think, in like 2014. And the topic of the day was Panera doing Panera 2.0, what should we think about this. And I remember at the time, it was $40 million investment and people were thinking, well, that's something you can justify. And my big point was that is the down payment. They're going to then every year have to maintain that platform. That is not cheap. That is an army of hundreds of engineers to go and do that. We at Olo spend $90 million a year on R&D, to illustrate that point. So this is something that you constantly have to keep secure, keep high performance, keep reliable, protect guest privacy as those laws change all over the place. That takes an army. So it really doesn't make a lot of sense for brands to build something and maintain it in-house. It's not just that CapEx. It's the ongoing OpEx that is just massive to support a program like this. We can do this for a fraction of the cost of what it takes brands to build and maintain themselves and with a lot of additional benefits of being a platform across 750 brands, being able to offer up benchmarking best practices that we've seen from around our customer base. And we're starting to do some really cool things that are differentiated structurally, meaning seeing Olo more as a 2-sided network between 86,000 restaurants and 95 million guests enables us to do some things differently that benefit both sides of that 2-sided network.

As it relates to that build versus buy discussion that, to your point, I remember was so compelling over 10 years ago now, have you seen a notable transition maybe from brands that thought, hey, we're going to do this ourselves, we get benefits, to the benefits that you've said and the savings and everything else?

Yes. Over a dozen cases of brands leaving homegrown platforms and coming on to Olo since our IPO. We're coming up on the 4-year anniversary of that next Monday. Brands like TGI Fridays, brands like Zaxbys, brands like Ruby Tuesday, CKE, many, many more. But making this transition off of an expensive homegrown tech stack that feels dated after some time and just needs a fresh coat of paint, but really needs more than that, needs a whole rethink and rebuild over to the Olo platform. And then again, redeploying their tech teams, not just taking all of it to the bottom line, but saying, what are the things we can do to up-level our brand differentiation? Can we build certain components on top of Olo that really make our brand and our digital experience unique in the way that our brand is? I think that's what the best are doing. So that old binary of buy versus build is kind of almost a false choice at this point. It's really do both, buy into the Olo platform, work with Olo and our library of 400 integrated technology partners and then build something differentiated with all of those LEGO pieces.

Terrific. How about -- as we look ahead and we think about the outlook for the platform's utilization or sort of customer adoption over the coming years, any thoughts maybe on, for your own business and even more broadly, where mobile digital adoption are headed over the coming years and longer term?

Yes. I think about the end market of guests using digital. I remember coming into COVID, it was around 8% of overall transactions in the industry were digital transactions, by the way, primarily takeout and not delivery at that point. Takeout has always been the lion's share of digital and remains that way. And then in COVID, we rocketed up for obvious reasons to 16%. And I think everybody after that thought, okay, now it's going to recede back. It's going to be something around 10%. And that didn't happen. It stayed at 15%, 16% for a number of quarters. And then we started to report on this, I think, 2 quarters ago that we are now at 18% digital as an industry. I think inevitably, as guests seek out digital experiences, we're going to become more and more digital over time, and that 18% will grow to 20% and then some. And I should also say mileage varies. There are some brands that are doing 75% of their overall sales through digital channels, especially with things like kiosks inside the 4 walls or, you heard it with the last speakers, digital in the drive-through is another big unlock. So I think digital from a guest -- from a transaction mix percentage, is going to increase dramatically. That's sort of round 1. Round 2 is the great thing about digital is that it has this incredible coproduct, which is transaction data tied back to the guest. So knowing not just that the guest has ordered this item, but how do they customize that order. How do they remove items, add items, substitute things on that standard preparation of the dish, all of those are a packet of clues about who that guest is. Do they reorder it the same way? Or do they change something? That might be something you can infer -- do they like it that way? Or do they not like it that way? All of that transactional data is an incredible coproduct. Being able to tie it back to a guest and being able to then get to a personalized approach to communications and guest experience is really the next big wave that has us so excited now 20 years into the journey for what's ahead and what we can unlock for our customers. So I think that's got a huge runway ahead of it. It will change the industry itself.

