A nice little step too.
I know. I, before, was taking people over the rocks before I realized that there were steps. Did some rock climbing.
Oh, these chairs are really oddly deep, but not deep enough. I don't know, whatever.
Yeah. For short people, it's been a struggle, let me tell you. Hello, everyone. How's it going? I hope everyone's enjoying the third day of the UBS Tech Conference. My name's Taylor McGinnis, and I head up the SMIDCAP Application SaaS space here. And in this session, we have Twilio. And I'm very excited because we have Andy, who's the VP of Product for Video and Voice. And just given how Voice has become such a focal point in a lot of the emergence of AI with Twilio and the broader CPaaS category, I think this is going to be a really good conversation. And then we also have Rodney, who's Head of Investor Relations. So thank you guys both for joining today.
Of course.
Thanks for having us.
Awesome. Maybe to start, Andy, if you could just give a brief background on yourself and your role at Twilio, and then we can go from there.
Sure. Sounds good. Thanks for having me. So I lead product for Voice and Video at Twilio. That's all the product management, research, and development for what we're building at the company. Teams spread across the globe that build all these technologies out from peer connectivity across the globe to all the fun AI pieces that we're going to be talking about. I was a longtime customer of Twilio, off and on with both public companies and smaller companies before joining about four and a half years ago as well.
Perfect. And if we think about Voice at Twilio, so Voice isn't new, right? I think the Voice API was first launched maybe 15 years or so ago. So when we think about over the last year plus and the greater emphasis that Twilio has placed on Voice, what's driving that? Is that really a function of the emergence of AI and some of the opportunities there, or is there other market demand trends that are pushing that?
Sure. Yeah. So this was the original product that the company was founded upon, where there was just an emerging need over time that the shift in all things telecom, where to be able to build a Voice application inside a business for simple calling required multiple, multiple steps and partnerships with carriers and everything else like that. So to build one API that's an abstraction over all of those carriers, and now that's full global, we were built for this moment, I think. So I'm fortunate in that standpoint to see all the growth that's happened over the years of the Voice business, call it incremental, where you're seeing traditional voice conversations and inbound contact center type applications or outbound sales service marketing. The large, vast majority of our customers that are serving B2C type audiences as well.
What you've seen over the last couple of years is just an inflection point of growth because of AI. You've seen advancements in speech recognition AI models and generative AI voices that sound incredibly natural models as well. Combine that with the biggest one, which is the LLM explosion too. When you bring those three ingredients together, you have all of this AI that I'd call it kind of sitting in the cloud. Regardless of the types of very sophisticated models that might be kind of solutions in search of a problem, all of those use cases that Twilio has been serving over the years are very real problems to be solved with Voice AI.
And so I think that's where we're starting to see this growth of the movement of all these AI models kind of coming down from the cloud to all the last mile where every local phone number for small and medium-sized businesses and enterprises where actual conversations are happening between consumers and businesses. That's where we sit. That's where the Programmable Voice product sits. And it interfaces with AI extremely well to deploy these use cases. And so it's kind of been a long time coming. It's not that overnight success that takes these years because it also took all of this time to build up this massive global infrastructure to be able to do it. Because enterprises and ISVs that want to scale rapidly, they want to be able to tap into this simply and reach global audiences across multiple languages and coverage and have the reliability to serve their growing needs.
Perfect. Yeah. So when Khozema talks about the renaissance that Voice is undertaking, it sounds like a lot of that is AI-driven. So in terms of how Twilio is trying to position itself in the voice market, I would love if you could elaborate there. So how is Twilio evolving the product, the go-to-market strategy to capitalize on a lot of these emerging opportunities?
Sure. So I think there's basic voice traditional PSTN that happens across telco globally over time. That raw connectivity doesn't have all the functionality that we have built over on top of that. So if you think about what an enterprise might want to do with a call, you might want to record it, transcribe it, do conference, route it in different places, obviously put then a Voice AI agent on that as well, apply intelligence to all those conversations, understand what was said, sentiment, keywords, did consumers mention competitors, were they going to churn from your product and you need to create a campaign to recoup that business. All of those types of things are at the programmability layer that we've invested so much into. So I think that's one big differentiating factor when we think about just pure voices make the call happen. That's standard.
