All right, excellent. Thank you everyone for joining us. Keith Weiss, I run the US software franchise here at Morgan Stanley, filling in for Elizabeth Porter, who had a beautiful baby girl. Excuse the substitution. Really pleased to be able to talk about a really exciting story, one that's been putting up really good fundamentals, not getting appreciated enough for it, I'll just tell you guys, in Klaviyo. We have the full cast. We have Andrew Bialecki, Co-founder and CEO. We have Amanda Whalen, CFO, and Chano Fernandez, Co-CEO. Thank you all for joining us. Two and a half years since going public, I think thus far, Klaviyo has disproven some of the initial bear cases in terms of too limited of a scope, too limited of a market opportunity. maybe to phrase it as a question rather than just a statement, how have you done that? Like, how have you guys been able to really sustain a durability of growth through an environment that's been mixed at best? Yeah. All right. Thanks for asking. Look, since we're Klaviyo's now 14 years old, I think. Since we started, we just had this thesis that if you think about businesses and organizations on one side and then end consumers, customers on the other, we're just going through this massive shift of, you know, hey, it's not humans in the middle, sales reps, customer service reps, other folks. It's gonna be all software, and increasingly, we think just, you know, powered by intelligent software, thus, you know, AI and agents. Yeah, we've been just following that trajectory for the last 14 years. So that's what's driven us, you know, over 190,000 customers, $1.2 billion in revenue last year, growing really nicely. I think what's exciting for us now is we think about what, if you look at like, you know, AI and LLMs and what those have, you know, capabilities have unlocked. We've kinda thought about Klaviyo the first 14 years, we built all this infrastructure to basically allow businesses to program the rules, store all their customer data, you know, communicate with customers across a wide variety of channels for marketing use cases, for service use cases, all of it. The big unlock was, like, making that not just things that humans could program the rules, but that AI could, you know, write the rules and then optimize it. That's what we wanted to get to. This is like, I think now, I sound like it's gonna take us another 14 years. I think these next couple of years, maybe the next 14 quarters are, like, the most interesting. 'Cause I think every business now is going to say, "Hey, when it comes to how I treat my customers across all services, you know, marketing, sales, service, et cetera," we're focused on consumer businesses. I think everybody's looking at what is the agentic way, or we say the autonomous way, to deliver those customer experiences. To have AI that can define the rules of how I treat folks and then deliver those experiences and then learn from them and optimize. That's what we've been after, obviously, we've increased the breadth of our products, and we think about, like, kinda the infrastructure that's underneath it. Back in September, we launched our two agents for marketing and for customer service. We've seen really good adoption there. Yeah, we're just excited to, you know, the future is autonomous customer experiences. We're excited to usher that into hundreds of thousands of businesses today and hopefully millions in the near future. Excellent. One of the things that's always been impressive and compelling about this story from the get-go is that closed loop nature, right? It's not just automating a process for customers. It's automating a process for customers, letting them understand the results, feeding that back into the system to further automate the process. When we think about that in context of AI and these learning systems, it seems to be a really ripe opportunity for exactly the system that you put together. This is actually a question for Chano. Chano, you've had a really impressive career, Co-CEO at Workday, leading Applied AI through a lot of AI-driven growth. You're on the Klaviyo board. I'm sure there's something that you saw of how you can make this story better. You're not gonna join the company unless you see an opportunity to make it better. What was it that you saw in Klaviyo? How are you gonna take what's already a good story that's operating really well, how are you gonna make it better? Yeah. Thank you, Keith, and thank you for having us and everyone for joining. I mean, well, first and foremost, I would say because I had the privilege to be as part of the board, and I clearly saw that there is a shift coming. I think I don't need to tell all of you what is that shift about. I really thought that Klaviyo was really built for that future and for that shift, particularly for that, you know, infrastructure and that real-time customer engagement opportunities that it provides. Then that, you know, that was the time to do it for sure, right? Obviously, it's about people, and I think the world of Andrew and his has a really great vision for the future and quite of a unique founder. I think we can do amazing things together, so he's very exciting about that. Last but not least, Keith, you know, I spent my career mostly, you know, working on large enterprise