It is interesting when you hear some of the large brands, even some that you're working with, that talk about 100%. That's our target over time, right? We're nowhere near that yet, but just to where that can go. One or 2 more for me, and I want to pass it over to Pat. Maybe let's touch on the potential as it relates to AI-powered technology and what that can do for your business, for the industry, but for your business as well specifically.

Yes. We use AI. We have used AI for many years now, and we use it across every product suite of ours. So in the order suite, some of the obvious things like voice AI ordering, whether that's a phone call or through the drive-through, we do a lot of that with partners today. Things like data-driven recommendations that I mentioned, looking at what you've ordered and what other guests have ordered who are like you to determine what to recommend to you, something that we call smart cross-sells instead of just saying in a sort of generic way, do you want fries and a drink with that? Knowing if we should offer you something else that better correlates with what you're ordering is something that we released last year. We've seen a radical improvement in basket size and somebody saying, yes, I do want that, based on a data-driven recommendation. In our Pay suite, we use AI extensively, and that's why we outperform any other payment solution in the industry from an authorization rate perspective, from a fraud mitigation perspective. The numbers really speak for themselves, but it's based on having this vertical focus on being a great payment solution for the restaurant vertical and a huge database of guests. And then the Engage suite, on a marketing front, being able to do all of that personalization and knowing what the guest wants to hear about, when they want to hear about something and through what medium we should communicate with them, all of that is driven by AI and machine learning. And then there's a lot of sort of like boring stuff that we do with AI. But that is actually like really exciting to us, like making sure the kitchen is running at peak productivity and as profitably as possible, as we say, as productive as possible, as profitable as possible by reading from what's actually happening in real time in the kitchen to determine, how much capacity do they have? Can they take another order for this time slot? Should we tell the guest they can't order for this time slot because we're at max capacity and then push them out into a shoulder time, another time slot and make that available to them? What's the expectation that we're setting for when the order will be ready for collection? Because again, the goal, as it always has been, is the guest arrives and the food is ready and fresh right at that moment. And that's increasingly important when you get into delivery and delivery drivers for whom time is money and they want to make sure that there's no kind of time when they're just sort of waiting there at the restaurant and also they're picking the food up at that peak quality. So AI is used extensively through our platform, and it will continue to be a huge driving force behind the data asset that we've created with 95 million guests with billions of transactions connected back to them. Letting AI loose on that for the brand's benefit and for the guests' benefit is a really exciting next chapter.

Yes. That's great. Last one for me for the moment. Given your perspective, the data that you've got, et cetera, curious to share any thoughts you have on the restaurant industry broadly in recent quarters, consumer behaviors, anything you've kind of picked up there. I feel like everything has been very dynamic, and a lot of the larger brands themselves are trying to figure this out. But if you've got any thoughts, observations to share on the restaurant consumer and demand for the industry right now.

