Amplitude (AMPL) Q3 2025 Earnings Call Transcript

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Date

Wednesday, November 5, 2025 at 5 p.m. ET

Call participants

Chief Executive Officer — Spenser Skates

Chief Financial Officer — Andrew Casey

Head of Investor Relations — John Streppa

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Takeaways

Revenue -- $88.6 million in revenue for Q3 2025, up 18% year over year and up 6% sequentially from Q2 2025, surpassing previously issued guidance.

Annual Recurring Revenue (ARR) -- $347 million in annual recurring revenue as of Q3 2025, representing 16% year-over-year growth in ARR and a $12 million sequential increase.

Non-GAAP Operating Income -- $600,000 in Q3 2025; operating margin (non-GAAP) was 0.6% of revenue.

Customers with $100,000+ in ARR -- 653 customers with more than $100,000 in ARR, up 15% year over year and up 19 customers from last quarter.

Multiproduct Adoption -- Multiproduct customers contributed 71% of total ARR, while 39% of customers used multiple products.

Gross Margin -- 76%, down one point from Q3 2024 but up one point sequentially from Q2 2025.

Free Cash Flow -- $3.4 million in free cash flow for Q3 2025, equating to 4% of revenue, compared to $4.5 million or 6% of revenue in Q3 2024.

Net Income per Share (Non-GAAP) -- $0.02 based on 143.2 million diluted shares, versus $0.03 on 131.3 million diluted shares in Q3 2024.

Remaining Performance Obligations (RPO) -- Total RPO grew 37% year over year, accelerating from 31% growth in Q2 2025; current RPO growth was 22% year over year and long-term RPO growth was 78% year over year.

Average Contract Duration -- Increased to nearly 22 months, up from 19 months a year ago.

Net Revenue Retention (NRR) -- In-period NRR reached 104%, largely driven by cross-sell expansions.

Sales & Marketing Expenses -- 43% of revenue (non-GAAP), down one point sequentially from Q2 2025.

Research & Development Expenses -- 19% of revenue, up three points from 2024.

General & Administrative Expenses -- 13% of revenue, down three points from 2024 (non-GAAP).

Q4 2025 Revenue Guidance -- Anticipated at $89 million to $91 million in revenue for Q4 2025.

Full-Year 2025 Revenue Guidance -- Raised to $340 million to $342 million; midpoint reflects 14% annualized growth.

Full-Year 2025 Non-GAAP Operating Income Guidance -- Adjusted to a range of $500,000 to $2.5 million (non-GAAP) for the full year, impacted by growth investments.

Full-Year 2025 Net Income per Share Guidance (Non-GAAP) -- Projected between $0.06 and $0.08, assuming 142 million diluted shares.

AI Product Launches -- Public availability of MCP server announced, enabling AI agents to interact directly with Amplitude data.

AI Agent Expansion -- Open beta for AI-powered dashboard and session replay agents released to all customers two weeks prior to the call.

AI Visibility -- Launched as a free product for tracking brand mentions and rankings within major AI platforms and LLMs.

AI Feedback -- Scheduled to launch next week; converts user feedback from multiple sources into product insights and action items.

Seven-Figure Deals -- Five seven-figure wins recorded, spanning traditional enterprises and foundational AI companies.

Notable Customer Wins and Expansions -- Bentley Systems, FanDuel, Thomson Reuters, Taco Bell, Global Radio, Empower, Cranola, Algolia, and Gusto included new or expanded enterprise agreements.

Summary

Amplitude (NASDAQ:AMPL) reported accelerating enterprise momentum with substantial year-over-year and sequential increases in core financial metrics, highlighted by 37% total RPO growth and a sharp rise in average contract duration. Management credited deeper engagement with large enterprise clients and multiyear, million-dollar contracts as the primary drivers of contract and RPO expansion. Product innovation was a focal point, evidenced by recent launches of AI-driven MCP server capabilities, expanded AI agent functionality, the introduction of AI Visibility for brand management within LLMs, and the impending arrival of AI Feedback derived from the Craftful acquisition. Strategic guidance for both Q4 and full-year 2025 was raised following broad-based enterprise wins and a rapidly growing base of multiproduct customers, with management emphasizing the durability and scalability of the go-to-market motion.

Chief Executive Officer Skates stated, "Innovation is the biggest driver of long-term growth at Amplitude, and our strongest moat in this AI-first world."

