AMPL

Amplitude’s Q2 results reflected continued momentum in its transition toward an AI-driven product development platform, with management attributing growth to increased adoption of AI-native capabilities and expanded enterprise relationships. CEO Spenser Skates noted that both AI-native startups and large enterprises contributed to growth in customers with over $100,000 in annual recurring revenue. The integration of Statsig, an experimentation and feature management solution, enabled Amplitude to extend its reach into engineering-focused buyers, while improvements in pricing and packaging simplified customer onboarding and cross-selling. Management emphasized that greater customer engagement with AI features has led to increased data analyses and platform usage, supporting revenue growth and platform durability. Is now the time to buy AMPL? Find out in our full research report (it’s free). Revenue: $100.9 million vs analyst estimates of $98.16 million (21.2% year-on-year growth, 2.8% beat) Adjusted EPS: -$0.01 vs analyst estimates of -$0.01 (in line) Adjusted Operating Income: -$1.45 million vs analyst estimates of -$2.48 million (-1.4% margin, 41.4% beat) The company lifted its revenue guidance for the full year to $409.2 million at the midpoint from $400 million, a 2.3% increase Management raised its full-year Adjusted EPS guidance to $0.07 at the midpoint, a 55.6% increase Operating Margin: -34.9%, down from -32.5% in the same quarter last year Customers: 5,200 Net Revenue Retention Rate: 105%, down from 106% in the previous quarter Annual Recurring Revenue: $410 million (22.4% year-on-year growth, beat) Billings: $131 million at quarter end, up 27.3% year on year Market Capitalization: $1.59 billion While we enjoy listening to the management’s commentary, our favorite part of earnings calls is the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention. Mark Cash (Raymond James): Asked if Wade could shift customers from bespoke agents to a unified AI-native platform. CEO Spenser Skates explained that AI is merging roles across engineering, product, and design, fundamentally changing buyer personas and expanding the addressable market. Jackson Ader (KeyBanc): Questioned the impact of operating expense leverage on organic growth. CFO Andrew Casey responded that revenue growth remains the primary driver of profitability and that margin gains will come from gross margin improvements and expense discipline. Scott Berg (Needham): Inquired about customer awareness of new modules and the pace of Statsig integration. Skates acknowledged the need for better customer education and highlighted progress in integrating Statsig and ramping field enablement. Billy Fitzsimmons (Piper Sandler): Asked about the cross-sell opportunity between Amplitude and Statsig. Skates noted the larger opportunity is to bring Statsig to Amplitude’s customer base, as more traditional product management buyers look to adopt AI-native practices. Clark Wright (DA Davidson): Sought clarity on growth drivers behind $100k+ customer additions. Casey attributed growth to both Statsig adds and continued momentum from new enterprise logos, with AI-driven experimentation and multi-product adoption supporting expansion. In the quarters ahead, the StockStory team will monitor (1) the pace of adoption and monetization of new AI-native products like Wade, (2) progress toward optimizing Statsig’s hosting environment and restoring gross margin levels, and (3) the effectiveness of cross-selling and multi-product adoption among existing enterprise customers. Additionally, we will track execution on platform education and customer enablement efforts as key indicators of future growth. Amplitude currently trades at $12.56, up from $10.01 just before the earnings. Is there an opportunity in the stock? Find out in our full research report (it’s free for active Edge members). ONE MORE THING: Top 5 Growth Stocks. The biggest stock winners almost always had one thing in common before they ran. Revenue growing like crazy. Meta. CrowdStrike. Broadcom. Our AI flagged all three. They returned 315%, 314%, and 455%, respectively. Find out which 5 stocks it’s flagging this month — FREE. Get Our Top 5 Growth Stocks for Free HERE. Stocks that have made our list include now familiar names such as Nvidia (+1,460% between June 2020 and June 2025) as well as under-the-radar businesses like the once-micro-cap company Tecnoglass (+1,552% between June 2020 and June 2025). Find your next big winner with StockStory today.

Image source: The Motley Fool. Wednesday, Aug. 5, 2026 at 5:00 p.m. ET Head of Investor Relations - John Lewis Streppa Chief Executive Officer and co-founder - Spenser Skates Chief Financial Officer - Andrew Casey Operator: Good afternoon, everyone, and welcome to Amplitude's Second Quarter 2026 Earnings Conference Call. John Lewis Streppa: I am John Lewis Streppa, head of investor relations, and joining me today are Spenser Skates, CEO and cofounder of Amplitude, and Andrew Casey, chief financial officer. During today's call, management will make forward-looking statements. Including statements regarding our financial outlook for the third quarter and full year 2026, 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 in these statements. Further information on the risks that could cause actual results to differ 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 these statements after today's call except as required