We've built all of the features and functionality on top of that and then continue to build these abstraction layers like Conversation Relay that handles all of that aspect of the back and forth between a consumer and an AI agent, Conversational Intelligence that then does the analysis of what was just said and what happened, and then give those to our customers as infrastructure plays so ISVs can build businesses and then say, "We can take an AI to the go-to-market piece that I can now go out as an ISV that I specialize in salons and spas," and I can go to every single salon and spa out there and say, "Now you can build your own Voice AI agent to handle all the appointment scheduling and everything you need for your business or in food service or retail or automotive or anything else like that," so I think that's the differentiator is the features and functionality that bring pure connectivity to interface with the AI.
And then from a go-to-market standpoint, we've got ISVs that are now taking that technology out to all small and medium-sized businesses and then as well as enterprises that trust us for the scale and reliability and everything else that we've brought to the call so they can start to then deploy those same type of capabilities out in their customer service departments or sales and service departments. And we've made a lot of investments too in the self-service side of things. I mean, massive asset. Like I said, I was a customer in a variety of businesses. Twilio was one of the first go-to companies that we needed as infrastructure.
And to have that as very simple APIs that can be embedded into your application is still bread and butter for us in terms of especially capturing these new innovative Voice AI startups that are coming about. They pop in on a Saturday, and by Monday, they're up and running and scaling and watching that growth. So there's a big go-to-market emphasis in terms of getting our enterprise customers enabled, our ISVs to go after small and medium-sized businesses. And those developers are key because they're the ones that are seeing how they can apply these AI models into the Voice AI space.
Yeah. What are the most popular use cases today and how has that evolved? Because a lot of the examples that you gave earlier sounded like traditional contact center use cases. So is that really what Twilio is coming in and displacing with some of the Voice solutions that you're creating, or is there a whole new set of greenfield opportunities that haven't been addressed?
Yeah. I think for sure there is a massive shift in terms of all the OPEX in terms of contact centers that handle inbound calls globally and then Voice AI tech on that side. And I think as you've seen kind of the shift of dollars, we're sitting there and helping customers do that for sure. And a lot of those use cases, I think about it as kind of a pyramid of complexity. On the bottom rung of the pyramid, you have tons and tons and tons of calls, but pretty rote, mundane, repetitive type reasons that a consumer might call a business in an inbound call standpoint in a contact center, for example. And you want to be able to offer customers the ability to start automating those in a really good fashion. I forgot my password. I can't log into the website.
What's my package status? Those types of things. Or I want to rebook my doctor's appointment, and I don't want to have to go to your website or send an email. I just want to call while I'm in the car and rebook my doctor's appointment, those types of things. Then as you start to work your way up that kind of pyramid of complexity, there might be fewer calls, but higher complexity calls. So those traditional contact center agents, they might have a couple of screens in front of them and two or three different software systems that they might have to interface with. What we're seeing in terms of growth is our customers really going after that first rung in those use cases, heavy inbound for sure. But we also see outbound too. One other I use a lot is that healthcare appointment reminder.
Super expensive for all of us to miss a doctor's appointment. And they want to trigger an outbound call. We want to make sure that call is branded for the customer so you know it's at your doctor's office. You can reschedule because those are pretty rote, and you can do those over and over again, but they're expensive. And so customers want to go after those and then move their way up the stack, integrate with more systems, personalize with more data until they can get to a point where a majority of those communications are powered by AI.
Perfect. And I'd love for you to talk about how the competitive landscape is evolving here. So if I think about traditional Voice use cases, I think about the contact center players. I think Unified Communications, other CPaaS players like Bandwidth, right? Now with the emergence of AI, you have a whole host of AI startups that you mentioned. You also have some of the cloud infrastructure players getting into this to some extent. So when your customers are evaluating you for AI Voice agents or even non-Voice workloads, who do you typically go head to head with, and how is the competitive landscape evolving?
Yeah. I think for those AI startups that are coming in, I think there's a good reason that we've seen a lot of them come first to Twilio. I talked about that developer reputation for sure of just, "I know I can come in. They've got great APIs. It works. It's scalable. I can get global coverage. I can scale up." And so I think that differentiation of why we become that choice de facto for builders and developers, which could be an enterprise developer, a large enterprise, not just Voice AI startup, to say, "This is the one I trust and can grow." And then it relates to some of the larger clouds and different players. Some of them, especially in the Voice category, have focused largely on just pure Voice connectivity.
