Everyone, and welcome to Amplitude's Third Quarter 2025 Earnings Conference Call. I'm John Streppa, Head of Investor Relations. Joining me today are Spenser Skates, CEO and Co-Founder of Amplitude, and Andrew Casey, Chief Financial Officer. During today's call, management will make forward-looking statements, including our financial outlook for the fourth quarter and full year 2025, the expected performance of our products, our expected quarterly and long-term growth, investments, and our overall future prospects. These forward-looking statements are based on current information, assumptions, and expectations and are subject to risks and uncertainties, some of which are beyond our control, that could cause actual results to differ materially from those described. Further information on the risks that could lead to different actual results is included in our filings with the Securities and Exchange Commission. You are cautioned not to place undue reliance on these forward-looking statements, and we assume no obligation to update them after today's call, except as required by law. Certain financial measures used today are expressed on a non-GAAP basis. We use these non-GAAP financial measures internally to facilitate analysis of our financial and business trends and for internal planning and forecasting purposes. These non-GAAP financial measures have limitations and should not be used in isolation from or as a substitute for financial information prepared in accordance with GAAP. Additional information regarding these non-GAAP financial measures and a reconciliation between these GAAP and non-GAAP measures are included in our earnings press release and supplemental financial information, which can be found on our Investor Relations website. With that, I'll hand the call over to Spenser.