by law. Certain financial measures used on today's call 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 financial measures are included in our earnings press release and the supplemental financial information, which can be found on our Investor Relations website. At investors.amplitude.com. And with that, I will hand the call over to Spenser. Spenser Skates: Thanks, John, and good afternoon, everyone. Welcome to Amplitude's second quarter 2026 earnings call. Today, I will cover 3 things. First, our Q2 results. Second, how we transformed Amplitude into an AI company and why every company I talk to now wants to learn how they can do the same. Third, a look at our product and a spotlight on our customers. Let me start with the numbers. Q2 revenue was $101 million. Up 21% year over year. Total annual recurring revenue was $410 million, up 22% year over year and up $36 million from last quarter. That was made up of 2 parts. Inorganic ARR from Statsig of $17 million and organic ARR growth of $19 million. Andrew will walk through the details. Non GAAP operating loss was $1.5 million. Customers with more than $100 thousand in ARR grew to 824, an increase of 30% year over year. Both AI natives and large enterprises are driving this growth. Let me step back and tell you about our transformation and then how we are helping customers along their AI journeys. We help companies build better products. Every company wants to transform to deliver software products in an AI native way. We have made that transformation at Amplitude over the last 2 years and now our customers are looking to learn from us. Becoming an AI company starts with the organization. 2 years ago, we first transformed our engineering team by bringing in AI engineers who built with it for years. Then we moved into adjacent functions like product management, design, and the more technical parts of go to market. We also brought in AI expertise through acquisition, Founders and other members of the team from these companies have taken leadership roles across Amplitude. I have focused on bringing in leaders who are former founders and who have a technical background. Gabe, our chief product officer, started multiple companies, including Loom Systems, which sold to ServiceNow in 2020. In addition, Nate, our chief commercial officer, has a degree in math and physics and started his career as an engineer programming in c plus and Java and building databases. Most recently, we added Angela Ferranti as SVP of marketing. Angela founded Lovable, which went through Y Combinator Summer 2021, sold it in 2025, and is a technical marketing leader who builds apps with AI in her spare time. In addition to all of this, we are continually reeducating everyone at Amplitude through initiatives like AI Week, unlimited token spend, and a living token leaderboard. This has all resulted in 3x the number of pull requests in 6 months. We have reduced our pull request cycle from 5 hours to 44 minutes. Bug reports are down 55%. 5% of our pull requests are submitted from designers and product managers with no engineering involvement. We have leveraged AI to shorten our closing process by a day. We built customer health dashboards that enable our sellers and leaders to track customer usage, bring our own Amplitude data alongside Salesforce data and data from other sources. When I talk with our customers, they are all focused on how they can transform their business to be AI native like we have done at Amplitude. The AI landscape is changing rapidly, and they want to learn how to adapt. Our customers are on a spectrum of AI adoption. Our job is to meet them where they are and then educate them on how to take the next step. We work with leading AI companies to learn what the bleeding edge in product development looks like. We use that knowledge to educate the rest of the market, including the largest enterprises to deploying at scale. More than 40 AI native companies now pay us over $100 thousand a year. Those customers include Harvey, Midjourney, Character AI, and 1 of the leading foundational AI model companies. On the enterprise side, enterprises are now more than 68% of our ARR. This quarter included agreements with Paramount, Jaguar Land Rover, and Domino's Pizza. We have improved our pricing and packaging. We reduced down to a 1-meter to make it simpler for enterprises to add additional products. We increase the amount of data on our free plan so we are the best for those just getting started. Amplitude has the best pricing whether you are a startup or a large enterprise. 1 of the biggest changes with building an AI native company we are seeing at Amplitude and with our peers in private markets is in the cost structure. A lot of inference spend is required in order to deliver AI native products, which increases the amount spent on cost of goods sold. On the other hand, you do not need to add as much operating expense to continue to grow a business at scale. We are embracing this change in cost structure as part of our transition to an AI native company. For now, we expect gross margins to stay in the low 70s. We will offset that with a commensurate reduction in operating expenses. That allows us to continue to show the same leverage as op in operating income as we have planned. I am continuing to drive Amplitude to a 20%+ operating margin business over the long term. We offer 3 products to meet customers wherever they are on their AI