That lower layer that I talk about of just pure connectivity, make the call happen, which is largely a SIP trunking type product, which massive, massive volume, but the features and functionality aren't there to do all the programmability stuff that I was talking about of interfacing with LLMs and recording and transcribing and conferencing the call and routing it, doing secure payments across it and things like that. So you as a customer then have to build all that stuff or buy Programmable Voice from Twilio in that standpoint. And that's a large business, but gross margin profiles are different, and it's easier switching costs. And so that's why we invest to make these things work better together. So then leads into kind of that last piece of differentiation.
Once you look at Twilio Voice as your choice because it's modular, it's programmable, it'll interface no matter what LLM comes and goes, you can still plug that in, then there's complementary work with the other channels that we have too. So in many of these Voice AI cases, you might want a text for a DocuSign or a text to a verification for an OTP to verify that user to know that you've authenticated with your bank or before you get a package shipment change or anything else like that, or you want an email receipt right there to know what the Voice AI agent just accomplished and you have that. Well, then that introduces Twilio as, "Well, we have all those channels too." You've known us for those. They're trusted more and more.
They'll work more seamlessly and integrate together, which is also a differentiator, not in the channel itself, but in the idea that you can orchestrate across multiple channels. Because we think about, it's not just Voice AI, it's conversational AI. That could happen anytime. You could start as a web chat, switch to a voice call, maintain, remember who you are, switch back to messaging or vice versa. And so that's when we think about the multiple channels that work better.
Yeah. Thanks for explaining that because I think that's really interesting, that edge in connectivity, right? And having more of that out of the box as being a differentiator, I think, is really interesting. So I appreciate you explaining that. I think one thing that's really intrigued me about the emergence of AI and Twilio's focus on Voice is that Voice is still between 10%- 15% of revenue, and Twilio, the big lion's share of Twilio's business, has been on the SMS side. So I would have initially thought that that would have been the area of a focus when AI started to emerge as a bigger theme. So what is it about Voice? Is it that the Voice channel is very natural as you think about AI agents, SMS? It's still a little bit more further out. What about the focus on Voice is so interesting to you guys?
Yeah. It's great, healthy competition with my peers that lead the products. I think I talked about these emerging technologies that kind of all hit, really hit a couple of years ago, and now are really working better together in terms of speech recognition and voices and LLMs coming together. That piece came together at the same time. You can even see it from the native applications, whether it's Gemini or OpenAI, that they all want to be your AI agent, very voice-driven. Even the UI is really encouraging voice because it is the most natural, fastest way for us to communicate. So I think that's one reason is just we're training a generation of consumers to be able to just talk at their phone and yell at their phone.
And why would that be any different to say, "Change my doctor's appointment," versus ask a question to ChatGPT about the world? So I think that's one trend that we're seeing. And I'm pretty bullish on long-term just overall voice as a modality in communicating. I think also because it's expensive for businesses to handle all these customer and consumer interactions via the voice channel, whether it's outsourced for a BPO or internal employees that are doing this, back to that pyramid to power a big workforce for all of those types of repetitive calls that might come in, naturally, you're going to go to a place where you're not going to change the consumer behavior in many of these cases.
The verticals like healthcare, retail, financial services, real estate, those types of places where a voice call still is the thing, calling your local plumber or calling these other places where a voice call still is the thing. And it's expensive. That's a natural place where customers have gravitated to say, "This is a place where we want to deploy what I'd call conversational AI." It's fast. It's easy. But there's nothing prohibiting you from going back to a web chat or a text-based chat. The way we think about it is anything could be conversational at any point in time in a customer's journey with the business. So traditionally, you target them with Facebook ads and Google ads, and they land on your website. Why wouldn't they be able to converse with your business about your product offerings and catalogs and services and return something or do anything else via Voice modality than anything else? And so I think that's an interesting trend that we're seeing that's helping the Voice channel grow overall.
Perfect. And I think one of the key questions that we get from investors is, "Are enterprises adopting this today?" I know Rodney gets that question all day long, "What are the proof points? Do you have Fortune 500 companies that are using or testing Twilio's Voice AI agents today?" So any color, I guess, that you can give us there when you think about the different segments, whether that be AI-native companies using Twilio, SMBs, mid-markets, enterprises, where are we on the adoption curve? And if it's still early, maybe you could just speak to the pipeline and what you're seeing?
