Ryan Barreto: experience as people are coming in through the trial. We're seeing good progress in terms of the product market fit, in terms of the publishing use case, and I think we'll have more updates for you in the future once we have a little bit more time with this being available on the website.
Alex Underwood: Yeah, and I'll just add, Willow, that we mentioned this on the Q4 call, and it's worth mentioning again. A lot of these implementations on the pricing and packaging essentials, this is just happening right now. So we do expect to see a modest deceleration in the sub-30K segment this year and then looking to stabilize going into next year.
Ramo Lenshow: That's great. Thanks, guys.
Operator: Thank you. Thank you. Your next question comes from the line of Rob Oliver from Baird. Your line is live.
Rob Oliver: Great. Thanks very much. Appreciate it. I'm on for myself tonight. Two questions, one for you, Ryan, and then Alex, one for you, a follow-up. I mean, Ryan, you've been selling to marketing departments for a long time, and I'm sure that's informing how you guys are thinking about Trellis. And I know we're going to get more next week, but I guess I'd maybe ask the question a different way. What are you seeing in terms of patterns of behavior among users within marketing departments, users of Sprout, that gives you optimism that Trellis may, you know, perhaps be an avenue or an opportunity to, you know, get more of those additional products, say, influencer marketing, news web premium analytics, into customers' hands natively via kind of an AI-driven platform. Any early reads there would be helpful, recognizing we're going to get, obviously, more on that next week. Then I had a quick follow-up.
Ryan Barreto: Yeah, I appreciate it. Good to have you on, Rob. A few things I'd call out. So one, I think one of the biggest things here is just speed to insights. We talk a lot about social intelligence, and Trellis is really landing that for customers. We gave the example in the prepared remarks of the entertainment company that had a reputational issue that was going viral on social media. Historically, for most listening solutions, that would have been a very difficult thing for a practitioner or a marketer to be able to figure out. You think about the amount of time to be able to try and go through and create a Boolean query and report to be able to identify this type of issue, to get the data, to then have an analyst go through it, and then make some decisions and take action. And we're talking about minutes now in which our customer was able to figure out what the situation was, where it was happening, what the sentiment was, what the source was, and could quickly turn that into updating an executive team and then turning it into action. So there's just a ton of value for customers and the speed to insights. and really delivering social intelligence. We're also just seeing for our customers, as you can imagine, as we go past listening into other parts of the platform, the ability to create better performing content or to ensure that you're responding to customer issues that might be gaining traction. Those are really big value ads for customers that are really resonating for customers today and feel like pretty unique experiences that exist in the market. So those things are all things that are really standing out for our marketing customers today. And, you know, we're excited to have it in more hands as we get Trellis across listing in the rest of the product set.
Rob Oliver: Okay, great. Really, really helpful caller. Thank you. And then Alex, just one from you on the margins, obviously really strong margin in Q1, nice beat. And the full year was raised, but a little bit lighter on Q2. And just if you could just refresh us or help us understand just that the cadence there, is there some seasonality and where that additional margin is going in terms of spend? Thanks, guys.
Alex Underwood: Appreciate that, Rob. Good to have you on. So we're pleased with the Q1 leverage performance and the discipline team showed on the spend side. At the same time, we wouldn't view the Q1 beta as like a dollar-for-dollar change in the full-year cost structure. So a meaningful portion of the upside for Q1 came from expense timing and spend cadence, particularly around hiring and just the pacing of investments early in the year. So we're maintaining the flexibility for the balance of the year, not assuming that every Q1 expense benefit repeats. Importantly, this has not changed our operating discipline. So we're pleased to raise the operating margin a bit for the year, but we're still committed to 15% operating margin exiting the year and getting to that 30% number for Q4 2027.
Rob Oliver: Got it. Helpful. Okay. Thanks, Alex. Appreciate it.
Operator: Your next question comes from the line of Ramo Lenshow from Barclays. Your line is live.