companies. We are ready. We know how the infrastructure will have the foundation to move towards the enterprise and building that market opportunity, which is certainly even larger than the one we've been navigating on. That's really exciting. Got it. It's really the intersection of, one, an expansion in sort of the solution portfolio and what you're focusing on. Going from more of a just a focus on marketing lens to being the autonomous B2C CRM and at the same time expanding out the customer focus of it's not a SMB solution, it's one that's now ready to move upmarket into the mid-market into the enterprise. Those two axes enabling a very nice scaling function. To start on the TAM and the opportunity side of the equation. What does autonomous B2C CRM mean, right? Can you, can you walk us through kind of the vision and how the agentic layer is gonna further that vision and enable it to, to really work for the, for the end customer? Well, here's how we look at our product portfolio. I think there's, you know, we think about, like, traditionally, you know, pre this wave of AI, how we thought about software. It's either like infrastructure, and we thought about that as primarily stuff that you sell to developers and developers use to build applications. There's applications, and then your applications kinda get muddled because we're like, well, some of it's kind of like domain-specific infrastructure, and some of it's just like a nice, you know, polished UI. What's great about LLMs is I think they've expanded the scope of what software can be into now it's like, hey, look, all these like, you know, human users that are running around using software as tools, like that now, that can be done by artificial intelligence. That's just a huge new opportunity. For us, we look at that and say, "Hey, for every dollar that's spent on Klaviyo, there's like between $5-$10 businesses are spending on like human capital to go run it." Not, I mean, frankly, particularly efficiently, right? We talked to a lot of folks who are like, "Hey, do you think you really know, you know, do you have a good sense of like what your customer experience, like whether it's on customer service or in marketing should be?" "No, I don't. Do you guys have best practices? Can you help coach me up on that?" "Hey, do you feel like you're getting to all of your ideas?" The answer is like, "Well, I'm getting more done, but no. I mean, still there's stuff that I don't know or I can't get to. We look at that and think, man, you've got a whole bunch of people that are doing things. It's actually not optimized. They actually could be driving more customer engagement. Well, great. We're gonna build agents to go do that. That's one big opportunity. We have a whole product group that is we call our autonomy group that is just focused on building these agents that will sit on top of, you know, software as infrastructure. Underneath that, we think about, like, hey, what is the best, you know, infrastructure, the best platforms, the best software that agents are going to prefer and use when it comes to storing all of their customer data, indexing it, allowing, making it queryable in real time, then actually using that to communicate, so messaging, but not messaging, not just for marketing, but having conversations with customers, you know, whether it's over web chat or voice or through text messaging. What, how were they gonna define the rules and run the experiments? One of the really cool things we've seen now with our Customer Agent products is now that people have this always-on agent that is, like, good at adhering to the rules of the business, the policy of the business, we're seeing these, like, CX teams and operational teams, they're starting to experiment with the policies they use to run their business. Like, how do they treat customers? For instance, who gets a refund and when? Now all of a sudden that used to be something that's like, man, it's so hard to get adherence with that, you know, across like a customer experience organization. Well, agents don't have that problem. Now we can start to experiment and say, "Hey, 10% of the time, why don't we try something different, and let's see how that impacts, you know, things like NPS and retention." We look at these two different layers. This autonomy layer, we have a whole product group that just focuses on agents that will play the game of marketing and service and really, you know, design and deliver, you know, customer experiences for businesses. Then we think about the infrastructure it needs to run on. You know, since that's the thing we were founded on, you know, we built, we started Klaviyo as a database company that has, you know, is very good at storing, indexing consumer data at scale, but making it available in real time for, you know, whether it's an agent chatting with a customer or rendering a webpage or sending a message. Yeah, those are the two big opportunities. We think about that, you know, those, that agent layer, I mean, that we think is gonna be a bigger business than our current, you know, really like software infrastructure business. We also think that agents, because they're better users, you know, one of the things we talk about is like a typical software user base has this distribution where you