Yeah. I do think we're still in the early innings, honestly. We're seeing these, obviously, and we've quoted some of these numbers of some of the segment of native AI Voice startups that are seeing these use cases, whether it be changing some of the traditional use cases and going after it into a vertical, very vertical specific, and growing rapidly that way. And then as it relates to then the enterprises, so yes, we are seeing enterprises definitely in the testing phase for sure, where they're looking at it and saying, "Maybe I get 1,000 calls an hour on a given topic. How do I then take this use case for this specific call, outbound or inbound? If it's a lead qualification, take it outbound." We always ask these 10 qualifying questions. How do I make sure that then I can deploy a Voice AI agent there?
I've got Twilio for the global connectivity. It's trusted. They can help me brand that call so the consumer knows, check there. And then how do I train maybe my internal data in a model, plug that into Conversation Relay and Conversational Intelligence, deploy that as a percentage of traffic to say, "Okay, now I test it, evaluate it, feel better, then start to ramp up." Then maybe personalize it more with some data that's internal to my data warehouse so that AI agent knows who that consumer is. They know their purchase history. They know their loyalty status. And then start to ramp up and then move to another percentage of traffic. So I think it's not the all-or-nothing stage of just deploy an OpenAI model to every single call that would ever happen. That's not going to go well. It's a surgical approach.
And so I think that's what we're seeing in enterprises. Interestingly enough, because I think the pain threshold is high and it's expensive, some of the earliest companies that are ramping up into production, a couple of our public case studies that we've done are in these regulated verticals, in healthcare. Why is my healthcare bill so expensive? When's my next appointment? Types of businesses that are handling credit union. So in those regulated type verticals, because of that kind of pain, it is expensive. You have that human power. And so customers are starting to weigh that ROI and starting to deploy.
Rodney, feel free to chime in with this question because we're going to get into some of the financials.
Sure.
But so as I mentioned earlier, Voice today is anywhere from low to mid-teens in terms of revenue contribution to Twilio. You guys talked last quarter how that accelerated to the mid-teens, which I think you said was the highest growth rate that you've seen in three years.
Yep.
It sounds like Voice is still a very early contributor. Voice AI, sorry, is still a very early contributor to that. But could you speak to that? What is driving that reacceleration, if not AI? And as you think two, three years from now, what would be your ambitions in terms of where Voice could get as a percentage of the business and how big of a role AI plays into that?
Yeah. So Voice is 12% of revenue in 2024. So you're spot on. It's kind of right smack dab in the middle of that range. And look, AI has been; this is the place in the business where AI is announcing itself as present most acutely. But it's still a minority of the growth dollars that are coming into the Voice business year-over-year. But that contribution has increased in each of the last several quarters, which I think is actually the best of both worlds. It's still early innings, as Andy has described, but you're also seeing very good go-to-market execution with the "traditional non-AI customer" at Twilio.
And so as we've placed more incentives around cross-sell and multi-product adoption in our comp plans for our sales teams, they're still spending plenty of time selling through messaging, selling through many of our other software add-ons, selling through email, but it also allows them to gravitate into the Voice channel as well. We've won some competitive takeouts. We've won some cross-sell opportunities where maybe we've fully consolidated while it's shared in other channels, which then allows you to go and pursue other opportunities with those accounts. So you're getting very balanced performance in the Voice business, but Voice AI is absolutely coming on as a more meaningful contributor to growth year-over-year. Where it could go? I mean, I think one of the interesting things about Voice now is you can actually scale it programmatically in a way that you really couldn't historically.
I mean, Andy's talked about all these use cases, even for super mundane use cases to us as a consumer, to the business, it's incredibly expensive to solve that problem because there has to be a human on the other side of every single one of those phone calls. And that's why we're all met with 30 minute-40-minute wait times when we want to actually solve a real complex issue. We should never see a wait time in five years in the Voice channel. And so you can now scale this channel programmatically in much the same way that you scale messaging and email. So through that lens, if you took it in the most blue sky version, the ceiling is uncapped. But we also have a very large messaging business. We have a pretty good-sized email business.
And I think it would be naive to think that AI won't inevitably influence those channels as well. But as Andy's alluded to, we're still very early innings in the adoption curve of Voice AI. And it is the place where you have kind of the perfect storm of businesses spend a lot on it. It's inefficient spend. It's generally a bad consumer experience. And so at a minimum, you can do it more effectively from a cost perspective. But with LLMs and AI and many of these very innovative voice models, you can actually solve the customer's problem more effectively and drive ROI on that through the actual conversation itself, not just through the cost to serve that interaction.