Ramo Lenshow: similar to what people have been asking so far. Could you speak to the conversations you're having with customers and their appetite to purchase social marketing products? And are you seeing continued tightness around budgets as a result of AI? And if AI is a core criteria during the deals, how is Trellis helping during this motion? Thank you.
Alex Underwood: I think you were on mute for the first part of your question. Would you mind just repeating yourself?
Ramo Lenshow: Yeah, absolutely. No, I was just going to say that my question was more around the buying environment and sort of what you're seeing in front of you. If you could speak to the conversations you're having with customers about their appetite to purchase social marketing tools amid the bifurcation between AI and non-AI budgets, that would be really helpful.
Ryan Barreto: Yeah, I appreciate the question. You know, I think like everywhere, the demand environment is similar to what we experienced last year. You know, there's customers that are certainly facing bugs. budget constraints today, but you can see it in some of the customer stories that we've had and the performance in Q1. Customers are still buying. They're just expecting really strong return on investment on those purchases, and they're expecting that the speed to value, that the speed to onboarding and adoption happens really quickly. And similar to one of the earlier questions that I'd highlight, you know, this really comes down to what kind of impact are you having for customers today in this environment? How can you help them either grow revenue, reduce risk, or contain costs? And so we see our opportunities across all of those things. From a revenue growth perspective, certainly this is a great opportunity for customers to be able to run really great campaigns, whether they're organic or paid. and to know exactly how to leverage their dollars to drive greater pipeline for the organization. We're also seeing that our customers have to be where their customers are. And the reality is today, social is becoming one of the number one channels for customers to go to from a customer service perspective. And when they show up on social, they have a high bar in terms of expectation on you responding and the timeliness of that. So ensuring that our customers are set up to respond as fast as possible to have these conversations with their customers is incredibly important. The social intelligence, the data component of this is huge. The signal that exists on social is absolutely massive. It's unfiltered. It's unbiased. It's your customers and the customers you want to get. And we have the ability to parse through all of this data and give real insights to our customers to help them make really transformative decisions in how they're running their business. These are all the things that end up being at the forefront as customers are in cycles with us today and as we're helping justify the value for them as they're investing in Sprout and convincing their CFOs that this is a really smart thing for the growth of their business.
Ramo Lenshow: Okay, perfect. And maybe just one follow up on trellis. It's really nice to hear the early traction you guys are seeing from the going GA. If you think about the long term opportunity within the platform from monetization perspective, is there a possibility? I mean, it sounds like it might be just be embedded within the platform pricing, but is there an opportunity in the long tail of it to be sort of standalone pricing level? Or how are you guys thinking about that?
Ryan Barreto: Yeah, I appreciate the question. And so the answer is yes. And we mentioned on the call, but we'll be going a little bit deeper into the monetization strategy as well as a bunch of the AI advancements that we're making at Breaking Ground on May 13th. So hopefully you and a bunch of others will join us. But at a high level, the way to think about this is Trellis initially will use a hybrid model. that will combine user access with usage-based monetization. And this really reflects how the product works. So customers need access to the AI layer inside of Sprout, and that usage should scale with the amount of value and compute being consumed. So our goal really is simple to start in that we want to drive adoption. We want to make sure that customers are getting in there, that they're having these magical experiences with the product and seeing value. They're building it into workflows. And then as we're getting it in customers' hands, we expect that it's going to drive usage and it's going to happen across, you know, listening today in News Whip, but later broader, the broader Sprout platform. And as more of those customers adopt Trellis across all of those capabilities, we expect to see that usage and value go up, which we'll be monetizing as well. So we will have a SKU for it that we'll be talking about. We do see it as another area of opportunity for us to be able to grow our ACVs and to grow our overall revenue with our customer base while adding more value.
Ramo Lenshow: Perfect. Thank you. Thank you. Thank you.
Operator: Your next question comes from the line of Adam Hotchkiss from Goldman Sachs. Your line is live.