like have a couple of power users that are really advanced, and then you have a bunch of intermediate users, and you have a long tail of kind of more novice users. You build, you do a lot of work to try to move people up the curve. The nice part about agents is they just go straight to advanced mode. In fact, they actually beat our advanced users. You know, they're kinda like PhDs at whatever the discipline in once we train them up. We also find that they push the infrastructure, and they use more of it. Just as an example, like a typical business for us, we don't have a seat-based model. Like, we charge based on like the size of the business in terms of the number of profiles or contacts or customers it has. We find that our agents, because they're better at delivering customer experiences, you know, to those individual consumers, they actually retain more customers. You end up with the infrastructure ends up getting used more. We look at both of those opportunities. One, we have like a whole business that's gonna be even larger than our business today, and the acceleration you get from agentic usage. You know, it's the most excited I've been since we started Klaviyo because I think both those things are very big opportunities. We've expanded into service, right? Expanded the scope. A really competitive environment out there. There's a lot of people who are focusing on the customer service opportunity. There's some really big incumbents, whether it's a Salesforce or the like, and there's a lot of startups who see this agentic opportunity as well. How do you look to differentiate the Klaviyo solution from both the incumbents and like the startups coming into the marketplace? Well, we're very good builders, so it's, I mean, no surprise we kind of put our heads together and think like, okay, well, what does it take to build agents and build, you know, kind of a good agent-building platform? I think that's become table stakes, right? How do you train up an agent, evaluate it, deploy it, et cetera, across all the various channels? There's two things that we're adding to our Customer Agent that we think are quite differentiated. The first is we built a set of algorithms, you can think of almost like agents on top of the agents that are good at training up Customer Agents. Let me explain why this matters so much. We've got, you know, about 193,000 businesses. I'll tell you, like, there's probably a 1,000 that know what it means to build an agent. If you gave them the tools, they would know how to train that thing up. You know, one of the patterns we've seen is there's a lot of this like, well, we'll deploy engineers, or we'll sell services around training these agents up. The problem is, like for a lot of businesses, that just immediately prices them out of the market. I mean, they can't afford hundreds of thousands of dollars to train this thing up once, let alone ongoing cost, right? They're just not at that scale. We actually think there's an enormous amount of latent demand amongst SMBs for Customer Agents because those are also the businesses that are the least optimized when it comes to customer service? 'Cause who is it? It's the founder of the business, the owner of the business, or somebody on the team that's handling these conversations one by one. These are not, you know, organizations that are like, "Yeah, we've employed a lot of automation. We've, you know, we've done a bunch of BPO." We need to help them train up these agents. What we started was we started this program where we're building agents. You can act as like a coach or trainer, right? You can imagine like your fitness trainer that like basically gets that Customer Agent for that business into shape. What does it do? It goes and takes all the information we can find about that business, right, on the internet, you know, on the publicly available internet, plus all the connectors that people already have embedded in Klaviyo. It goes, creates basically like a, you know, you could think, I'll just extend the fitness example here for a bit. A workout routine to put it through its paces and figure out how, like, strong it is, right? How good is it at delivering customer experience? Grades it, figures out where it's weak, and then tells either goes and fixes those problems on its own or goes back to the user and says, "Hey, you know what? You're a restaurant. I can't handle all your reservation requests 'cause you haven't hooked me into your back end here. Go connect, you know, Toast or whatever it is that you're using to manage reservations." Like, now I can answer those. Literally almost we have this like video game style interface where you're training up this Customer Agent that represents your business, and it just gets smarter and better. Like, as you give it more information, as it learns on its own. What's really important about this is we think this is not this matters just for SMBs. It's also really important for enterprise because enterprises need the agents that are gonna be sitting on top of their agent, kind of like the boxing trainer that's whipping it into shape as the business evolves, right? A large enterprise might, you know, launch a new product line, new set of services. They might acquire a company. Something changes, and they need to, like, constantly