Perfect. And when we think about the components of a Voice AI deal, so from my understanding, there's four pieces. Correct me if I'm wrong. You have the Voice APIs. You have the software pieces, which are Conversation Relay and Conversational Intelligence. And then I also believe there are some model hosting costs as well too if a customer chooses to go down that route. So for those in the audience, can you just describe each of those moving pieces, why that's important, why would a customer need them, or in cases potentially where they don't? Why is that?
Sure. So I think whether it's enterprise or upstart that's thinking, "I have a unique approach that I want to build some Voice AI solution for a given market. What are the elements that I need from the bottom of the stack all the way to the top?" I probably don't want to spend all my R&D time rebuilding the Super Network and all the telecom infrastructure that Twilio built. So that one right there is the easy one. And that's why we see the developer audience come to us really quickly. Come get a phone number, buy connectivity, buy Programmable Voice, get up and running in a few minutes, and then start building on top from there. So that's just the pure and simple global connectivity and coverage any number in all these countries and all the trust that the calls are just going to work.
And then from a Programmable Voice perspective, you have all these inside that API. You have all these features and functionality to very quickly say, "I want to record that call. I want to transcribe that call. I want to say or play things back to a consumer," just even at a primitive level. So you have a Voice AI usage that's built on top of those. Then we saw customers build those over and over and over again. And so we said, "Okay, let's introduce Conversation Relay that handles all the speech recognition." And we have a variety of providers.
Unfortunately, I get pitched by every single company that says, "We have the best speech recognition in every language across the globe," or, "We have the best generative AI voices in every language across the globe." Well, we want to offer our customers no different than we built an abstraction over all things telecom, all things for speech recognition and voices. And so we have multiple providers under the hood there. So a customer from Google to Amazon to Deepgram to ElevenLabs and others under the hood, that's just a configuration for our customers. So they can quickly build that conversational AI product on top. Then Conversational Intelligence essentially takes and bundles a recording very securely and encrypted, and then a transcription and redacts PII, so personally identifiable information. And then it applies LLMs on top of that to analyze that call transcript.
So instead of just giving a customer a raw transcript, it's analyzing it. Like I said earlier, did that consumer mention a variety of keywords? They're going to churn, or they had bad sentiment, or their flight was canceled, and they want to rebook. These types of things that can then trigger via a webhook anything you want to do. So if a consumer could say, "Don't ever call me again," we identify that. We append that and send that over and append that to the do not call list. Those types of things for a simple use case, or this is now an upsell product. This consumer said that they are interested in opening a new account on these things. Well, that can trigger it to a lead flow to something else. It can also help then train your AI agent.
So you can go back and look through and say, "We just did 1,000 calls with our Voice AI agent. We applied conversational intelligence. We now have understanding. We can tweak the prompts and the models and add more data." And then we feel more comfortable about going up and up and up to production too. So those pieces from connectivity and the programmable APIs to conversation relay to conversational intelligence, the way I like to put it is these LLMs like modularity. And to Rodney's point that we're in early innings, we see customers, whether it's ISVs and enterprises, they want optionality because they hear every single day something is better, faster, smarter. They don't want to be locked in, and they want to be able to deploy the best solution at any given time.
And so while we offer these as modular components, we make them work better together. So you get the best of both worlds in that sense. You can get up and running quickly, but you're not stuck in the black box scenario of, "I don't know what's going on inside that conversational AI agent that I just built." Or the other side is, "It's too many pieces that I can't get up and running quickly." You want to be able to get up and running quickly but have optionality to bring in and out components or data pieces as you go along the way. So that's in the buy versus build that we see customers say, "Okay, you have those pieces, but you also offer me optionality." So six months from now, a year from now, I can add more to this and make it better and better so I can take my enterprise use case and get a full production.
Yeah. I think there's a lot of excitement around Conversation Relay specifically, given that's a software product, high gross margin, right? We'll get into potential uplift around that. But from my understanding, you could go to the cloud infrastructure players also offer that. I think there's thoughts on, could you see a Sierra or one of the AI agent platforms start to incorporate this in their offering as well too? So when you think about the competitive landscape, maybe you could talk a little bit about Twilio's edge there. Why would a customer decide to go with Twilio? Why might they go with another solution? What's influencing that decision?