Adam Hotchkiss: Okay, great. Thanks for taking the questions. I'd love to ask a quick follow-up around the AI products. How do you think about token costs within the context of these AI products as they scale? I sort of think of social platforms, obviously, as having high volumes of data. And I'm curious if there's inherently higher inference loads associated. associated with that compared to more narrow application use cases. So maybe just talk at a high level about how that impacts scalability of use cases or whether there are mitigating factors that we should know about in terms of token usage and inference load. Thanks so much.
Ryan Barreto: Yeah, Adam, I appreciate it. I think probably a few things that I would take away here. One, we feel really good about our ability to manage the costs related to AI and tokens. Two, a lot of credit to our engineering team who spent a lot of time Within all of this, thinking about the models that we use in the back end and the way that we approach these things and ways to be most cost efficient in the work that we're doing. Obviously, the use of AI and the use of models varies depending on the use cases that go in. So there's this opportunity for us to be able to swap out things in the back end and make sure that we're optimizing token costs based on what our customers are doing. And then we're doing, as you might imagine, a ton of modeling capabilities In the background, we've had the opportunity while Trellis was in beta to understand usage patterns from customers and developing our monetization model. And then obviously making sure that the SKU that we'll be sharing more details on factors in the expected costs, as well as we'll have tiering systems to allow us to make sure that we're monetizing any of the consumption that's going in. So this ends up being a really good net positive for the company while customers get more value.
Adam Hotchkiss: Okay, got it. Great. That's really helpful color. And then I guess second, could you just update us on what the mix of your channel for new logo looks like, particularly for some of the 30k plus new ads that you're doing today, maybe versus historical? I know we had historically talked about things like social studio conversions and the Salesforce relationship. And you obviously have the robust direct sales team. But how should we think about that mix today? And how do you think about that going forward? Thanks.
Ryan Barreto: Yeah, I appreciate it. The majority of our business is direct through our sales teams. We certainly have some great relationships out in the market. Salesforce is a great example. We continue to be in a lot of events with Salesforce and our integrations into things like Service Cloud and AgentForce help us get referred in and help us co-sell many places. We've built some amazing integrations into other places like Canva and Adobe and a number of other organizations, which ends up being a helpful thing for us as we think about the ecosystem value of having integrations. But the majority of our channel is direct. for us, and there's a healthy mix in our customer base of inbound versus outbound, and then customers that are moving from other competitors, and then customers that are either using an agency or might be just directly in the native networks. So we see it as many different opportunities for our sales teams to be able to create pipeline and go execute against that opportunity.
Alex Underwood: I would just add, Adam, as you'd expect, and we went through some of these customer stories in the call today, I mean, when you're getting into deals for customers over $30K, over $50K in ARR, those are majority direct. I mean, agency is still a really critical part of our go-to-market strategy, but it's a little bit more down-market at times.
Adam Hotchkiss: Okay, great. Thank you both. Thank you.
Operator: Your next question comes from the line of Scott Berg from Needham & Company. Your line is live.
Luke Smekap: Hey, guys. Luke Smekap on for Scott Berg. Thanks for taking the questions. Maybe just a question for you, Alex. It's been a few years since the company moved from ARR to CRPO for measuring bookings on a quarterly basis, but it really hasn't been kind of a perfect proxy to date. And I guess with CRPO kind of growing that 10% year over year versus where the 1Q revenue growth rate shook out, I guess would you say are we at the point that CRPO gives the right view kind of on the current business momentum?
Alex Underwood: So is the question about RPO performance in the quarter or just how to better understand the business?
Luke Smekap: Yeah, just kind of how to better understand kind of if CRPO is the right metric to be watching.