Chief Financial Officer Casey reported that long-term RPO grew 78% and current RPO 22% year over year, both accelerating from Q2 2025 rates.

Enterprise-focused sales execution led to seven-figure deals across both legacy and AI-native customers, supporting contract duration growth.

AI enhancements released during the quarter have broadened Amplitude’s addressable user base to include nontechnical audiences, with management citing aggressive adoption targets.

Multiproduct attach reached 71% of ARR, demonstrating successful cross-sell of new platform functionalities.

Cost structure continued to improve, with sales & marketing and G&A declining as percentages of revenue, even as R&D investments increased to support AI-driven innovation (all percentages non-GAAP).

Management indicated sustained cost consciousness among customers, but also heightened interest in substantial AI-enabled efficiency gains from new platform capabilities.

Industry glossary

MCP Server: A middleware API developed by Amplitude enabling AI agents to interact with all Amplitude analytics functions without direct use of the UI or prior knowledge of customer-specific data taxonomies.

AI Agent: Autonomous software components leveraging machine learning to monitor analytics data, detect anomalies, and surface actionable insights automatically for Amplitude platform users.

RPO (Remaining Performance Obligations): The total dollar value of contracted future revenues yet to be recognized, considered a key visibility and durability metric in SaaS business models.

Session Replay Agent: An AI-powered tool that reviews user sessions to detect product friction points and curates highlight clips for product teams.

AI Visibility: A feature designed to reveal the mention and ranking of customer brands within responses from large language models and generative AI search engines.

AI Feedback: A forthcoming Amplitude feature that aggregates and analyzes user feedback from sources such as app reviews, support tickets, and social media using AI to surface product issues and opportunities.

Multiproduct Attach: The practice or resulting metric of customers purchasing and deploying more than one product within Amplitude’s platform, used as an indicator of cross-sell effectiveness.

In-period NRR (Net Revenue Retention): A measure of recurring revenue retained and expanded from existing customers within a specified reporting period, exclusive of new logo additions.

Full Conference Call Transcript

Spenser Skates: Good afternoon, everyone, and welcome to Amplitude's third quarter 2025 earnings call. Today, I'm gonna 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 $600,000. Customers with more than $100k 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 multiyear contracts. And we're winning the category with multiproduct 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 product.

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 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 gonna use Claude. I'm gonna start with a simple prompt, "Give me high-level web traffic metrics over the last few weeks." Claude will then get context, search web traffic metrics, and then it's identified that during the week of September 21, we've had a peak.

I can then ask follow-up questions to drill down. "Investigate 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 gonna ask, "What are the downstream growth metric impacts by these campaigns?" Claude then queries the campaign dataset, downstream conversion funnels, and Salesforce metrics. It concludes that the September campaigns drove a higher number and quality of visitors to the site. Of course, I'm gonna wanna share these findings, so I can prompt it to create an Amplitude notebook for the growth team.

So in 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 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 Craftful acquisition in July. We're going from acquisition to 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. AgenTeq 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, like, top 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 on subtopics.

For example, there are four mentions of 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, 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, Cranola, Algolia, and Gusto among others. I'm gonna 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 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 startup adopted Amplitude before launch after hearing about us through the AI ecosystem.

Today, more than 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 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 its 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 and 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 startups 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.

Andrew Casey: Thank you, Spencer, 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 the 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 our platform can deliver, 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 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 from 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 on our website. Third quarter revenue was $88.6 million, up 18% year over year, 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 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 one point from 2024, but up one point since last quarter. We continue to make progress on optimizing our hosting costs, driving multiproduct 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 one 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 incremental investment with efficiency gains. G&A was 13% of revenue, down three points from 2024. Expect G&A to improve as a percentage of revenue over time. R&D was 19% of revenue, up three points from 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 one point sequentially. Operating income was $600,000 or 0.6% of revenue.

Net income per share was 2¢ based on 143.2 million diluted shares compared to net income per share of 3¢ on 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 Spencer 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 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 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 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 million and $342 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 $500,000 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 multiproduct attach 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. Over to you, John.

John Streppa: Thank you, Andrew. We will now turn to Q&A. For the sake of time, please limit yourself to one question and one follow-up. Our first question will come from the line of Koji Ikeda from Bank of America, followed by Patrick Schultz. Koji, your line is now open.