Yes. I think we are in a tough time for the consumer. That's not new. It's been happening for a number of quarters. But what is new, and someone who's been around for 20 years watching this industry, you see these kind of waves where you have input costs increase, and so restaurants are challenged. They take price, they increase their prices. And at some point, the laws of supply and demand kick in and guests just say, this is too expensive. I can't come as much. And so what happens is restaurants are desperate to drive traffic. They do short-term things, value menus, bombing price, bundles, meal deals. And it's short-term helpful. It gets traffic going. It helps them to hit their numbers for the quarter. It is long-term harmful for the brand because it squeezes even more franchisee profitability and you get store closures and you get bankruptcies. And this is the break glass in case of emergency playbook that all of these brands who do value meals and discounting always do. We saw it during the Great Recession. You can trace the sort of prices go up, take price, traffic drops, do discounts, 1, 2, 3, 4 playbook. And there has to be a better way for this industry. And our perspective at Olo is now there is. With personalization, with understanding the guest and all of these transactional data points that we have about them and the personalization you can then unlock with AI and machine learning, you don't have to just drive traffic at the expense of profitability, you can now drive profitable traffic. And that's the message that we are sharing with our customers and the industry. And we have great examples. One that's top of mind that we just spoke about in our last earnings call a couple of weeks back, the brand California Fish Grill, fast-casual brand, they started to work with us on the Engage suite. They have a very high digital mix because they have kiosks in the restaurant. I think they're about 70% digital. But they deployed our Engage suite wanting to drive profitable traffic and more hospitable experiences for their guests. And over a 6-month period, they saw a 41% increase in the database of guests that they had in their guest data platform, a 21% increase in the number of guests who are contactable so they could actively market to them. And then based on running those marketing campaigns through our Engage platform, knowing the right message, the right time to send the message and the right medium to send the message for each individual guest, really segment of one kind of marketing, they were able to drive $7 million of attributed sales to their stores, and that was not through discounting. It wasn't through value menus or meal deals. This was profitable traffic, and they did it through personalization. And so stories like that -- we have our customer conference this year coming up next week. These are the stories that we're elevating and getting brands like that to get up and tell their story in front of their peers in a way that I think is going to educate restaurants that you don't have to bomb price and you don't have to do something that is short-term helpful, long-term harmful, eroding the brand's pricing proposition to the guest, challenging franchisee economics, et cetera. There is a better way.

Terrific. That's great. Great anecdotes. I'm going to send it over to Pat. I know he's got a bunch.

Yes. I appreciate it, Dennis. So we touched a little bit on this earlier. But for the new brands you've added this year, could you maybe provide some context around kind of who the existing digital solution was you are most frequently displacing, if any at all? I know we touched a little bit on kind of the in-house solution some of these brands may have already, but outside of that.

Yes. I think this year, in particular, well, a lot of our success is not just with new logos, but also selling additional capabilities into existing customers. In fact, if you look at sort of the scale of our opportunity, that is the bigger unlock in scale is selling more of our modules into existing customers. I think we shared the average restaurant location on our platform uses 3.7 modules. We now have 16 modules overall. So we're not even at 25% penetrated. In new logos, oftentimes, what we're landing with is a single module and something that's like, we want to add delivery to our in-house takeout platform. You can use the Olo Dispatch module as a service to add delivery so that your guests cannot just order takeout, but also say, I want the order delivered through your own direct channel. That's one way. Enabling marketplaces through our Rails module, it's another way that we can land with a brand to expand what they're already doing. We do have great examples like Jack in the Box, we talked about that on our call the other week, where they started with that Dispatch product. They started just augmenting what they had already built with direct delivery through Dispatch. Then they started to use Olo for their ordering platform. So we replaced their homegrown platform. And then this past quarter, they added marketplace enablement for the marketplaces to be able to get the menu from us and then send orders to our platform and directly into the store. So that's a good example of a homegrown over to Olo transfer. We do have some subscale competitors. We're at 86,000 locations. There's nobody I can think of that we directly compete with that has more than 5,000, maybe even 2,000. But there are some that we compete against. I'll name like Lunchbox as an example of that. And recently, we announced -- I don't think it was last quarter. Well, last quarter, we announced Walk-Ons, which is a competitive win from Lunchbox, and then also Papa Gino's, which is a personal favorite of Peter and mine, Papa Gino's and D'Angelo, both within Authentic Brands Group in the Boston area. We both grew up in the New England area, so that's one that's very familiar. But that was also a win from Lunchbox.

Perfect. And I guess staying on the kind of the competitive landscape but moving a little bit more towards the enterprise TAM. How do you guys define enterprise? And what would you describe as kind of the TAM within kind of the broader restaurant industry?

Peter, do you want to speak?