Alex Underwood: Yeah, so I can talk a little bit about RPO, then we can talk a little bit about the segmentation we provided last quarter. So RPO and CRPO reflect the demand environment we're operating in today and reflective really of the performance from 2025. So both metrics grew approximately 10% year over year, which is now much more aligned with revenue growth. So from a revenue visibility standpoint, we feel the guide appropriately reflects what we're seeing in the business today. That said, we're not satisfied with the bookings performance underneath those metrics. The pressure is not broad-based customer value or renewals, right? So the renewal base remains durable, and customers continue to make longer commitments to Sprout, which we talked about with our multi-year contract mix, which is now half of our overall contract mix. The opportunity is moving the pace of new business and expansion in the current environment, and really that's what Ryan and the team are focused on. The part of the business that's most aligned to our strategy continues to perform better, right? So 30K and above, that grew 21% year over year and crossed that 60% threshold for total subscription revenue. And then customers above 50K grew nicely in the quarter as well. So I think that's where I would leave the RPO discussion. I think when we contemplated the data disclosure on the Q4 call, we really wanted to help uh, investors and analysts understand how to better model the business. And that's why we gave you the 30 K above and below, because we really think that's what is ultimately the strategy of the company that we're driving at right now for both segments. And, uh, you know, we understand that we had to come back with something when we took air our way a couple of years ago.
Luke Smekap: Got it. Thanks. That's helpful color.
Operator: Your next question comes from the line of David Hines from Canaccord Genuity. Your line is live.
David Hines: Hey guys, this is Ryan. I'm for DJ. Thanks for taking our questions. Um, so AI has obviously led to this great reevaluation of existing tools across the tech stack. Um, so a bit of a two parter, but do you typically find that social has its own dedicated budget for AI experimentation or is it included within marketing? And then if it is within marketing, where would you say it stacks up against other competing priorities?
Ryan Barreto: Yeah, I appreciate the question, Ryan. You know, I think from a budget perspective, I don't know that... Our customers today are thinking about it as one and the same. I do think we have a huge opportunity here to help them with it. Most customers we're talking to are trying to figure out how to better leverage AI to move their business forward. I think there's a huge opportunity that we see as we're getting in front of customers to help them see the art of the possible, to help them see specifically in the marketing department where there's massive opportunity for them. The examples that we gave on the call today with Trellis and with AI are some really good examples of where value is coming, speed to insights for customers, enabling you to create better content that's going to perform, helping you differentiate against your competitors, identifying potentially challenging reputational issues. So these are some of the things that we get to take these AI needs and put some real products and solutions behind them, which I think is really, really helpful for our customers. And then in terms of how they think about the stack rank and the prioritization, what we hear from our customers today is, You know, budgets are tight, but we've got to figure out a way to grow, and we've got to figure out a way to make sure that we're reducing risk and consolidating cost. And so similar to an earlier question that I provided some feedback on, we see opportunities to help customers in all those things. You know, from a growth perspective, we can help you create amazing content, whether it's organic or paid, to make sure that you're driving the right amount of awareness or pipeline there. from a social campaign perspective. We know that our customers more and more are getting pulled into social to be able to engage with customers from a community management or social care perspective. And then we know that that data that exists on social can really help them thinking about the investment strategy that they need. It tends to be one of those things because of the way that social shows up on where our customers' customers are that it becomes pretty important. But I think that in this budget environment, making sure that you're really tying the ROI back for customers and ideally, in many cases, consolidating some of their other solutions or spend is really how you help.
David Hines: Okay. Makes sense. And then maybe more of a higher level one. So we saw Meta acquired a notebook a couple of months ago. So I was just wondering, you know, as agents get more sophisticated and conversational, do you think there's a legitimate risk that these large social networks will develop their own conversational agents for brand users to directly engage with their customers?
Ryan Barreto: Yeah. I mean, one of the, The reasons that we exist is that we really, you know, kind of going back to an earlier question that we had today just about the networks that our customers use and the proliferation of those and which ones are most important, we see this every single day. And so kind of going back to that stat, 90% of our customers use five or more social networks. The reality is that's just continuing to grow, you know, certainly across all the meta properties, but then... all of the social networks and our customers need to show up across all of them. They can't just work within one social network and hope that they're addressing all the things that they need to do from a marketing perspective, a sales perspective, a customer support perspective. And so, you know, historically through time, you know, we'll see some of the social networks create some sorts of productivity assets for their own internal network. But what we hear from our customers is that's not going to be It's not going to be the full solution. It's not going to allow them to change their workflows because they need to think holistically about their social strategy. And that's where we come into play. Our customers log in to Sprout Social every single day. Our practitioners are spending hours a day in our platform. And this is how they're accessing all the social networks. This is how they're sending out their marketing campaigns and engaging with customers. So I expect that in scenarios like that, that might play for a customer that's maybe more in the SMB space that might only be on one network, but from a business tool perspective and for the customers where we're really focused, they need to be thinking across all of their networks and they need a platform like Sprout to be able to show up in the right places.