evolve that agent. That's not a job for human developers to do the way we're doing it today. I mean, we're sort of a little bit existential for us. We wanna serve all 190,000 businesses, so therefore we have to build these agents that can train up, you know, these Customer Agents. We think this technology is gonna become table stakes and the differentiator in enterprise as well. That's one. The second thing is because we already have our customer database, right? You can think of it as like a data warehouse that's just optimized not just for analytical queries, but also real-time usage, right? You can connect it to a Customer Agent, and it's not gonna go think for 10 minutes. It can respond in milliseconds. We already have that, every time you talk to our Customer Agent, if we have context on you can think about, you know, we talk about, like, memory files when it comes to, like, ChatGPT or Claude. We basically have a memory file on that consumer, and we can inject it into the context, into that conversation and optimize it. Just like you see, like, if you play with these personal AIs, like, man, it starts to feel like it knows you. Yeah, we can do the exact same thing. Now you can imagine you're getting these signals from, you know, our marketing use cases. You know, what are you browsing on a website, looking at on a mobile app? How are you using those products and services? You know, interaction with our marketing events. We then plumb all of that into the Customer Agent, and it produces a way better experience. Simple example, like, we have folks that will come back, you know, come to websites, you know, where we've enabled, you know, web chat through our Customer Agent, and people will just stop browsing the site. They'll just ask for recommendations and get spit out things based on their past purchase history because they're already authed through our Customer Agent. Our Customer Agent can handle that, and it's instantly a better experience. I think we're gonna find personalization on the Customer Agent side, not just generic handling, but personalization is gonna be another big differentiator. Got it. Chano, in terms of taking this platform, one of the things that has always been impressive about Klaviyo is it brings the customer a solution. It doesn't bring them a set of technologies, right? That's a, I think, a necessity for operating an SMB. SMB customers, they don't care about technology. They don't wanna deal with technology. They just want a solution to their problem. Does that resonate in the same way as you go into the enterprise, or does the go-to-market have to change, the presentation of the solution have to change to make this amenable and make it attractive to a larger enterprise customer? Yeah, great question, Keith. What we're seeing with the enterprise customers is they're looking for one single unified platform that really powers that entire customer relationship. Otherwise they have too many different flows and architectures and, you know, that don't provide that much efficiency, and they are costly. Let me give you a couple of examples, right? When they have that kind of retrofitting into general, the flywheel effect and understanding of the market, of the customers as a whole with that kind of memory file and, you know, understanding of the consumer that Andrew was talking about, and we're helping out provide real-time information with some of our automated flows. Those produce 10 times more revenue per customer that basically static customer campaigns will produce, right? That talks a little bit to the power clearly of the infrastructure, right? It resonates obviously in the enterprise. I think we commented that we doubled the number of customers to $1 million ARR+ in Q4 last year. We have our largest, you know, enterprise pipeline ever. Really we are confident that we can solve for that problem. Excellent. Then, Amanda, to bring you into the conversation, in early 2025, you guys implemented some pricing changes, billing based on total active profiles, an auto-downgrade feature, flexible sending options. As we go more into this agentic opportunity, are there more pricing changes that need to take place, or are you comfortable that you're well sort of positioning to accrue the value of what Andrew's bringing to the equation here? The beauty of our business model is that we do not price based on seats. We have never priced based on seats. We price based on the value that we provide to our customers. Okay. Our mission has always been that we are going to help you take your most valuable asset, which is your customer relationship, and make that even more valuable because we're gonna help you with technology make it feel like every single customer is the only customer that that business has. By personalizing those experiences, by, as Chano said, making them more automated, we increase the value of those profiles. By making each messaging and each communication and every experience more valuable, we increase the demand for it. The pricing going forward will continue to align to that point of view, which is as we help customers generate more revenue and more value, we'll align to that. In the case of Marketing Agent, which Andrew spoke about, it'll be priced based on the number, you know, roughly