Good afternoon, everyone, and welcome to Amplitude's Third Quarter 2025 Earnings Call. Today, I'm going to cover three things: first, our strong Q3 results and progress in the enterprise; second, the AI opportunity within analytics; third, product innovation and our customers. Let's go ahead and get started with our Q3 results. We delivered another strong quarter, continuing the acceleration we saw in Q2. We exceeded expectations on our core financial metrics and made solid progress against our enterprise strategy. Our third quarter revenue was $88.6 million, up 18% year-over-year and exceeding the high end of our guidance. Annual recurring revenue was $347 million, up 16% year-over-year and up $12 million from last quarter. Non-GAAP operating income was $0.6 million. Customers with more than $100,000 in ARR grew to 653, an increase of 15% year-over-year. Our Q3 performance reflects our continued execution against our strategy. We are winning simply by bringing Amplitude to everyone with AI. We are winning the enterprise with broad-based success with both AI natives and traditional enterprises, securing larger multi-year contracts. And we're winning the category with multi-product adoption now representing 71% of our ARR. Finally, we're winning together by leading the shift to being AI native across the entire Amplitude team. I wanted to take a little bit of time to talk about how AI is changing how software gets built. Every single product team runs the same loop: build, ship, use, and learn. The left side of that loop, build and ship, has been transformed by AI. AI coding has made it faster than ever to turn ideas into products. We are now at a point where someone can create a product that's used by millions overnight. By contrast, the right side of this loop, use and learn, remains in the stone ages. Companies ask users what they want, but actions are more powerful than words. The best way to understand what people want is to watch what they do. This is what Amplitude solves. Our AI analytics platform helps companies understand how people engage in their products, what they like, where they get stuck, and what keeps them coming back. These behavioral signals are the most powerful indicator for what to build. Automating and scaling that understanding is the next frontier. In this context, analytics is the perfect problem for AI to solve. To use analytics, you have to do a lot of manual work in specifying and setting up your query in between rounds of thinking. AI can handle all of that manual work, freeing up humans to focus on the thinking that leads to great insights. Amplitude has a unique position to build the AI analytics platform of the future. We have the world's largest database of product behavior. We have spent a decade working with world-class analytics teams. Over the past year, we've rebuilt the Amplitude team to be AI native. We've reorganized product development twice, and we've acquired four AI companies. We've trained our engineering, product management, and design teams deeply in AI. The company that disrupts the right side of this loop, the use and learn, the fastest will define the future of this space. We are all-in here. Let's get into the details on product innovation. In the last few weeks, we have launched several AI-native products here at Amplitude. I want to start with MCP. In October, we announced the public availability of our MCP server, the top requested feature from our customers. MCP is made for data analytics. It exposes all of Amplitude's functionality, so an AI agent can interact with it directly. It allows you to use Amplitude without knowing anything about the Amplitude UI or your data taxonomy. This is the best MCP use case that I have ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. It shows what is possible in the AI analytics future I talked about earlier. It brings the power of our data to anyone in any workflow. This opens Amplitude up to an entirely new cohort of nontechnical users, in turn driving our growth. Let me show you with a quick demo. MCP lets AI tools interact directly with Amplitude data. You can ask a vague question about your product inside any AI model and have it query Amplitude iteratively. Our MCP already has native connections to Claude, Cursor, and GitHub, with more to come soon. For this demo, I'm going to use Claude. I'm going to start with a simple prompt: give me high-level web traffic metrics. Claude will then get context, search web traffic metrics, and identify that during the week of September 21, we had a peak. I can then ask follow-up questions to drill down, investigating the September spike. What's driving this growth? Claude then accesses behavioral insights, checks traffic sources, marketing campaigns, and content performance. It shows that our webinar campaigns and the release of our product benchmark report drove this traffic. To get deeper insights, I'm going to ask what the downstream growth metric impacts are from these campaigns. Claude then queries the campaign dataset, downstream conversion funnels, and sales force metrics. It concludes that the September campaigns drove a higher number and quality of visitors to the site. Of course, I'm going to want to share these findings, so I can prompt it to create an Amplitude notebook for the growth team. In just a few minutes, customers can get deep research, insights, and a detailed shareable notebook that allows them to take action. In addition to the launch of MCP, we expanded the open beta for our AI agents. These agents continually monitor product data, detect anomalies, and surface insights automatically. In June, we launched our closed beta, and then two weeks ago, we opened the beta to all customers. Our focus is now on two agents. The first is the Dashboard Agent, which analyzes charts and proactively flags significant changes. The second is the Session Replay Agent, which reviews thousands of user sessions, detects points of friction, and then shows curated clips that highlight issues. Both are powered by the same behavioral data that MCP can access. They are already helping customers uncover opportunities and resolve issues faster. In addition, last week, we also introduced AI Visibility. As consumers turn to AI tools like ChatGPT, Claude, and Google's AI summary when they search, marketers are flying blind. They have no idea how their companies show up or rank within the results produced by these new tools. To solve that problem, we launched AI Visibility for free last week. Think of it as SEO for large language models (LLMs). It shows where a brand appears or doesn't across all major AI models, how they rank against competitors, and how they can improve their position. We saw a lot of excitement around the launch with our customers and on social media. The conversation about the future of AI Visibility is still going today on Twitter. Let me show you a quick demo of this too. Understanding how your products appear in AI responses and improving it will be the key to increasing awareness. With AI Visibility, customers can now see the percentage of mentions of their product in AI responses. They can also see competitor mentions versus their own and then topics by visibility. They can dig into prompts to see the exact questions customers are asking and how AI is answering. For example, when people ask LLMs for product-led growth tools, they mention Amplitude 90% of the time. Customers can also learn how to improve their ranking. I can use the Analyze page to see how AI interprets the existing content or run a series of simulated changes to test updates before publishing. AI Visibility tracks your brand and helps you turn that visibility into growth. Finally, next week, we will launch AI Feedback. This is our newest AI-native product based on the core offering from our Kraftful acquisition in July. We're going from acquisition to a new Amplitude product launch in four months. AI Feedback takes user feedback and information from multiple sources and turns it into insights a company can use. By bringing feedback, behavior, and action into a single platform, it helps teams hear customers and understand them. Let me show you with my last demo. AI Feedback is the new way to listen to users at scale and act on their feedback. AI Feedback collects input from all of our customers' feedback sources. You can link Zendesk tickets, Gong call transcriptions, App Store reviews, comments on Reddit and other social media, first-party surveys, and more with no engineering help. In this example, I have already set up AI feedback for a mobile app and connected it to reviews from the Apple App Store, as well as Google Play. Agentic AI processes the massive volume of unstructured data and sorts it into categories like you see here. Our proprietary AI analysis gives product teams the right level of detail. Users can see feature requests to help build a roadmap or can filter by topics like complaints to know which issues to address. Here, there are 26 mentions of reliable read, start, and alert query. I can click in to see specific comments for more detailed information and subtopics. For example, there are four mentions and notifications not syncing across devices. With Amplitude, customers can then turn that feedback into action. We can create a cohort of these 96 users watching session replays of how they interact with notifications or surveying them for more on what they need. Our innovation will accelerate from here. In addition to what I've just shown, over the next few quarters, we'll introduce new AI-first products like automated insights, a global chat assistant, and additional agents that extend our reach. These new capabilities expand who can use Amplitude and strengthen the value of the analytics platform overall. Every new product draws on the same behavioral dataset and feeds back into it, creating a single system of improvement. That's what makes our use and learn opportunity so large. Innovation is the biggest driver of long-term growth at Amplitude and our strongest moat in this AI-first world. Let's talk about customers. We had a great quarter for new and expansion deals with enterprise customers, including Bentley Systems, FanDuel, Thomson Reuters, Taco Bell, Global Radio, Empower, Granola, Algolia, and Gusto, among others. I'm going to highlight how a few of them are putting this all to work. Three examples stand out this quarter, each showing the power of the Amplitude platform in a different way. First is FanDuel. They continue to be a great example of platform consolidation at scale. FanDuel is constantly refining its experiences and tailoring them for millions of fans. Connecting real-time feedback to customer experience is critical to their success, and Amplitude powers that loop. FanDuel uses Amplitude end-to-end across multiple product lines from analytics to guides and surveys to session replay. That unified view helps their teams test, learn, and improve faster. Their expansion and renewal patterns remain among the strongest in our base. Second, Granola. This fast-growing AI start-up adopted Amplitude before launch after hearing about us through the AI ecosystem. Today, more than half the company uses Amplitude every day to understand how people use their product and where to iterate next. Granola ships new features quickly and relies on real-time feedback to guide product decisions. Their story is a great example of how AI-native companies are choosing Amplitude to accelerate growth and scale with confidence. Third is Bentley Systems, a global leader in design, construction, and infrastructure software. Bentley selected Amplitude as a single analytics platform across all products. The company previously relied on siloed legacy tools but needed one system to understand usage, drive adoption, and guide feature development. By activating historical data from Databricks and combining it with behavioral insights in Amplitude, Bentley can now test, learn, and implement improvements far more quickly across its portfolio. These stories all point to a common theme. From AI start-ups to global enterprises, customers are betting on Amplitude as the AI analytics platform that will help them thrive in this new era. We are at the beginning of redefining analytics as an AI-native system that learns, reasons, and acts. Over the next few quarters, we will bring a new wave of AI-native products to market that will reshape how companies use data to build better products. This is just the beginning of the AI era for analytics. I'll now hand it over to Andrew to walk through the financials.