Yeah. Yeah. And like I said, over the years, we observe how customers have used our primitives, lower-level primitives, for lack of a better term, of these APIs, observed that behavior, and then abstracted one layer more of complexity. It started at the telecom layer. Then it went to the programmability layer. Then it went to the, "How do I choose which speech recognition is good for me or voice is good for me?" Okay, now that's a configuration. And then once I stitch those together, well, that's done Conversation Relay. And then insights on Conversation Relay to show how it's performing and things like that. Same thing with Conversational Intelligence.
So as we look at ISVs that are at the very top, called the application layer, completely, what we often see is they might think, "I need to build all of that stuff, all the way down to maybe just raw connectivity." And then what we see over time is Twilio has already done that. And it's already connected. And there's insights all the way through this. So maybe I don't need to build all of this. I can buy these layers. And as we're kind of chipping away upstack and offering them more and more of those types of solutions, we're seeing in the whole buy versus build, "I want to deploy an AI agent for this specific vertical or this fully managed service." Twilio has offered a lot more upstack than maybe I thought. And I'm seeing more and more R&D investment.
And they're experts in this because they observe all of these customers doing it over and over and over again. Is that really my differentiator? Or could that be something that I would buy from Twilio so I can focus on my vertical that I'm going after and all the nuances that I need to integrate with 20 different healthcare systems to get this AI agent to work or my proprietary LLM or how I orchestrate my LLM in that case? So I think that's where we see the opportunity is at that infrastructure layer. And at the same time too, like I mentioned, the other channels that they might bring in to say, "Oh, if I want it to work well with messaging channel and email channel, Twilio is already building those types of orchestration. Do I really want to spend my time and energy and R&D effort in that or my industry-specific thing?
Yeah. Makes a lot of sense. We'll have one last question that gives people some numbers to go plug into their model. But when you think about these Voice AI deals and how they compare to maybe a traditional SMS deal, what's the upsell opportunity when you include something like Conversation Relay, Conversational Intelligence? What does that do to the average deal size versus just a Voice AI deal? Can you give us some context around that? And then Rodney, one for you is just when you think about the opportunity with Voice AI, I think there's a lot of excitement on these software products being able to add a higher gross margin component. But you could also make the argument that voice in itself, right, is higher gross margin. So do you need all these software pieces to be successful in voice? Maybe you could just talk about how that influences gross margin too.
Yeah, so I think first and foremost, the interesting thing about Voice AI in particular, number one, and Nady's described this at length, a lot of our voice business is, in fact, software. So we do absolutely provide that base layer of connectivity, and that's one of the beneficial positions that we're in. We don't have to be everything to everyone. If you just want to rely on this for the communication rails, that's our bread and butter, and that's what we've been doing for the entirety of the history of the company, but as Andy just described, there's so much more that we can do at that infrastructure layer so that you don't have to deploy your own precious resources to go and build stuff that we've already handled and arguably done better because that's our sole focus.
You can focus much more on the customer experience at the end of the day. So in the context of an AI conversation, whereas before maybe all you were monetizing was the minutes, maybe now you're layering on recording and transcription and conversational intelligence and conversation relay, all of those things are generally priced as additional charges per minute over the top of that voice call. So instead of getting your $0.01 per minute in programmable voice alone, I mean, the list price for conversation relay is $0.07 a minute. Now, like most of our products, as you scale up in production, you'll get volume discounts. But we've seen customers have meaningful uplift on a per interaction basis. But to them, it's a huge reduction in cost because the previous version of the world was burdening that call with a human, which could be measured in dollars.
This is a fully programmable solution that's measured in pennies. And so the ROI, it proves itself out at the point of implementation. That's before you get to the better outcome for the consumer at the end of the day. And so tying it all back to how does this contribute to Twilio's P&L overall, voice is structurally a higher margin channel for us, not just at the connectivity layer, but also because you have many of these software-enabled components to it. And so this is an area where we're obviously spending a lot of resources internally to develop newer solutions, but also gear the sales team to drive more cross-sell and multi-product adoption because it also benefits gross margins and gross profit dollars at the end of the day.
Perfect. Well, we'll leave it there. Thanks, everyone, for joining. And thank you, guys. I appreciate all the thoughts today. So let's give them a round of applause.
Thank you.