Koji Ikeda: Yeah. Hey, guys. Thanks so much for taking the questions. I wanted to ask on RPO. You know, 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 of contract duration? You know, what's really driving that 37% growth there?

Andrew Casey: You may recall, Koji, that back in the beginning of the year, we made a lot of efforts at resegmenting our customers, refocusing our sale coverage, on the enterprise group of clients. And we even have a stratification that's even larger than that. We call it Strat in the enterprise. And for those who don't remember, we define enterprise clients as anyone who has a thousand employees or more or over $100 million in revenue. And when we did that, we really had a lot of marketing efforts, focused efforts to show how we are consolidating the space. How we could increasingly leverage the power of the Amplitude platform, how they get greater value.

And I would tell you when you have those conversations with clients, they often look to not just a single tool replacement, but rather a multiyear journey of how they're gonna continue to drive value as their business changes, as their business grows. And that's led to more strategic conversations and thus, the deal constructs. Which have more duration to them. I mentioned earlier, contract duration has increased overall to 22 months. I will tell you in the enterprise space, it's even larger. And the reason is because so many of those multiyear, million-dollar contracts result in multiyear commitments. And that's driving our RPO. Now, you don't do that without getting the sales teams very focused in an execution way.

And aligning incentives approach lead to drive those outcomes. I would tell you they've done a great job in multiyear contracts and making sure that our RPO is growing quite rapidly.

Koji Ikeda: Thank you. Thank you for that. And maybe a question here. For Spencer, you know, in the presentation, you talk about this, I'll call it, the build ship use, and learn circle of life here. Where are enterprises today? Circle of life. Absolutely. Circle of life. Yeah. Where are enterprises today? You know, where are they investing now, and where are they really gonna 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 invest in the use and learn side? And that's the real opportunity where you guys yep.

Spenser Skates: Yeah. 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 know, 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 you know, actions are much more powerful than words. Users are great at the problem they have, you know, but it's like that old great Henry Ford quote.

If you just listen directly to what they do, they'd ask you for fast horses. And so the companies like the Facebooks or the Net 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 broadly. 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, yeah, how is my learning side getting completely disrupted by AI? We're already on it on coding.

You know, they're having the developers use cursor and Claude code and a whole bunch of other AI coding tools. They wanna know how the same is gonna happen in analytics. And so what I was presenting is like, hey. What's our vision for that future?

Koji Ikeda: Got it. Thank you so much. Thanks, guys. Thanks for taking the questions.

John Streppa: Great. Thank you, Koji. Our next question will come from Patrick Schultz from RW Baird, followed by Elizabeth Porter from Morgan Stanley. Go ahead, Patrick.

Patrick Schultz: Thanks. Appreciate you guys' time this afternoon. Maybe first, just thinking about the growth for revenue in 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 investment 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.

Andrew Casey: 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 progress this year, we're gonna 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 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 or 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.

Spenser Skates: Yeah. I mean, Patrick, I'll say you don't find the bottleneck to growth is actually not a lot of times 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.

Patrick Schultz: Okay. That's very helpful. Maybe just one quick follow-up to a 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 land, and maybe landing multiple products?

Spenser Skates: Yeah. I mean, as I kinda outlined in all three examples, I think we're doing everything across the board way better than we were a year or two ago. You're seeing many more multiyears, which is reflected in that 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 gotta 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 7-figure wins. It was about $5.07 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 up for Amplitude. So it's just exciting to see kind of, hey. Across the full spectrum, we're doing well.

Patrick Schultz: Awesome. Appreciate it, guys. Thank you.

Andrew Casey: Great.

John Streppa: Thank you, Patrick. Our next question will come from Elizabeth Porter from Morgan Stanley followed by Willow Miller from William Blair. Go ahead, Elizabeth.

Elizabeth Porter: Awesome. Thank you so much. I think one of the really exciting parts about agents is its ability to tie together multiple products across the Amplitude platform. Yes. And should we expect kind of a step function increase in multiproduct adoption? I know that it would about 70% of ARR, but the customer base is still below 70, which is a big opportunity. So how does the agent strategy just overall accelerate that mix shift in the broader platform strategy?

Spenser Skates: 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 the 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 lead to a whole bunch of these other use cases. You know? 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 gonna be doing a lot more on the action side.