Thank you, Spenser, and good afternoon, everyone. We've delivered another solid quarter of acceleration in our ARR, improved operational efficiency, and created greater durability in our future revenue base. Our customers are increasing their pace of innovation and in turn, need to understand how changes are being received, how to adapt, and how to implement those changes. As such, we believe Amplitude's importance to the enterprise is increasing. On our business, we have continued to perform against our strategy that we communicated at our Investor Day earlier this year. We've increased the value that our platform can deliver by adding Guides and Surveys, AI agents, our MCP server, and others. We've grown the base of our enterprises we are serving, the number of customers that are using multiple products, and the full platform. We've done all this while improving the operational efficiency of the business. We continue to improve the durability of our business as measured by improving our contract duration and remaining performance obligations, or RPO. This quarter, our average contract duration grew to nearly 22 months, up from 19 months just one year ago. Our RPO growth has improved from Q2, with current RPO growth year-over-year accelerating to 22% from 20% last quarter and long-term RPO growth accelerating to 78% year-over-year, up from 64% last quarter. This results in total RPO growth of 37%, accelerating from 31% last quarter. The growth in our RPO is a direct result of building a more repeatable and scalable go-to-market strategy, focused on enterprise customers. Turning to our third quarter results. As a reminder, all financial results that I'll be discussing, with the exception of revenue, are non-GAAP. Our GAAP financial results, along with a reconciliation between GAAP and non-GAAP results, can be found in our earnings press release and supplemental financials on the Investor Relations page of our website. Third quarter revenue was $88.6 million, up 18% year-over-year and 6% quarter-over-quarter. This quarter's growth benefited from better linearity in deal signings earlier in the quarter, growth in our services business, and the strong net new ARR growth we had in Q2. Total ARR increased to $347 million exiting the third quarter, an increase of 16% year-over-year and $12 million sequentially. Here are more details on the key elements of the quarter. We had a strong quarter for both new and expansion deals in the enterprise. Platform sales were also particularly strong. 39% of our customers now have multiple products, with 71% of our ARR coming from that cohort. The number of customers representing $100,000 or more of ARR in Q3 grew to 653, an increase of 15% year-over-year and up 19 customers since last quarter. In-period NRR progressed to 104%, led by cross-sell expansions. Gross margin was 76% for the third quarter, down 1 point from the third quarter of 2024 but up 1 point since last quarter. We continue to make progress on optimizing our hosting costs, driving multi-product contracts, and monetizing services engagements. And we will continue to look for opportunities to incrementally improve our gross margin over time. Sales and marketing expenses were 43% of revenue, a decrease of 1 point from the second quarter. We continue to focus on improving sales efficiencies, driving improvement through our changes in process, coverage, and expansion of enterprise customers. At the same time, we are investing for future growth, while balancing this incremental investment with efficiency gains. G&A was 13% of revenue, down 3 points from the third quarter of 2024. We expect G&A to improve as a percentage of revenue over time. R&D was 19% of revenue, up 3 points from the third quarter of 2024. We expect to continue to invest in the talent and the capabilities of our team to drive greater innovation in the future. Total operating expenses were $67 million or 75% of revenue, down 1 point sequentially. Operating income was $0.6 million or 0.6% of revenue. Net income per share was $0.02 based on 143.2 million diluted shares, compared to a net income per share of $0.03 with 131.3 million diluted shares a year ago. Free cash flow in the quarter was $3.4 million or 4% of revenue, compared to $4.5 million or 6% of revenue during the same period last year. In the third quarter, we managed our cash collections and made meaningful progress, shifting to contracts with annual payments in advance. Now, turning to our outlook. As Spenser laid out, the world of development, test, and ship is changing rapidly. Analytics and the use of data to understand outcomes and drive action will be more important than ever for enterprises. Our strategy remains consistent with our go-to-market. We will continue to focus on gaining new enterprise customers and driving cross-platform sales with our existing customer base. We also believe that with the release of our AI capabilities, the monetization of data ingested into our platform, and cross-sell opportunities of new products gives us the right strategy to align the value our customers receive with our growth opportunities and to grow our business in a profitable way. For the fourth quarter of 2025, we expect revenue to be between $89 million and $91 million, representing an annual growth rate of 15% at the midpoint. We expect non-GAAP operating income to be between $3.5 million and $5.5 million. And we expect non-GAAP net income per share to be between $0.04 and $0.05, assuming diluted weighted average shares outstanding of approximately 142.6 million. For the full year 2025, we are raising our revenue expectation for the full year due to the quarter's positive performance. We expect full year revenue to be between $340.8 million and $342.8 million, an annual growth rate of 14% at the midpoint. We are adjusting our range for the full year non-GAAP operating income to be between $0.5 million and $2.5 million, reflecting growth investments. We expect non-GAAP net income per share to be between $0.06 and $0.08, assuming weighted average shares outstanding of approximately 142 million as measured on a fully diluted basis. In closing, we continue to execute our strategy of growing our enterprise customer base, expanding multi-product attachment with our customers, and growing with additional leverage in our business model. This has only occurred through the focused execution of our employees and our relentless drive towards creating value for our customers. With that, we'll open it up for Q&A.