Happy to take that one. So I think there's a couple of ways to think about it. So from -- and how you think about building the model, fundamentally, it's locations and ARPU, so adding more locations to the platform and increasing the amount of revenue we earn per location. So you think about the TAM from a location standpoint, there are about 300,000 U.S. enterprise restaurant locations. That's our focus currently. We have 86,000 that are on the platform today. So call it a 4x opportunity to expand from where we are today. Then you have the module adoption and module growth opportunity. So as Noah mentioned, 16 product modules to sell today across the 3 suites. On average, brands are using 3.7 modules per location. And that's been steadily increasing as you go back over prior years every year as brands adopt more and more of the platform. I think the one item that has kind of an outsized impact around how we grow ARPU is Olo Pay. So we mentioned earlier from a gross processing volume perspective, this past year, we processed about $2.8 billion of GPV. That's against $29 billion of GMV, so about 10% penetrated within the installed base. And if you think about that $29 billion of GMV, if that represents 18% of our customers' share of business, there's over $160 billion of GMV being processed just within the installed base that we work with today. And as card-present comes online, that really is the immediate TAM, if you will, that is addressable via the payment opportunity. And having only processed $2.8 billion of GPV this year, that's, call it, 2% of the opportunity just within the installed base. So we've had success across all segments of the enterprise market that we serve. We work with 5 of the top 25 brands today. Obviously, we're most well known for the kind of traditional enterprise segment, so call it the 100 to 2,000 location per brand segment. And then over the years, as we've built out the open platform with 400-plus integrated partners, it's allowed us to service the emerging enterprise segment of the market more efficiently from a CAC perspective. So now we're working with over 14,000 in that 5 to 99 cohort of locations per brand. So a lot of opportunity ahead on the location front and, of course, on the ARPU side as well.

Pat, if I may, I know you're the payments guy on the stage. Just to sort of double down on what Peter just said, Olo Pay's penetration, I think that's part of the really exciting story, just how big that SAM is. $161 billion is something like 15% of overall U.S. restaurant sales. So it's a lot that's going through our platform that's now addressable. The other impressive thing is the journey that we've been on with Olo Pay, a product that we launched 2 years ago with people saying, why is anybody going to want this? What's differentiated about this? This is going to be a dog. We said, well, there's a real opportunity here because our customers are asking for it because they're not happy with the current offerings on the market, the horizontal payment platforms, and they need something purpose-built for them. And so we went from 2022 initial launch of Olo Pay, $250 million processed. 2023, we did $1 billion in processing, so 4x growth. Last year, we did $2.8 billion. So the growth has been phenomenal, over 10x over the first 2 years. And now we've just unlocked this massive SAM of $161 billion. And it's in line with -- this is not just a better payments offering. It is that, I would argue. But it's also about this is an unlock to pull guest data into your guest data platform that eliminates an 85% blind spot for you. That's why restaurants are so excited about this move from card-not-present only to Olo Pay is now card-not-present and card-present and why we're so excited about the opportunity from a business perspective, from our revenue perspective. But it aligns with being on the restaurant side and helping them to unlock a blind spot, run their businesses differently as a result and run their businesses better. So we feel like the wind is definitely at our back with what we've built with Olo Pay, the success that we've had, how that set the table for what's ahead and the massive opportunity that we have just unlocked.

Definitely. That's some good context. And sticking with Olo Pay, I definitely want to touch on kind of the omnichannel benefits you get with the card-present offering. But first, just Stripe is an important partners of yours helping to power the payments offering. Can you maybe talk about some of the advantages Stripe offered when selecting an integrated payments partner and maybe some of the embedded financial services Stripe offers that Olo can distribute to their customers or your customers?