So suggested experiments, you know, 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 wanna go ahead and deploy that? Suggested cohorts of users to target with messaging? So I'd say today on the AI 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.

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

Andrew Casey: So I'd say that everything is better within the enterprise. You know, 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 a 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. You know, 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.

John Streppa: Thank you. Great. Thank you, Elizabeth. Our next question will come from Willow Miller from William Blair followed by Ian Black from Needham. Go ahead, Willow.

Willow Miller: Hi, team. I'm Willow on for Arjun Bhatia. Thanks for taking our question. 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?

Spenser Skates: Oh, absolutely. I mean, the hard part there's 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 an interface. What dropdowns, what type charts to use, all of that sort of stuff. The other thing you have to learn, this is the biggest bottleneck, in analytics, is the data taxonomy that you have. And the problem with product data taxonomies is they are huge. Like, the average product has thousands of different things you can do in it, so no one's gonna 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. 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, you know, 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 kinda going back and forth with it. So the answer is highly yes. We've set really aggressive internal targets for next year. For what we expect the how we expect the adoption of Amplitude to grow because of what we're building.

Willow Miller: Awesome. Thank you.

John Streppa: Thank you, Willow. Our next question will be by Ian Black from Needham. Followed by Claire Gurtis from UBS. Go ahead, Ian.

Ian Black: Hi. Congrats on the great quarter. As you guys start to lap the switch to multiyear contracts that you started last year, is there an impact on sales productivity?

Andrew Casey: 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 had said something similar at our Investor Day. When we had even fewer customers. We do a 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.

Ian Black: 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?

Andrew Casey: Yeah. 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.

Ian Black: Awesome. Thank you.

John Streppa: Thank you, Ian. Our next question comes from Claire Gertz from UBS. Followed by Jackson Ader from KeyBanc. Go ahead, Claire.

Claire Gertz: Hey, Ed. I'm on for Taylor McGinniss. Thanks for taking the and, great to see the results today. I wanted to ask you 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 you know, 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, you know, free at this time? Or how are you thinking about that right now?

Spenser Skates: Yeah. Adoption is our key focus. Like, 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, you know, 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 be able 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.

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

Spenser Skates: Yeah. I mean, I think there's been I don't think there's any change quarter to quarter. If there's a continued cost consciousness among all customers, there's the same way it's been for the last few years. I think what they're really to see is like, hey. Does this AI stuff work? Is it legit? You know, 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 kinda did that on today's call. And they're really, really you know? Yeah. A lot of customers are very, very excited about that.

They wanna know how can I get, you know, five, 10, even more times leverage, with, you know, leveraging AI agents, MCP, get a lot more insights than I would doing all of that work manually?

Claire Gertz: Awesome. Thanks.

John Streppa: Thank you, Claire. Our next question comes from Jackson Ader at KeyBanc. Followed by Yituan Wang from Citi. Go ahead, Jackson.

Jackson Ader: Great. Good to see you guys. Thanks for taking our questions. The first one is kind of a product question. One of Francois's major initiatives, I guess, if you wanna call it that, is a tighter integration between customer feedback and the product roadmap. And kinda getting that flywheel going. So I'm curious, what are customers at you know, agents are rolled out. You've got AI features and functionalities. What are customers kinda looking for as we head into 2026 that might be able to, like, continue to compound the growth that we've seen.

Spenser Skates: Yeah. 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, you know, 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, you know, to the ranges that we talked about on the Investor Day earlier this year, you know, so beyond the 20%, which in my mind is 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 gonna happen to analytics and you know, we see what that opportunity is. We're gonna go really aggressive after it, and there is a lot of appetite to adopt that. So, you know, I'm very excited and bullish on it, and I think you know, as we see customers adopt and use and get value on that, that'll all translate downstream to Amplitude revenue growth.

Jackson Ader: Okay. Alright. 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 you're you know, we're getting into kinda new budget territories with the marketing piece. Totally. At what point does that split become material enough to where I'm sure that you know, the high growth rates coming from marketing analytics is able to contribute to, like, a material amount of your overall revenue. Or are we there already?

Spenser Skates: No. No. It's early on it. I mean, there's customers that have switched off of legacy marketing analytics products and moved wholesale to Amplitude. Like, Decathlon's one, realtor's another. You know? There's a few that do that are, saying, hey. Google Analytics or Adobe is not working well enough, so let me move on to something like an Amplitude. Now there's still more for us to build there, and we're gonna be we haven't really talked about what we're gonna be doing there, but there's we're gonna be doing a lot in 2026 that will allow us to capture a significant amount of the marketing budget and have that contribute to growth.