Thank you, Andrew. We will now turn to the Q&A session. Our first question will come from Koji Ikeda from Bank of America, followed by Patrick Schulz.

I wanted to ask on RPO. I look at ARR, nice growth there, but RPO, real nice acceleration of 37%, most added sequentially in a long time. Andrew, totally hear you on the repeatable and scalable enterprise aspect of the execution here. But I was hoping you could break it down a little bit by enterprise, mid-market, vertical, maybe even annual contract size and contract duration. What's really driving that 37% growth there?

You may remember, Koji, that at the start of the year, we put significant effort into resegmenting our customers and refocusing our sales approach on enterprise clients. We have a broader categorization, which we refer to as Strat in the enterprise. For clarification, we define enterprise clients as those with 1,000 employees or more or more than $100 million in revenue. During this process, we actively engaged in marketing initiatives to highlight how we are consolidating our position and how clients can leverage the Amplitude platform for greater value. When talking to clients, they often envision not just replacing a single tool but embarking on a multi-year journey to extract ongoing value as their businesses evolve. This has led to more strategic discussions and longer deal structures. I previously mentioned that our overall contract duration has increased to 22 months, and it is even longer in the enterprise segment. This is primarily due to many multi-year, million-dollar agreements that necessitate long-term commitments, which is positively affecting our remaining performance obligation (RPO). Achieving this requires our sales teams to remain highly focused on execution and align their incentives accordingly, and I can confidently say they have excelled in securing multi-year contracts and driving significant growth in our RPO.

And maybe a question here for Spenser. In the presentation, you talked about this, I'll call it, the build, ship, use and learn circle of life here. Where are enterprises today? Where are they investing now? And where are they really going to be investing in the future?

You mean, in product or in analytics?

In that circle. Are they investing more in the build process, the ship process? Are they yet to really start to invest in the use and learn side, and that's the real opportunity for you guys?