Yes. So Stripe has been a wonderful partner to date, as you mentioned there, historically supporting us in the card-not-present use case and most recently via the announcement with FreedomPay, helping us on the card-present use case as well. I think one of the benefits that we've seen in working with Stripe is obviously, they have their network of customers that they serve, which doesn't always overlap with the network of customers that we have. So one of the things we learned very early on in terms of the value prop of adopting Olo Pay were things like fraud mitigation, charge-backs and authorization rates. And how you improve those metrics is through network and scale. And what we had done was we had -- through the network that Stripe has and Stripe Radar coupling with the network of transactions that we have, we have an incredible scale to then look across all of those transactions to have better data points on whether or not that transaction should be authorized, is it fraudulent, what is the likelihood of charge-backs, et cetera. And as a result of that, when you look at things like authorization rates and fraud, et cetera, we are leaps and bounds above kind of the traditional processors that we compete against. So that's one example where the -- we've seen a lot of benefits in partnering with Stripe.

Definitely. And I mean, you touched on this a little bit, but scale is pretty important in the payments industry and probably part of kind of some of the gross margin expansion you're expecting going forward. But could you maybe just contextualize some of the unit economic benefits you may be able to achieve with processors and maybe networks as the payments volume and GPV scales forward?

Yes. So if you kind of look back over time, we've -- and this is purely card-not-present, we've steadily increased our gross margin over time, and that's really being driven by that scale factor. So with greater scale comes better pricing for Olo, and that's obviously key to increasing gross margins. How we then unlock a next kind of leg of scale and further margin improvement is through the emergence of card-present just because of the sheer magnitude of transactions that happen in a nondigital setting. So as card-present comes online, we're estimating that, that will be immediately margin accretive for the payments opportunity. And then, of course, as we continue to scale that, we'll see more and more improvement over time. The other thing that is interesting about card-present is oftentimes the card mix lends itself to better economics as well. So where you're pricing deals that may be 1% of the transaction, if interchange can come down because there's more debit card usage, as an example, on premise, that can help to increase overall margins as well. So this is something we've been very focused on, in particular, given that blended gross margins have come down on the platform. Gross profit dollars, gross profit growth has become more relevant. And as a result of that, we're hyper focused on gross profit dollars and gross profit growth.

Absolutely. And for the card-present aspect, you recently announced the FreedomPay integration. Could you maybe touch on some of the benefits of that? And is Olo focused now -- gathering more data from consumer transactions to better build a complete view of your customers' guests? Is that the main benefit? Is there any direct monetization we should think about?

Yes. So FreedomPay was the continuation of our card-present announcement. So we started about a year ago, we stood on stage at our customer conference, Beyond4, and we talked about some direct-to-POS relationships, a flagship partner that we announced then and then a couple of weeks later, 2 more. So Qu was the initial partner POS player in the space, then NCR and then TRAY. And we've -- in Q3 on our earnings call, we talked about 5 pilots between enterprise and emerging enterprise with those POS partners. That was exciting if you were a restaurant customer of Olo's and used NCR or Qu or TRAY, and that's a meaningful, call it, 30% of the overall base. But the other 70% were like, when are you going to get to my POS? The nice thing about FreedomPay is that they have done thousands of POS and payment processor integrations. And so when Stripe and FreedomPay announced their relationship, that was the kind of jumping off point for us to then say, hey, let's make Olo the first big project that you all work together on to unlock Olo Pay card-present through Stripe, which, as Peter said, had been only card-not-present, into the broad base of Olo customers. And that's exactly what we've done with the ability to process those transactions in store, whether that's counter service, table service or drive-through or kiosk, and similar to the direct-to-POS integrations, be able to pull the transaction data, tie it back to the guest using payment account reference to identify that guest and house that in our guest data platform. And that's the big unlock for the restaurant, and it's a huge differentiator. Not just a secure and great payments experience for the operator and a fast experience for the guest, it is those things, but -- and the transactional data gets tied back into the guest data platform.

The 2 things I would add there is from a cost perspective, we're indifferent between the direct-to-POS or the FreedomPay opportunity, which I think is great because that means we could just meet our customers where they are and we don't have to kind of push one initiative over the other. The other thing just on the kind of data value prop is while the ability to gather data from the POS and the transaction is important, the real differentiation is all of the billions of transactions that we've accumulated over the 20-plus years of operating or nearly 20 years of operating that allow us to enrich that data at levels that others cannot, right? So it's really the pairing of those 2 datasets that creates a level of differentiation that others can't compete.