David Hines: Got it. Thanks, guys. Appreciate it. Thanks for the question.
Operator: The next question comes from the line of Jack McShane from Stiefel. Your line is now live.
Jack McShane: Yeah. Hey, everyone. This is Jack on for Parker. Thanks for taking the questions today. Ryan, for you, kind of a two-parter, but can you speak on how your current AI feature set and roadmap has resonated in the market to the extent that it's had any material impact on the top of funnel? And, you know, similar to that, you know, within your existing base, have the launches of, launch and marketing of Trellis impacted upsell conversations around the core underlying premium products like listening and News Whip?
Ryan Barreto: Yeah, I appreciate the question, Jack. So in terms of the AI features and resonating, you know, I'd say again, we're pretty early on here. The progress is being strong. from the standpoint that we were in beta for the end of last year going into this year, we went general availability at the end of the first quarter here. So pretty early on, too early to really call out any specific numbers, but I will say that it is differentiating us in conversations with customers. We're getting a lot of great feedback from new business customers and prospects. And then on the customer side of things, Clearly, we've had a lot of good adoption in a short period of time and listening with the thousands of users that have got access to it. Certainly, it is a huge opportunity for us, one, from a driving adoption and value perspective and listening in News Whip for the customers that have it, and then certainly from an upsell opportunity. As you can imagine, these products deliver these magical experiences, and if you've used something like listening There's not many products that look like News Whip, but if you've tried to understand what's happening from a PR perspective, and then you look at what Trellis offers to our customers today, it's really a magical experience. It's enabling customers to get insights in a way that wasn't available before, wasn't possible before. And so we certainly see this as something that's going to help us over time from a new business perspective.
Jack McShane: from an expansion perspective and then certainly from an adoption usage retention and renewal perspective got it and uh on the essentials package um just be curious is this more so targeting you know low-end existing customers or net new
Ryan Barreto: Yeah, it would be targeting net new customers. We know that there's an addressable market out there. We know that we have a code base and a platform that could serve those customers today. We see them coming into our inbound funnel, but in the historic state, the pricing and packaging wasn't the right fit. The product had too many capabilities for what those customers were coming in for. And so now we've got a really targeted network effort for those customers with the right product mix, with the right pricing and packaging. And then for us, it's, you know, with the PLG and self-serve motion of it, it's really reducing the customer acquisition cost against it. So it's definitely targeting new customers. And we think that, you know, there's a lot of customers out there that'll get great value from it.
Jack McShane: Great.
Ryan Barreto: Thank you. Thank you.
Matt Van Fleet: your final question comes from the line of matt van fleet from canter your line is now live all right good afternoon thanks for taking the question curious on on how uh you're approaching i guess third-party models and agents from accessing the data in sprout to to run workflows across the business um i guess what's your approach on sort of a more open platform versus monetizing that access point and understanding that there's a lot of unique and critical data here and not wanting to just simply be a data source and actually help with those workflows.
Ryan Barreto: Yeah, thanks Matt. I appreciate the question. And actually, you know, the answer is really wrapped up in the final part of your question here is, We are sitting on really important, incredible data that is not easily accessible, in most cases not accessible at all by any of these frontier models or the LLMs. The data set that we have is incredibly rich and real-time and unbiased. And a huge part of what we do is taking that data and making sense of it. If we think about the work that we've done over the last 16 years to be able to understand data The various data sources, the sentiment behind these sources, to be able to categorize this and put it in a place that we can leverage AI to make sense of it is a huge part of the secret sauce here at Sprout and the value that we're adding to customers. And so for us today, this really isn't about having third-party agents and models tapping in to the raw data and the things that we're doing. Over time, You know, I think there's a conversation to be had in terms of how do we take the insights and the things that we've uniquely done with our proprietary models and put in a place that can hand off to agents so that customers can use it in the rest of their tech ecosystem. So, you know, I think a future conversation to happen there, but so much of the work that we're doing today is so nuanced, and that's really what our competitive advantage is from an AI perspective in the work that we're doing for our customers today in Trellis.