I think it's much earlier on the use and learn side, right? If you look at the state-of-the-art for how companies do this, it's literally you go ask, talk to a bunch of customers, you do a focus group, you send out a survey, you're getting lots of qualitative feedback. The point I am trying to make is that if you can master that quantitatively, that is so much more powerful because you can – actions are much more powerful than words. Users are great at describing the problem they have. But it's like that old great Henry Ford quote, if you just listen directly to what they do, they'd ask you for faster horses. And so, the companies like the Facebooks or the Netflixes of the world that have done a great job of that have this incredible edge over anyone else. And so, we see ourselves as bringing that infrastructure much broader. Now, to your question, it's much, much earlier there. I think we see a lot of excitement. Like I was just in Europe a few weeks ago, and every single customer wants to talk about, yes, how is my learning side going to get completely disrupted by AI. Like we’re already on coding. They’re having the developers use Cursor and Claude Code and a whole bunch of other coding AI tools. They want to know how the same is going to happen in analytics. And so, what I was presenting is like, hey, what's our vision for that future?

Our next question will come from Patrick Schulz from R.W. Baird, followed by Elizabeth Porter from Morgan Stanley.

Maybe first, just thinking about the growth for revenue and ARR, another very strong quarter. And looking at the Q4 guidance, there's some revenue deceleration implied there. Just wondering if you could provide a little bit more color on what went into that forecast. And maybe more broadly, there's always some trade-off between investing for growth and driving profits. But curious to hear how you guys are balancing these two as you head into next year, especially just given the velocity of innovation you guys are seeing.

So I'd tell you that our guidance is always based upon the lens of execution for us. And as we've gotten better and better at executing our enterprise play, that's given us a lot more visibility into future revenue, and it shows up in our RPO. And so, rather than go back on what has worked very well for us as we progressed this year, we're going to stick with that guidance pattern and stick with what we know we can go execute in the market, and we believe that will continue to deliver benefits for us. Now, on balancing growth with leverage, if you were a fly on the wall within the Amplitude offices, you'd find that we're often making debates – we have debates about when to make the right investment, how much leverage can we expect from it, and then how can we make sure that we are continuing to drive towards the expectations we set at Investor Day back in March. And so, it's always a little bit of a difficult conversation. But I think the teams have learned to manage within those constructs, and we're making the investments that really matter while still delivering progressions on our growth with leverage plan.

Yes. I mean, Patrick, I'll say you don't find – the bottleneck to growth is actually not a lot of time spent. It's about how can I retrain this team to be more effective. So Andrew and I and with Thomas have been looking at sales productivity and how do we drive that for next year. The teams have really stepped up and done a good job of how do we be really effective. You can get a lot of leverage from AI tooling in this world without a crazy amount of spend.

Okay. That's very helpful. Maybe just one quick follow-up too. Very impressive list of customer wins during the quarter. And one of your goals over the past year has been to improve the enterprise go-to-market motion. Just can you maybe talk about how some of these improvements have impacted the trends with initial deal wins? What are you seeing in terms of changes to sales cycles, size of initial lands, and maybe landing with multiple products?

Yes. I mean, as I kind of outlined in all three examples, I mean, I think we're doing everything across the board way better than we were a year or two ago. You're seeing many more multi-years, which is reflected in the RPO growth. You're seeing 71% on multiple products. That's a huge deal. You're seeing customers willing to just invest in analytics, invest in the whole platform. They're very excited about what we're doing on the AI side as well. And so, I got to give a lot of credit to the go-to-market teams for how they've built much stronger relationships with those. Even though I didn't speak to it too much, they've done a phenomenal job, and that's why you see ARR reacceleration, as well as all those other numbers. One other just data point to call out, we had a really broad-based set of seven-figure wins. It was about five seven-figure wins in Q3, which was just fantastic to see, everything from some of the enterprises, the very traditional enterprises I called out, all the way to – we actually had a foundational model company that we can't disclose who it is but signed for Amplitude. So it's just exciting to see kind of, hey, across the full spectrum, we're doing well.

Our next question will come from Elizabeth Porter from Morgan Stanley, followed by Willow Miller from William Blair.

Awesome. I think one of the really exciting parts about Agents is its ability to tie together multiple products across the Amplitude platform. And should we expect kind of a step function increase in multi-product adoption? I know that it was about 70% of ARR, but the customer base is still below 40%, which is a big opportunity. So how does the Agent strategy just overall accelerate that mix shift in the broader platform strategy?

Okay. So there's what we're doing today and then there's the future. What we're doing today, we are focused on the analytics adoption piece because more people using analytics, the more people sending us data, the more people querying that data, the more value we create, and that will naturally expand and lead to a whole bunch of these other use cases. So the two agents I talked about, the dashboard monitoring agent as well as the session replay agent, those are all kind of insights-level agents. Now, what we do have coming and will be in next year is we're going to be doing a lot more on the action side, so suggested experiments, as we showed in June on the last earnings call, where we come up with a strategy for how you can improve conversion on your website, suggested guides for you to send out to users, hey, you don't have a new user onboarding guide. We've created one for you. Do you want to go ahead and deploy that? Suggested cohorts of users to target with messaging. So I'd say today, on the Agents front, we're specifically focusing on the analytics and insight layer because that's where we're hearing the most pull from customers, but we'll add a whole bunch of action layer stuff as a fast follow-up.