the usage that you have, and how are we able to drive really great outcomes with that usage. It'll be, think about it as roughly equivalent to tokens. Mm-hmm. The most important thing is that, again, if that usage is driving better consumer experiences, customers are very, very willing to pay for it. Got it. If we think about that and take it up one level into the 2026 revenue guidance, you talked about a minimal contribution from the newest slate of the AI products and the service products. Can you help us better understand the adoption curve? Like, what should be our expectation for the adoption curve? I mean, Klaviyo service was only went into GA back in September 2025. The agents now coming into the marketplace. How should we think about that adoption curve? The way to think about that adoption curve is it's off to an incredibly strong start. Service, for instance, is our fastest-growing product in our company history, even going back to looking at Text, which has been a really significant product for us over time. Today, almost 30% of our SMB plus customers are using that Text product. Service is off to an even faster start. What's driving customers to adopt it is that as they get exposed to the product, they're seeing the revenue that it drives, and they're seeing the benefit and really ingraining it in its workflows. One of the things we're really excited about on the Marketing Agent side is many of the customers who are adopting Marketing Agent, it's become their default. It's become the primary way that they're building campaigns because they see that it drives back to better outcomes. One of our customers, Adelson, is seeing 50% higher revenue per campaign from the campaigns that they're generating with Marketing Agent. Similarly, on the Customer Agent side, the customers who are really adopting it into their workflow, it's becoming the majority of the way that they interact with their consumers. As it becomes more embedded and customers are seeing this revenue from them, we're really seeing adoption pick up. Got it. We started to already see kind of the benefits of multi-product adoption. I think you guys talk about 60% of ARR now coming from multi-product customers, 15% from customers adopting at least three products. Any kind of view on where that's gonna go over the next two to three years? Chano, how can you kind of further accelerate that sort of platformization, if you will, of getting these customers to buy into the broader capabilities of what Klaviyo is able to bring? Obviously, as I said before, I believe on the power of that unified platform, and we're gonna be setting up things that will be much more ad hoc in terms of really focusing on, you know, upfront on those problems for those largest customers in terms of the upselling and cross-selling motions. Clearly thinking much more in advance in terms of pipeline and qualification on those opportunities and where are the ones that we should be participating on, right? As Andrew said, you know, the opportunity for some of these products is potentially 5x-10x, you know, what we have today in terms of the current opportunity. You know, typical customers may start more on email and text, but we're seeing much more adoption moving more rapidly, and we're gonna have some cross-specialist teams that are gonna be supporting some of those motions going forward. We're closing the loop much better between the value proposition that is coming from product marketing and sales that we were doing before as the teams are getting more ad hoc into, you know, how do we drive dynamics that work in the enterprise market. A big part of what makes that sale so possible is the value that our customers see from it. Just a couple of examples to help bring that to life. We have one brand we work with who's in the D2C space, who unified their email, their text messaging, and their analytics on Klaviyo, and they saw their time to generate campaigns decrease by 60%, and they saw their total cost of ownership decrease by 30%. They're really seeing the benefit of having everything on one platform. Even more importantly, it's the uplift that it helps to drive from them. Customers who have more than one product with us are seeing much higher revenue coming from it, even higher than just adding one plus one. It's almost a one plus one equals three situation here. A great example of that is a makeup brand who we work with, who again, unified email, text messaging, analytics, and in their case, service on it. In service, they're seeing high seventies resolution rate, and they saw a doubling in their AI-assisted revenue. We love it when unifying the platform drives higher revenue for our customers. Got it. Given sort of the environment that we're in, I mean, software has been under pressure through most of 2025. 