journey. Amplitude gives you the deepest understanding of how people use your product. Our agents increasingly do that discovery for you. Statsig gives you feature flagging and experimentation, built on the world's most advanced stats engine with an engineering first view. it is also integrated natively with data warehouses. Wade is the future of product development, self improving products where we automatically recommend what to build based on signals from users. While we are early here, I am actually excited to show you a demo today. Together, these 3 products close the product development loop. Understand what is happening, measure what ships, and ship what matters. That loop is how AI native business is built. Let me go deeper on Amplitude. Global chat is becoming the primary way our customers interact with their product data. You ask it a question in plain language and it does the analysis, No dashboard building required. it is become the de facto way many companies do product analytics. Global Agent finds the root cause behind 75% of customer questions and hands you the answer. There are 1.3 million global agent interactions every week and root cause to discovery rates are improving by 1 percentage point every month. As of today, over 40% of all insights come from AI agents as opposed to humans, and we expect this to continue to grow. Today for a demo, I wanna show you custom agents Statsig, and Wade. Let's start with custom agents. Custom agents are teammates that automate recurring workflows on your product data and push that work to other tools and systems. This is our chat interface. An increasing number of users are interacting with Amplitude mostly through chat and agents. I will ask a question. Which group of users are most likely to purchase next week? Chat can now write its own code to perform this analysis. This unlocks the ability to run deeper analysis and create powerful new graphs and artifacts, including diagrams like you see here, out of time decile lift, an ROC curve, segment propensity. You can dig in by seeing the actual code used and step by step analysis. This type of deep analysis has never been available before in analytics tooling. We are no longer bound by the constraints of a UI. We can also create automatic and recurring agents that run in the background. I give it these instructions. I want this analysis run every Monday morning. Cross reference with marketing activity in Confluence. DM me the results in Slack. Amplitude then creates the agent. That you see here. This is the entire prompt, including connectors to Atlassian and It will run regularly every Monday and push the results to me. We are building the best analytics agent across all data sources. Statsig is the leading product for experimentation and feature management. Statsig runs experiments natively on your cloud data warehouse, whether that Snowflake, BigQuery, Databricks, or Redshift. Let me show you what this looks like. Here is the results page for 1 of hundreds of experiments that an ecommerce customer is running. This experiment is testing a larger product image versus the default size. there is a lot of statistical machinery behind a good experiment, but the UI makes it simple for an engineer to run. Up top, they can monitor exposure, which is saying the experiment is healthy or not. We expect to see a 50-50 split. So we are doing good. And as you can see over here, we are getting a healthy check. We move to the scorecard that has the results. This has a confidence interval of 95%. Statsig uses advanced techniques like CUPID and sequential testing that allows engineers to speed up time to decision. We have those turned on. In monitoring, we see specific events we are tracking for this experiment. We are seeing positive results. The checkout event is up by 27.4% plus or minus 2.3%. Cart conversion is up. Total purchase dollars is up, while carts per session is down. For the rollout of this feature, we have a progressive rollout. Starting with employees, moving to early access users, then early release, and a scheduled rollout for everyone else. Statsig has a variety of advanced experimentation like feature gating, dynamic configs, and automatic rollbacks. Together, these are the mechanisms that a team uses to ship a change gradually tune it while live, and pull back automatically if it goes wrong. Last, I want to show you Wade the future of product development. Wade allows for self improving products that automatically recommend what to build next based on signals from your users. Wade is magical. Wade looks across all the different data sources you have. Analytics, experimentation, session replay, guides and surveys, feedback, and many others. It then synthesizes that data into a set of product recommendations plans those recommendations, and then helps you create those changes in your product. I am going to walk you through a real example WAVE suggested and built for Amplitude's documentation site. On our documentation site, Wade found a spike in failed searches through looking at session replay and analytics data. The core problem was that search on our docs page fired on every keystroke. Typing a single letter to start a search returned an empty no results state before the person finished typing their search, leading to a bad experience for users. Wade explains the reach of this issue. Every user who uses search, it has an impact expected impact of decreasing total search failures