Great. And then, just as a follow-up more on the financial side. As Amplitude moves further upmarket, should we expect there to be any seasonality in in-period NRR, just given we can have some of these quarters that are heavy in the enterprise deals? And how would you frame the cadence in the NRR trend and how it could evolve through the year?

So I'd say that everything is better with – in the enterprise. Our NRR is much higher than the overall average for the business. We still have cohorts in the SMB and mid-market that have higher churn rates. But as we get more – a higher and higher percentage of our ARR in the enterprise, NRR will continue to progress. And we expect that we'll see a continued progression in our enterprise content. As we delineated at our Investor Day back in March, we'll see that progression continue to go up. That drives better gross retention as well. And so, although we didn't see a big progression this quarter, the reality is, we have a lot of faith in our long-term expectations of being that 115% that I talked about last quarter.

Our next question will come from Willow Miller from William Blair, followed by Ian Black from Needham.

I'm Willow on for Arjun Bhatia. I believe, in your prepared remarks, you mentioned that you believe the new AI functionality like MCP and Agents can open up Amplitude to nontechnical users. Can you comment more on this? And could this expand your market opportunity?

Absolutely. I mean, the hard part – there are two hard parts in analytics today. One is you have to learn an analytics product. And so, as easy as we made it with Amplitude, you still have to learn our interface, what drop-downs, what type of charts to use, all of that sort of stuff. The other thing you have to learn, and this is the biggest bottleneck in analytics, is the data taxonomy that you have. And the problem with particularly product data taxonomies is they are huge. Like the average product has thousands of different things you can do in it. So, no one is going to be able to keep that in their head. The huge leverage point you get, which I showed in the MCP demo, is that you can start with a very vague question, like show me my onboarding funnel, and then it will look across your dataset to see, okay, which are likely the onboarding events, let me construct a funnel with them. And then, if you're not happy with the result, you can iterate with it. But the point is, you're not having to learn our interface or any analytics interface. You're also not really having to learn your data taxonomy. It's leveraging – it's doing the thinking and reasoning for you on specifying the query and constructing it and putting that back in a chart. So you're just getting the result and then kind of going back and forth with it. So I – so the answer is, highly yes. We've set really aggressive internal targets for next year for what we expect how we expect the adoption of Amplitude to grow because of what we're building.

Our next question will be by Ian Black from Needham, followed by Claire Gerdes from UBS.

Congrats on the great quarter. As you guys start to lap the switch to multi-year contracts that you started last year, is there an impact on sales productivity?

No, I don't think that – we certainly look at sales productivity both on a gross and a net basis. But I think that the opportunity for us to continue to drive expansions within our existing customer base is well over $150 million. We said something similar at our Investor Day when we had even fewer customers. We've done a pretty good job of adding new enterprise clients. And even at the rate that we're adding them, we still think that there's a large footprint within each one of them where we can show great expansion opportunities.

Awesome. And then, you mentioned customers increasingly viewing you as key strategic partners. Is there an opportunity to expand your service partner network as you go deeper within your customer base?

Yes. That is one of the other growth engines that is somewhat nascent for us today. I think that as Amplitude becomes increasingly important to enterprise clients, you'll start to see more and more partners look at ways in which they can develop on our platform and create their own value add. And that's something that, over time, we believe will happen.

Our next question comes from Claire Gerdes from UBS, followed by Jackson Ader from KeyBanc.

I'm on for Taylor McGinnis. Great to see the results today. I wanted to ask about some of the newer AI products that you're offering. I know some are still in beta. But as we think about where you are with those and balancing adoption and monetization in the future, I know, again, still very early, but is it more that you're wanting customers to adopt and get familiar and we can expect more of those free at this time? Or how are you thinking about that right now?

Yes. Adoption is our key focus. They drive a bunch of value. Customers will track more data. They'll use that data a lot more broadly across more users, and that will very naturally lead to more value and upsells and everything else. I mean, if you look at our ASP, we're hovering around $400,000 a year. In a lot of companies, we are the largest spend after their cloud hosting. So we have no problems already commanding a premium price point. The key is to consistently deliver value and make that barrier lower and lower, which is what we're doing with MCP and Agents and all of the stuff that's targeted at nontechnical users.