Jackson Ader: Got it. Thank you.

John Streppa: Thanks, Jackson. Our next question will come from Yichuan Wang from Citi followed by Clark Wright from D. A. Davidson. Line is open.

Yichuan Wang: Hi. Thanks for taking the question here. So Spencer, the AI agent launch over the summer was, like, pretty big fun fair. OSF. So today, we've better availability. Could you kinda give us an update on how customer adoption has been? What are some of the most effective use cases you are seeing and ROI from customers? And then also if there's any update on pricing monetization for AI agent as it goes better. Thanks.

Spenser Skates: Yeah. Yeah. 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 already command an extraordinarily high price point with a lot of our customers, and so we're not looking to squeeze them for more. We just wanna give them a lot of value. It's I think it's a common misunderstanding about our business relative to other SaaS. As we already command, like, very, very high price points. Which is great. You know? But you obviously wanna 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. I think customers are not ready to trust AI agents to come up with a whole strategy 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 dash I didn't do the demo today, but we have a dashboard monitoring agent that can do the exact same thing at that. Deliver kind of a root cause analysis saying, hey. You had a spike in September, and you know, here are the particular causes, the product benchmark report, and this other launch that you did. And that, you know, customers are using and getting a bunch of value, and that's what our focus is in the short term. And then same with the 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, you know, maybe watch three or four that are relevant to be like, oh, okay. I can see how the product experience can improve if I make these changes to the app.

Yichuan Wang: Got it. That's clear. Andrew, maybe one for you. I think the guide implies there's, like, a stronger momentum going into Q4. Can you kinda help us understand the dynamic that you're seeing that have made you raise the guide bigger than a beat in the quarter and kind of how much conservatism you see in the guide and how is the pipeline going to your end? Thanks.

Andrew Casey: Well, as we moved our business more towards pursuing enterprise opportunities, you still 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, that gives us confidence. And it would be remiss of me if I didn't say, you know, our 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 multiyear 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 gonna continue that.

Yichuan Wang: Thank you. Congrats on the great result.

Willow Miller: Thank you for the question. And our last question comes from Clark Wright from D. A. Davidson. Go ahead, Clark.

Clark Wright: Thanks. Spencer, your product teams have been hard at work this quarter. Every quarter, but yes, we're accelerating. Yeah. 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.

Spenser Skates: Yeah. So you always wanna be able to do both. Like, I think experiment you know, we actually look for a while for the right team to come in, but ended up deciding 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've bought when we think it makes sense. So our activation back in 2022, guides and surveys, now AI feedback. That made a ton of sense. So you're kinda 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 two to get to the same point a state-of-the-art product like Craftful was. And the same with command on guides and surveys. That would have taken us, you know, two to three years, no question at least to build internally. So it's just a much faster path to market. So you're always looking at both. The other thing I wanna point out is that I think I mean, I've been really excited to work with the founders that we have.

You know, on our craft from Craftful has done a phenomenal job 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, 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, you know, to look much more like an AI startup than, you know, 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, you know, different folks from that group. So as just as example, like, AI agents was led by James Evans from Command and then now Frank from Anari's taking it, and then like, Yana's working on LLM. Analytics as well as a bunch of automated insights that we haven't even got to talk about yet. You know? And then you combine that with folks who have been at Amplitude for a long time, and you get just incredible results.

So, like, yeah, you pair a lot of long-time product veterans into Amplitude with some folks who have been in the AI ecosystem, and you're just able to be really aggressive about the innovation.

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

Spenser Skates: 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? Was 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, you know, some seats, some cases, like, you tickets handle, their size of customer base, or what have you. But the customers have been most receptive. Like, they don't wanna 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, yeah, we're not planning. You know? While I think there are things we're gonna continue to improve about pricing to better make sure we have a fair exchange of value between us and our customers, we don't wanna intrude you know, we actually are looking to simplify our meters.

And that's something we're gonna be coming out with next year where we're just gonna focus on the events piece.

Clark Wright: Awesome. Thank you.

John Streppa: 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.

Spenser Skates: Thank you, guys.

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