by 80%. Then Wave has automatically created a visual example of the problem below so it is easy to understand. It also has a full explanation of the evidence. For the plan, WAVE sketches a wireframe of the recommended update. Setting a 3-character minimum and a 200-millisecond debounce to trigger the search. Wade can also drive execution. It automatically created the pull request and cursor wrote the code. Mark, our technical writer, was able to merge this pull request and ship this. No engineers, no designers, and no product manager. Finally, Wade measures the results of the change. There is a massive decrease in total search failures. Simply amazing. Now let's talk about some of our customers. We had a great quarter with both new lands and expansions, We added or expanded our relationship with customers, including Paramount Global, Jaguar Land Rover, Teladoc Health, Chime, Disney ad platforms, F5 Networks, Coursera, Grammarly, Kraken, and Crunch Fitness among others. I want to tell you 3 stories about how these customers are leveraging our platform. First is Coca Cola FEMSA. Which sells to hundreds of thousands of small shops across Latin America. Every shop is different, but for years, they had to run the same broad campaign to everyone because there is no way to tailor a message to that many retailers by hand. AI changed that. They began sending each retailer its own recommendation every week written by AI. Their own teams were actually skeptical. A different message for every shop every week felt risky, and no 1 knew if it was going to work. They used amplitude to find out. Their AI campaigns actually had an 11% click-through rate, 4x higher than their previous approach. Our cohort analysis also showed that this lift lasted. Once a retailer engaged, its revenue stayed higher in the weeks that followed. That evidence turned skeptics at FEMSA into believers, and they went from a 2.5 thousand-store pilot to 690 thousand retailers. The second is Replit. Replit is an AI app-builder that allows non-technical builders to turn an idea into an app using AI. Replit has a large global user base of passionate builders that provide feedback. Replit is using Amplitude AI feedback to understand how customers are engaging with their agents. They have connected AI feedback to Zendesk App Store reviews, Twitter, and Reddit, and surfaced and prioritized what problems should be solved to increase their retention and engagement. It changed weeks of manual work on their end into a simple click with AMP. Amplitude. This is the next generation of product development at work. Third is the economist. The Economist is a print publication that is in the midst of a transition to digital delivery and subscription. Their research arm built an AI assistant called Lens that answers questions for analysts and strategists using The Economist's content. Their normal analytics could show what users did, but not whether the AI's answers were any good. The team was reading sessions by hand, but they could not keep up. 96.9% task success rate and weekly failures are down 84%. That is the loop working. Build with AI, measure whether it is good, and fix what is not. To wrap up, the companies on the bleeding edge are choosing Amplitude. We have transformed Amplitude to be AI native, and we are building the future on what can be done in analytics. Self improving products are closer than ever with Wade. Our pace of innovation continues to accelerate, and we are building in a way that can scale with leverage I am extraordinarily excited about what is ahead. With that, I will hand it over to Andrew to walk you through the financials. Andrew Casey: Thank you, Spenser. This was a strong quarter and a clear step forward in our execution. Bringing our vision of how products will increasingly be developed and improved. We crossed $100 million in quarterly revenue, ARR reached $410 million, growing over 22% with the addition of the ARR assumed from the Statsig, business, and free cash flow was a record quarterly high of $23.7 million. We also returned $69 million in capital during the quarter as part of our share repurchase program. We accomplished these milestones while integrating the Statsig and customers, managing through our own AI native evolution, and implementing our new pricing and packaging strategy. AI is changing how customers use Amplitude. More our customers bill with AI, the more they need to measure. Customers that adopt our AI into their workflows run nearly 10x the number of analyses compared to those that are running things manually. This increases the value that customers receive from the data ingested into platform and makes it more likely that they will both ingest larger amounts of data and expand into additional products, which is the basis of our growth. Our new pricing and packaging is working. It supports our market consolidation strategy by providing customers with a lower overall cost if they consolidate applications onto our platform. It provides customers greater cost predictability and simplifies the quoting process for our sellers. In the second quarter, 70% of the ARR we closed was on the new model. Up from 25% in the first quarter. Now 28% of our total ARR is on the new pricing and packaging. This is leading to average ARR increasing, higher multiproduct attach, longer contract duration. Which all contribute to greater durability of our revenue. Our margins reflect a choice. These are