2026, it probably even accelerated. And a lot of it is on concerns about Claude, tool use in terms of tool use. Is that about the ability to DIY? The Amazon CTO tweets that he developed a CRM system over the weekend. I'd like to ask him if he wants to support that CRM system every weekend for the rest of his life, but that's another question. All of this has weighed on multiples in software and multiples for Klaviyo as well, despite no degradation in terms of the fundamentals, which is frustrating for us, and I'm sure even more frustrating for you guys. Andrew, where are investors getting it wrong, right? Like, why is DIY not a risk? Why should we not heed more signal from what the Amazon CTO is tweeting out about what he can do with these vibe coding tools? Yeah. Well, look, we've always taken a very long-term view of like, "Hey, what, what do customers care about? Like, where is technology really going?" I go back to two things. Like, two things we think are, like, very persistent themes. One is, hey, we now have the technology that you can build agents that can do the work that humans were doing before. Like, that's just a whole new category of software that is going to be, you know, won or defined, right? Literally, I mean, if not certainly years, but like, certainly in probably the next couple of months, right? I think we're gonna find out also, you know, what? One of the things that's tough is, hey, what software is actually, like, differentiated infrastructure and what's like a nice, you know, a nice coat of paint on top of an Excel spreadsheet. You know, I think that's I don't envy folks. You know, you gotta go kind of figure that out. Like, I think that's something that we feel very confident. It's like, oh, no, what we build in terms of our customer database, what we do around messaging is like, hey, you couldn't just go replace that. To your comment on, like, do it yourself, actually, an experiment that we run internally to kind of prove this out, 'cause actually I think in the future, very near future, you're gonna get a lot of agents that are actually making the decisions about what software to use. It's not gonna be humans doing the eval. It's gonna be, you know, hey, agents are, hey, go tell me what you think is the right stack. One thing that we do is we actually have set up, you know, some agents, some coding agents and others, to like, hey, you're, you know, you're a business, and we do this different size. You're just starting out or you're a larger enterprise, and hey, you wanna set up, like, you wanna build your software stack so that software defines the entire customer experience. You're gonna want something that is this always-on agent, API, voice, text, et cetera, you know, that is our Customer Agent or something that looks like that. You want something that's gonna handle, you know, marketing, proactive messaging, something that personalizes and customizes mobile applications, you know, the website, even maybe in-store experiences. You want some underlying, you know, database that kind of makes all that consumer data accessible, right, and stores it, so you have one sort of central source of truth, right? We tell it to go out and go build that. We say like, "And by the way, I want you to use as much open source as you can," right? I mean, do the best, do high quality job, but do, you know, dumb down stack as much as you possibly can. What we find consistently when we send out, I mean, now these coding agents that can code for hours and hours, what they go off and do is they basically try to go replicate, you know, our data platform, and they quickly recognize, they're like, "Oh, shoot. Well, I can't use a data warehouse or data lake. It's actually too slow. I can't use an off-the-shelf database. Like, it's not flexible enough in terms of the querying. You know what I'll do is I'll build this hybrid stack that basically rebuilds what we've tried to do," right? It doesn't have the insights and, like, the query patterns that we've seen, right? That we have these, you know, routing systems that can optimize for that. I think there's a little bit of an experiment that folks need to run like that of, you know, hey, how really, like, trivial or non-trivial is that underlying infrastructure? We feel really good that, you know, what we've done on the database side in terms of real-time access to customer data, and this, like, attribution loop built in. Plus then what we've done with messaging around identity and compliance really matters. On top of that, we're actually doing a lot of work to expose that to agents so they can pick us from the start or, you know, I think a lot of RFPs now will be done agentically. Also we have our agent that we're running that will do marketing, right? Our Marketing Agent will just go define the marketing strategy for a new business or audit the marketing strategy of some of our largest customers. Again, it kind of reasons at a PhD level 'cause we expose it to all the marketing data we have of here's what works best. Then we tell it, you know, pick whatever underlying technology you want in terms of like, you know, how would you access customer data? How would you build marketing and these customer experiences? You know, tell us what requirements you need for that system. We're actually using those agents, you know, not only plumbing back into obviously our infrastructure, but we're telling it like, where are there gaps in what we built that you would want as an agent if you could have it? It's actually pressing, like, hard. I'll give you an example. You know, just email as a medium actually allows for a lot of interactivity. We're not used to this because very few companies actually expose it, but you might have bumped into like a Google spreadsheet or