And then, just maybe a quick follow-up, a bit broader, but can you just comment on the selling environment right now? Obviously, still a lot going on, but you're putting up a great acceleration. So just if you could comment on that, that would be great.

Yes. I mean, I think there's been – I don't think there's any change quarter-to-quarter. There's a continued cost consciousness among all customers, the same way it's been for the last few years. I think what they're really excited to see is like, hey, does this AI stuff work? Is it legit? Every B2B company under the sun is like pitching them on AI this, that or the other thing. And so, what I always say is show me the demo. So that's why I kind of did that on today's call. And they're really, really – yes, a lot of customers are very, very excited about that. They want to know how can I get five, ten, or even more times leverage with leveraging AI Agents, MCP, and get a lot more insights than I would doing all of that work manually.

Our next question comes from Jackson Ader at KeyBanc, followed by someone from Citi.

The first one is kind of a product question. One of Francois' major initiatives, I guess, if you want to call it that, is a tighter integration between customer feedback and the product roadmap and kind of getting that flywheel going. So I'm curious, what are customers – agents are rolled out. You've got AI features and functionalities. What are customers kind of looking for as we head into 2026 that might be able to continue to compound the growth that we've seen?

Yes. I mean, look, just to be really clear, we're in the really early days of Amplitude in this category. I think – let's see what would I call out. So first, take all the AI stuff and set it to the side. Just with the enterprise execution, plus the expanding breadth of the platform, that already, we expect to continue to accelerate us to the ranges that we talked about on the Investor Day earlier this year, so beyond the 20%, which, in my mind, is kind of the bare minimum for this category. And then, you add how this category gets dramatically reshaped by AI, as I've been outlining, like the same thing that happened to software engineering with Cursor and with a whole bunch of other AI coding products, that is going to happen in analytics, and we see what that opportunity is. We're going to go really aggressive after it, and there is a lot of appetite to adopt that. So I'm very excited and bullish on it. And I think as we see customers adopt and use and get value on that, that will all translate downstream to Amplitude's revenue growth.

Okay. All right. Great. And then, the follow-up question is just on the split between – or I guess, not split, but just product analytics versus marketing analytics. I know we're getting into kind of new budget territories with the marketing piece. At what point does that split become material enough to where I'm sure that the high growth rates coming from marketing analytics is able to contribute to a material amount of your overall revenue? Or are we there already?

It's still early in this process. There are customers who have completely transitioned from traditional marketing analytics products to Amplitude. For example, DECATHLON is one, and another is Realtor. They are transitioning because they find that solutions like Google Analytics or Adobe are not meeting their needs, prompting them to switch to Amplitude. We still have more developments planned in this area. While we haven't shared specific details about our future initiatives, we anticipate significant growth in 2026 that will help us capture a larger portion of the marketing budget, contributing to our overall growth.

Our next question will come from someone at Citi, followed by Clark Wright from D.A. Davidson.

Spenser, the launch of AI Agents over the summer was quite significant. With improved availability today, could you provide an update on customer adoption? What are some of the most effective use cases you're observing and the ROI for customers? Additionally, do you have any updates on the pricing monetization efforts for AI Agents as they progress?

Yes. So let me hit the pricing one first. So, as I said to Claire earlier, focus is just let's make Amplitude more valuable. Like we command already an extraordinarily high price point with a lot of our customers. And so, we're not looking to squeeze them for more. We just want to give them a lot of value. So I think it's a common misconception – sorry, misunderstanding about our business relative to other SaaS is, we already command like very, very high price points, which is great, but you obviously want to make sure you’re consistent about delivering the value. In terms of what use cases work very well, so the two I highlighted, dashboard monitoring and session replay are the big ones that customers use a lot of. They – I think customers are not ready to trust AI agents to come up with a whole strategy of wholesale for them and then recommend a series of actions. But they are very excited about using things that can monitor the data and just proactively tell them – like this is, in a lot of ways, the holy grail of analytics, like can you tell me when something has changed in my data and deliver that insight as to why it changed? And so, in the MCP demo, we have a – I didn’t do the demo today, but we have a dashboard monitoring agent that can do the exact same thing, delivering kind of a root cause analysis saying, 'Hey, you had a spike in September, and here are the particular causes: the product benchmark report and this other launch that you did.' And customers are using and getting a bunch of value, and that's what our focus is in the short term. And then, same with session replay. With session replay, you'll have often millions of sessions, and it's like you can't watch them all. So how can you have AI summarize the highlights for you? And then, you can maybe watch 3 or 4 that are relevant you're like, 'Oh, okay, I can see how the product experience can improve if we make these changes to the app.'