investments we are making to drive future growth with increasing profitability. Our gross margin was down over 1 point versus Q1, due to the integration of STAT SIG. We are working to optimize the new hosting environment and cloud structure but it will take some time to improve from the low 50s gross margin closer to our expectation of 70 plus for the Statsig business. We are also experiencing higher customer adoption of AI capabilities and greater data ingestion into our platform. Which combined has increased our costs and reduced Our gross margins by an additional 2 points versus Q1. We have long maintained that we will grow with leverage. This investment in the cost of revenue places greater emphasis on the management of our operating expenses to a lower level in order to achieve the leverage. In Q2, we have managed down our sales and marketing to below 40% of revenue, and G&A to the low teens. Which is contributing to an increase in operating margins. We will continue to manage both areas lower as percentage of revenue over time we will continue to invest in R&D to drive innovation. We are instrumenting our business to accelerate growth. Capture market share, and show leverage. 1 key metric we monitor is the usage of data compared to the entitlement for our customers, as this is a primary monetization metric. Today, that metric is at an all time high. This is the output from better pricing, packaging, and more usage driven by our AI features. Have increased the durability of our business through our RPO growth and reinvented our internal reinvented our internal processes to capture scalability that AI offers. We are running to the AI opportunity and taking share as we go. Turning to our second quarter results. As a reminder, all financial results that I will 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. Second quarter revenue was $100.9 million up 21% year over year and 8% quarter over quarter. Total ARR increased to $410 million exiting the second quarter an increase of 22% year-over-year and $36 million sequentially. This includes $17 million of incremental ARR from Statsig business compared to the $16 million we expected to add when we shared our first quarter earnings. Total remaining performance obligations grew 35% year over year to $483 million. Current RPO was up 30% year over year, and long term RPO was up 47% year over year. 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, and platform sales were again particularly strong. 48% of our customers now have multiple products, with 80% of our ARR coming from that cohort. We have over 26% of our ARR from customers with 5 or more products, up 2x since the second quarter last year. In period, net dollar retention was 105% on a pro forma basis, led by cross sell expansions across our customer base. This pro form a basis includes Statsig and Amplitude customers. Gross margin was 71% for the second quarter, down approximately 4 points from the second quarter of last year and down 4 points sequentially. This was driven by continued growth in inference costs as customer adoption our AI tools accelerated along with the integration of the Statsig business and its hosting environment. Sales and marketing expenses were 39% of revenue. Down from 44% in the second quarter of last year. G and a was 13% of revenue, down 1 point from the second quarter of last year. R and D was 21% of revenue, up approximately 3 points from the second quarter last year, reflecting investment to scale the Statsig opportunity and support for those customers. Total operating expenses were 73 million or 72% of revenue. Operating loss was $1.5 million or 1.4% of revenue. Net loss per share was -$0.01 based on 129.4 million basic shares compared to $0.01 a year ago. Free cash flow in the quarter was $23.7 million or 24% of revenue compared to $18.2 million or 22% of revenue during the same period last year. We ended the quarter with $162 million in cash and investments, We have conviction in the long term value of our platform and have used and will use our cash to minimize the impacts of dilution. Our balance sheet position remains strong and allows us the opportunity to be more aggressive in our M&A strategy to accelerate our R&D road map when appropriate. Now turning to our outlook. As a reminder, the philosophy of how we set guidance is through the lens of execution. Are pleased with our overall progress on consolidating point solutions to our core platform and the adoption of our different AI technologies. We have instrumented our business and selling to make it easier to use more of our platform. We believe that we are well positioned to continue to accelerate our growth in a profitable way. For the third quarter of 26, we expect revenue to be between $105.6 and $108 million representing an annual growth rate of 21% at the midpoint. We expect non GAAP operating income to be between $2.5 million and $4.5 million And we expect non GAAP net income per share to be between $0.02 and $0.03 assuming a weighted average shares outstanding of approximately 133 million as measured on fully diluted basis. For the full-year 2026, we are raising our expectation for full year revenue based on the performances in second quarter to be between $407.2 million and $411.2 million, an annual growth rate of 19% at the midpoint. We are also raising our expectation for the full year non GAAP operating income due to performances in the second quarter and actions