Google Docs that allows for commenting in line and things like this. It's actually any business can do that, just most people don't have the time to be able to do it. Our Marketing Agents will happily build interactive messages, and they convert way better. Okay. Right? They'll call back to our system and say, "Hey, it'd be really nice if you could add support for these different content types and maybe some components like this so the user can do some last mile editing." That's now become part of our roadmap for our infrastructure. We're actually using agents almost as like a customer advisory panel to feed back into the roadmap for our core, you know, marketing and now customer service infrastructure teams. I think I would look for companies that have these kind of loops of like, they're trying to build both the infrastructure layer and the agent layer and getting them to, you know, kind of work together to make both both parts better. Got it. Amanda, it sounds really cool, but it sounds like a lot of tokens, right? In FY 25 we saw gross margins come under some pressure. How should we think about that gross margin line on a go-forward basis? Is this a fundamentally kind of different COGS equation going forward as we get more and more of an agentic layer on top of the infrastructure layer? Sure. I would think about two things when it comes to gross margin. The first is that we have a lot of levers to play with. We have different products in the portfolio. As we expand the product portfolio and we're offering new products, that enables us to, you know, mix out the customer relationship in a way that overall is profitable. The second is that as we scale, we're getting increasing benefits from our own scale and our own infrastructure, which helps a lot. If you take a step back on gross margin, the way that we really think about it within our business is we think about almost, you know, miniature unit economics for each product line and each one that we're offering. It's not just about the gross margin, it's also about what's the right R&D model to support that? What's the right customer acquisition model to support that? Does each product that we're selling have strong unit economics? In certain ones, you may have higher, lower gross margins. They also come with lower customer acquisition costs because as Chano said, they're being sold into the existing customer base, and they come with huge expansion potential because they're driving those better outcomes and that higher revenue. Our customers almost see our business as a revenue optimization engine for them. If we can show them those better outcomes, they continue to expand, you know, to the point where they're seeing great ROI. We think about that gross margin not in isolation, but really. Right For each product, making sure that it's delivering the right economics for the long term. Right. If we abstract back, we see the results of that. That's right. Operating margins up 170 basis points. You're guiding to another 100 basis points of margin expansion in the year ahead. We're running short on time here. There's a lot more to talk about. Maybe just as a sort of wrap-up question, there's so much innovation taking place at Klaviyo right now. There's expansion of the kind of the market opportunity. As a fundamental analyst, I always wanna focus on the fundamentals, the stock price will take care of itself. If we're looking for the Key Performance Indicators that it's working, that this is really taking off, what should we be looking for in your results? What should we be looking for in terms of the KPIs to show us that, " hey, listen, the fundamentals are following through on the opportunity?" Yeah. Well, it's interesting you, I'll give you a couple that we look at internally. We'll start to share more of this as we go. One is we think this agent opportunity is very real. You know, what we've seen in some disciplines, coding, et cetera, is, like, is coming to all parts of, you know, human labor, but let's say digital human work. You mentioned like, hey, multiple products. I mean, we actually think about like, yeah, multiple products, but like today, it's all multiple products, but primarily multiple products through our infrastructure, right? I mean, we have a lot of adopters of our Customer Agent. We actually think it's like by this year, this is the year that every business, small business and enterprise, will adopt a Marketing Agent that helps augment what they're doing, right? The PhD that sits in the room and helps the whole team be better. Two is this is the year that everybody adopts like a Customer Agent for their business. Last year was the year of personal AI. This is the year that like every business, you know, doesn't just have a website, it actually needs an agent that represents them that's always on. I think both of those are gonna grow quite quickly, we actually look at like the multi, you know, multi-product adoption, but really focusing on like how many agents of ours have customers adopted. Mm-hmm. Yeah, stay tuned. We've seen some good growth so far, and I think there's this is gonna be the year that that really takes off. Amazing. Great story going on at Klaviyo. Congratulations on the success, and thank you for coming and sharing with us. Thank you. Thank you.