Got it. That's clear. Andrew, this question is for you. It seems that the guidance indicates a stronger momentum as we head into Q4. Can you help us understand the dynamics you are observing that led to a larger than expected guidance increase this quarter? Also, how much conservatism do you perceive in the guidance, and what is the outlook for the pipeline as we approach year-end?

Well, as we move our business more towards pursuing enterprise opportunities, you still – you have a pattern like many enterprise companies, and we're a calendar year company. So, all of our reps have end-of-year incentives to achieve and exceed their targets. And so, we typically have our strongest quarter in Q4. So that's the first thing. Pipelines and the maturity of those pipelines are something we look at very closely when we're putting together our guidance. What we've seen so far gives us confidence. And it would be remiss of me if I didn't say the RPO gives us great visibility into future revenue periods. And the more that the sales team executes on driving greater relationships with clients, more strategic agreements, we're getting those multi-year agreements booked. And so, as I said earlier, the guidance is based on the lens of execution for us, and we've pursued that same philosophy throughout this year, and it's led to strong performances. So we're going to continue that.

And our last question comes from Clark Wright from D.A. Davidson.

Spenser, your product teams have been hard at work this quarter.

Every quarter. But yes, we're accelerating.

Yes. And the pace of innovation has been great to see. I was wondering if you could talk about how you think right now about building versus buying incremental capabilities at this point in time in order to keep up this pace of innovation.

Yes. So you always want to be able to do both. Like I think experiment – we actually looked for a while for the right team to come in but ended up deciding to be able to build was the faster way to get that to market because there wasn't a company at the time that was the right fit. Conversely, like we buy when we think it makes sense, so Activation back in 2022, Guides and Surveys, now AI Feedback, that made a ton of sense. So you’re kind of always doing both. I think the important part is we're not religious. And so, whatever gives us the shortest path to market, like with AI Feedback, that would have taken us a year – I mean, I'd like to say only a year, but the reality is probably more like 2 to get to the same point a state-of-the-art product like Kraftful was. The same with Command on Guides and Surveys; that would have taken us 2 to 3 years, no question, at least to build internally. So it's just a much faster path to market. So we're always looking at both. The other thing I want to point out is that I think – I mean, I've been really excited to work with the founders that we have. Yana from Kraftful has done a phenomenal job of kind of educating me about AI and educating a lot of the rest of the company. Same with Enzo and Ferruccio from June, same from Frank and Eric from Inari; like they've all done a phenomenal job of like they've been building in this space in an AI-native way for a bunch of years. And so, as we're looking to change the makeup of the team to be able to build – to look much more like an AI start-up, then like they're kind of the tip of the spear on that. And so the explosion of products you've seen has come from ideas seeded by different folks from that group. So just as an example, like AI Agents was led by James Evans from Command, and then now Frank from Inari is taking it. And then, like Yana is working on LLM analytics, as well as a bunch of automated insights that we haven't even got to talk about yet. And then, you combine that with folks who have been at Amplitude for a long time, and you get just incredible results. So, yes, you kind of – you pair a lot of long-time product veterans at Amplitude with some folks who have been in the AI ecosystem, and you're just able to be really aggressive about the innovation.

Awesome. And then, just in terms of monetization, you talked about the fact that you're going to be giving away some of these features. How do you think – are events going to be the denominator going forward in order to look at really kind of pricing and packaging? Or is there another way to think about that, that we should be considering going forward?

Okay. So this is a topic I'm very passionate about. A lot of people in the AI space talk about outcomes-based pricing. I think it is an awful idea because you spend a lot of time arguing with your customers about, was that a good outcome? It’s like – what works much better is the same meter-based pricing that you had in SaaS. So whether that's, in our case, events, some seats, some cases like tickets handled or size of customer base or what have you. But the customers have been most receptive. Like they don’t want to feel like they’re getting screwed. And like whenever you try to introduce a new metric or a new way of doing pricing, it raises a huge number of red flags. Whereas if you go with something they've already been used to using like events and data volume, like they're extremely comfortable with that. And so, we're not – yes, we're not planning – while I think there are things we're going to continue to improve about our pricing to better make sure we have a fair exchange of value between us and our customers, we don't want to – we actually are looking to simplify our meters, and that's something we're going to be coming out with next year where we're just going to focus on the events piece.

Great. Thank you, Clark. That will conclude our third quarter earnings call. Thank you for your time and interest, and we look forward to seeing you on the road this quarter as we attend conferences hosted by UBS and Needham. Thank you.

Thank you, guys.