taken in the first half be between $6.3 million and $9.3 million. We expect non GAAP net income per share to be between $0.06 and $0.08 assuming weighted average shares outstanding of approximately 137.1 million as measured on a fully diluted basis. In closing, we are accelerating our pace of innovation, and we are growing the value that we can deliver to our customers. We have confidence in our ability to scale a durable and growing business while also bringing agentic analytics to the world. With that, 'll open up for Q&A. Over to you, John. John Lewis Streppa: Thank you, Andrew. We are going to Q&A. For the sake of time, please limit yourself to 1 question and 1 follow-up. Operator: Our first question today will come from the line of Mark Cash from Raymond James. Followed by Jackson Ader from KeyBanc. Mark, your line is now open. Analyst: Thanks, John. Yeah. If I could start with Spenser. I really wanted to ask around Wade. I appreciate it is still limited beta. I think you have been using internally for several months now. Yep. I guess, do you see Wade that it could cause maybe a shift-- a company shifting away from using bespoke agents for specific use cases towards a broader AI native product development platform from what you are seeing And if so, how could that change your buyer, maybe the budgets you see and the address market over time? Spenser Skates: When you say bespoke, like, say more on that. Like, Instead of using particular agents to do a specific task underlying because you have, like, a lot of agents doing things underneath for what you so I see what you are saying. I see. Okay. So let me separate out a few different things. What we have on the amplitude side and I showed with custom agents, is you have these agents that can look across your data and find insights for you and get to the root cause of questions and do that on a regular basis. And kind of send it out. With what Wade is doing in particular, to your point, is it is kind of-- it is looking at all your data all the time and then saying, hey. Here are points of friction. Here's something that is not working how it should be. Here's a feature that I think you should emphasize more. Here's something that I think is a best practice that you are not doing. And so it is operating at a kind of higher level. In terms of the persona, I think we are seeing is a convergence between engineers, product managers, and designers into this AI builder persona. it is not really, like, you have engineers who are thinking about what to build, and you have product managers who are also just shipping code. And so the best you know, if you look at where the AI native teams that everyone's aspiring to be, these roles are melding. So it is still the same problem we are solving, which is how do we help you build a better product, but we are just automating more of it because we are saying, hey. We are gonna look at all the data all the time and then suggest recommendations. That like, I have been-- we have been talking about self improving products here at Amplitude for about 9 years. And so I am actually been blown away by what is possible with the technology today where it is just it is the perfect problem for AI in a lot of ways. The datasets are massive and complex. So you cannot get any human to look at them. And then the synthesis of okay. Here's what I think could be better and best practices is actually like, extraordinarily impressive. And so what that means is that just by the fact that someone is using your software, like, it is getting better because it is just translating recommendations. You no longer need someone to go into amplitude or to any data system and say, oh, here's what my interpretation of these results. So I do think, you know, in terms of budget and persona, I do think, again, that means instead of having these distinct roles, you have engineering product management and design merge. You are still doing digital product development, and that still rolls up to some leader, the same executive, before. But yeah, the way you do it looks different. Did I did I hit on what you are looking for? Analyst: Yeah. Absolutely. Thank you for that. If I could follow-up with Andrew real quick. If my math is correct, the guidance for the year was raised by more than 2x the beat for revenue and operating income. So I was wondering if you could just go through the key drivers of lifting growth expectations why you-- it saw some pressure on pro forma expansion there in the quarter? And then what you consider regarding margin leverage-- the levers while you are facing COGS pressure and ramping token spend internally? Thank you. Andrew Casey: Yeah. Sure. So a couple things. 