Matt Van Fleet: Very helpful. And then as you look at the customer care offering, curious on what you're seeing in terms of a usage and resolution rate and ultimately where you think you can take that as Trellis is built more fully into that product as well.
Ryan Barreto: Yeah, you know, we are really excited about this. We talked a lot about it last year in that we really surged within the customer care use case. We've got some massive organizations and brands that entrust us every single day to be able to manage the massive volume that they have from a social customer care perspective. We built a lot last year when we think about our cases, our integration into the service cloud, our ability to really drive up human agent productivity and to help customers understand what's happening from a service perspective and then to take that data and have it go across the rest of the organization. And certainly as we think about Trellis, we believe that there's these massive opportunities to drive even more efficiencies for the service centers that are in social customer care every day. Part of what goes into the work that we're doing here as well is just thinking about where our customers are on the adoption scale for this. Because of the public nature of social, human in the loop is really important to our customers. So having AI solutions that might help you get much quicker at potential ideas to answer a question from our customer or to triage and route MVP customers to certain spots, make sure that you're delivering on SLA. So these are all things that the AI can help with. And then if we can do it in a way that increases the efficiency and productivity of agents, but still keeps humans in the loop, That's really what our customers are looking for. So we're excited about the work that we're going to be able to do with Trellis within customer care. And we think that it's going to be an additional unlock for customers as they think about how they're serving their customers, especially with a lot of the brands that just have such high volume. And similar to what I said before, the expectation on social is that you are responding faster than many other channels. And the pressure on a brand to do that is heightened given the social nature of it. So we know that we have a really big role to play there. We're excited about what we've been seeing with customers today, and we think we get some unlocks when we unlock Trellis for those customers.
Matt Van Fleet: Great. Thank you. Thank you.
Operator: That concludes our question and answer session. I will now turn the call back over to Ryan Barreto for closing remarks.
Ryan Barreto: Thanks very much, and thank you all for joining us this evening. I know it's a busy night across software, and we will be connecting with many of you in the days ahead. Before I close, I just want to highlight a few of the takeaways from the first quarter. First, our 30K Plus customer segment remains a clear growth engine for the company, up 21% year over year and now representing more than 60%. of our subscription revenue for the first time. These customers are demonstrating stronger retention, broader multi-product adoption, greater expansion potential, and deeper alignment with our social intelligence vision. Second, we're still early in the changes we're making below 30K. This part of the business requires a different product and go-to-market motion, and we're now implementing that through the Essentials product and self-serve, and we've created a more efficient onboarding and support model. We expect this cohort to continue to de-sell through 2026, which is reflected in our outlook, with the overall benefits of this strategy becoming more visible as we move into 2027. Third, we're making real progress with Trellis and AI. We spent a lot of time on that tonight. Trellis is now live across listening and News Whip. We're seeing adoption scaling, and we're really looking forward to sharing more at Breaking Ground on May 13th, including our broader AI roadmap and the monetization framework that we're rolling out as well. And then finally, our board's authorization of a $50 million share repurchase program reflects our confidence in the durability of this business, our free cash flow generation, and the long-term opportunity we see ahead. We believe there's a meaningful disconnect between the current valuation levels and the long-term value we expect to create, and we see this as a compelling use of capital. And I'll end with just a big thank you to our customers for their continued trust and partnership, and to our team for their focus and discipline and the care they bring to their work every single day. We appreciate all of your time tonight and your continued interest in Sprout, and we will talk to you soon. Have a great evening. Thanks, everybody.
Operator: That concludes today's call. Thank you for attending. You may now disconnect.