Absolutely. That seems like it will be a pretty important partnership going forward. Touching on some of the gross profit growth, gross margin and then also getting down to kind of operating margins. You recently introduced the Rule of 40 framework for gross profit growth plus non-GAAP operating income margin as a percent of gross profit with expectations to meet or exceed the Rule of 40 by Q4 '25 versus roughly 36% today. Could you walk us through maybe what that means for gross profit growth versus operating margin expansion in '25?

Yes. So what we've shared on a full year basis from a gross profit growth perspective is that this year, we will reaccelerate gross profit growth year-on-year full year. How that will sort of trend as we move throughout the year is essentially second quarter is the trough and then we start to reaccelerate in the back half of the year. At the same time, we're expanding margins all along the way. And the reason for that is the -- really, it's the high leverage that we see when you're pairing together software and payments and selling payments into that existing relationship. So the actual acquisition costs are relatively low and then payment scales really well over time because the cost to process that incremental transaction is essentially nonexistent, right? So once you've done the work from an R&D perspective to enable card-not-present and card-present processing, there's always going to be some investment to maintain and sustain the platform. But at a certain point, you start to get a point where the rate of growth on a dollar basis from gross profit significantly outpaces the reinvestment rate within R&D. And we're starting to see that play out as Pay has continued to scale. So when we look ahead, we see a path toward gross profit Rule of 40 later on this year. And we're able to do that in a very kind of natural rhythm. It's not being done in a way where we're sacrificing innovation or putting undue strain on the organization. It is just naturally happening as a result of the factors that I mentioned there. And we do think gross profit growth is the more relevant metric to kind of assess business health and really kind of future cash flow generation. As kind of Pay mix has increased and margins come down, we look at gross profit growth as kind of the true measure.

Absolutely. Appreciate that context. I'll pivot back over to Dennis to see if -- any questions we want to wrap up with.

Great. Yes. In the couple of minutes we have -- Peter, it's helpful on some of the margin color there. Maybe if there's anything else on 1Q '25 guidance expectations that you recently outlined, key assumptions embedded in those expectations.

Yes. So a couple of things to mention. So we reported at this point a couple of weeks ago now. And from a full year revenue perspective, the range is $333 million to $336 million of total revenue. That puts year-on-year growth around 15% to 17%. As I mentioned earlier, the commentary that we've shared from a gross margin perspective is blended gross margins declining about 250 basis points year-on-year. And again, that's because of the Pay scaling into the business. When you do the math, that then results in gross profit increasing year-on-year. Pay's contribution overall is about $110 million of the, call it, $333 million to $336 million, and that's up from just over $70 million this past year. So again, another great year of growth ahead. And then meanwhile, when you look at OpEx, OpEx full year growing kind of in the mid-single-digit range. So that stability within, in particular, sales and marketing and R&D is what's allowing us to expand margins and get to that gross profit Rule of 40 in Q4.

That's great. Maybe if we look longer term, even if at a high level, I would say, following impressive growth rates on key metrics over the last many years, how do you kind of frame up the longer-term growth opportunity ahead, either -- specifically high level?

Yes. I mean I think the mix that we're -- when you think about the mix of gross profit Rule of 40 as we exit the year, I would expect that mix kind of in that mid-teen to low teen percent with gross -- NGOI as a percent of gross profit being in that mid-20% range. We feel like that's a comfortable place to operate. Now of course, that could ebb and flow quarter-to-quarter. But when we think about the gross profit Rule of 40 composition, that feels like a natural mix.

Terrific. Well, we are basically out of time. But Noah, Peter, great discussion, great insights. Really appreciate it as always. So thanks so much for your time.

Thank you, Dennis. Thanks, Pat.

Thanks for having us.

Thanks, guys.

Thank you.