1, that when we look at our ability to actually generate revenue in the out quarters, 1, we start with the strong balances we are we are booking that are showing up in our RPO. Now when you have got commitments from customers for a longer term duration, you start to have better and better predictability about your future revenue. So that is the first thing. it is 1 of the reasons why we emphasize that so much. The second thing is we look at how much our customers are actually responding to some of the initiatives we are putting out in. And that comes in the form of our new product capabilities, our new pricing, new packaging, areas where our sales team is running new promotions and activities. All those are all bolstering our ability to see a stronger and stronger pipeline, and that pipeline progresses faster through its stages, which gives us greater and greater confidence that we will add more and more in net new ARR. Now from a revenue perspective, as you know, the predominance of our business is all coming from our subscription revenue. So those key factors on understanding, you know, what is the baseline? What can you see in your pipeline? What you expect it can convert is what I what I refer to as our ability to go execute against the plans that are in front of us. And the sales team's been doing a really good job driving consolidation in the market, and that alone with our products is driving great conversions. So that is the first thing. On some of the margin areas, would tell you, look. We just, in the case of, the Google environment that we got for Statsig, we are going to be focused on driving optimizations in that environment over a period of time. it is definitely lower. it is-- we said in the low 50s. From a gross margin perspective. That comes from us taking on a whole new environment. You know, most of Amplitude, all of it, in fact, is on, AWS. So we took on a whole new cloud and hosting environment and know, you have to go through the paces of really optimizing how you run those environments for customers. Our first objective was integrating, making sure there were no disruption of service Now we are moving quickly into how we can optimize those environments. So that is 1 big lever on the gross margin side. And we are constantly looking at how we can make investments to go drive greater efficiencies across all of our, our operating expense areas. John Lewis Streppa: Brent. Thank you, Mark. Operator: Our next question will come from the line of Jackson Ader from KeyBanc. Followed by Scott Berg. Go ahead, Jackson. Jackson Ader: Hey. Thanks, guys. Good to see you. I was curious on I guess, Andrew, kinda sticking with you and talking about rather than on the cloud side, just on the operating expense side. We have seen really nice acceleration in organic ARR. You know, from the business. But you know, if I take kind of a longer term view, even on a non GAAP basis, we are still around breakeven. Right? And so I am curious as you are thinking about, like, driving more leverage and more incremental margin that you talk about before on the income statement, what kind of impact should we expect that to have on the organic growth number if at all? Andrew Casey: Well, I would tell you that, 1, we are still we are still expect from an organic perspective, we got a great set of products, Spenser just walked through a number of them that are brand new to the market. We think they have enormous total addressable market that we can go after. So revenue growth would be the predominance where we will see increasing operating income. As far as leverage as a percentage of what that would be, a percentage of operating income, I do expect over time that we will be able to drive better and better gross cost of start revenue and, say, increase gross margins over time. It just takes time to go do those things, especially when you are seeing such a demand inflection from customers and increasing data lines. As I mentioned, we are at an all time high for the amount of data ingestion in the platform versus entitlements When I first joined, it was in the low 60s. We are in well into the 80s now as far as percentage of what customers have ingested versus what their entitlements are, and that portends increasing expansions on upsell, which is you know, usually where we have had a lot of problems in the past of overselling and how to do right size contracts. The first time we are past those things, and we are starting to see really good, upsell, not just cross sell driving growth. So revenue growth is the predominance of the first aspect of driving improving profitability. Far as the leverage goes, I think gross margins will improve over time. it is just gonna take a while. And we still have a long way to go on sales and marketing is reducing that as a percentage of revenue. I think G and A has room, and I do think that over time, we will see greater and greater efficiencies with the R&D organization as they adopt more and more capabilities to build products at a faster rate. Jackson Ader: Okay. And then just a quick follow-up. Can you remind us, should there be any now that we are on a different kind of pricing packaging model, you know, a little bit more variable, I guess, if you will, you know, But should there be any difference in terms of the seasonality your revenue ramp or recognition as we as we move forward with the new packaging? Andrew Casey: So on revenue, I would say, you get a fairly predictable pattern under which revenue is recognized. Because as said, most of our most of our revenue in the future periods is designated by our RPO, the committed contracts. But ARR will follow a very typical seasonal pattern My expectation is a bit more on the enterprise selling basis. Q1 will always be our weakest as far as net new ARR ads because we are adding new territories, adding new reps, implementing new strategic initiatives. This year, in particular, we are educating the sales teams on not only the new pricing and packaging, but a lot of the new products we have. So every year, you are gonna have that, and so it will be a slow start and then pick up. This year in 2, just to remind everybody, we also had some big changes in our sales and marketing leadership, which is predominance of what you see now flowing through and a cost benefit from a lower, sales and marketing as a percentage of revenue. And that is that is from efficiencies we are driving. John Lewis Streppa: Brent. Thank you, Jackson. Operator: Our next question will come from the line of Scott Berg from Needham followed by William Fitzsimmons. Go ahead, Scott. Scott Berg: Hi, Spenser and Andrew. Nice quarter. Thanks for taking my questions. I wanted to follow-up on sales enablement that Andrew was chatting about there. We did a couple different customer checks in the quarter, and the 1 thing that we came back is I do not think your existing customers are quite aware of all the different module modules and innovation that you have rolled out this year. Yeah. Totally. I see Spenser smiling. Is I know that is a function of time, obviously, and 1 customer did not even know that you had acquired Statsig. So I guess, where are you kind of in that journey? Where do you where do you when is the properly ramped in that? I mean, the quarter sales results were good as is, but obviously, better, better awareness there can be even more helpful. Spenser Skates: Yeah. To your point, I think a lot of people still bucket us in the analytics company, and it drives me absolutely crazy. I honestly just sharing, hey, we have Statsig now, and this is bleeding-edge feature experimentation. And you can use it too, and this is the same infrastructure OpenAI runs internally. Like, awesome. A lot of customers do not even know that. You know? And then same with Wade. You know? I think just starting to understand Wade and then same with our other products. I think if you remember from the prepared remarks, like, do see ramping. So, know, we are moving customers from 1 to 2 to 3 to 4 to 5 to more products, but it is much slower, and that drives me crazy. I think it is, you know, there is no substitute for the work of, hey. We built something amazing. We have to educate, you know, the hundreds of people we have in our field. And then they have to educate the thousands of customers in market. Like, that is just work. that is just the whole thing. Something I am spending a lot of time with Nate, our chief commercial officer, well as the rest of the executive team on in terms of how do we get that and do that more efficiently. We just had to kick off a few weeks ago where we showed off a lot of what you saw today with Statsig and Wade and custom agents. But, you know, that is not even to say if the other products we have, like session replay and guides and surveys and AI feedback that can displace point solutions. Anyway, that is I think last year, said the year of the plat-- it was the year of the platform. I think we still have a ways to go on educating people on it. I will say that the good news on it is the main thing customers are looking for is a proof to me you guys are at the bleeding edge of where this field is going. And so my view is that analytics and the whole data behavioral data ecosystem is gonna go through the same shift that coding has in the last 2 years. Like, that is still gonna happen. And so they wanna you know, they we see it in, like, a lot of stuff we have been demoing and, you know, our customers see it too. And so they wanna know, hey, am I working with the company that is bleeding edge on this? And so even if they are not necessarily ready to adopt a WAVE or even a Statsig, I know that, okay. You at least help me take the first step to using some of the basic on these capabilities, and then I can add more, you know, even if it is maybe too overwhelming for me right at the start or I am I am not ready as a as a company. So anyway, that is all to say. We still have a bunch of work to do to make sure our field is equipped. You know, there is definitely areas that do it extremely well, but then there is areas we need to do a better job on this. So appreciate you calling that out. Scott Berg: Thanks for that, Spenser. And then from my follow-up question is on, the integration traction with Statsig. You all had a pretty aggressive goal obviously, to move that asset into your organizations. Kinda where are you with it? Because the other customers that we spoke with were super excited about that. You know, couple of them already, you know, SaaS customers, etcetera. So just kinda understand, have you hit all your goals around that? And are you kind of at that point where now you can just deliver on product and sales versus just having to integrate the organization? Spenser Skates: Yeah. So as you imagine, like, Statsig has been around for 5 years, and there is a lot of work with getting it from, you know, a whole group of people who have never seen the codebase or sold it or whatever else. I think we have kind of gotten through you know, there is always stuff, but you have we have gotten through all of the urgent fires. In running and delivering Statsig. So that is great. You know, customers are very excited about how it is landing. We wanna make sure to give you know, the fact that it is our main focus as opposed to at OpenAI AI, it was a little more of a side thing for them. You know, it is it is all been received positively. that is good. Now we are starting to think about, okay. what is coming next for Statsig. So if you look at, like, statsig.com/updates, we are shipping stuff. We have been shipping stuff for the last, few months. We are continuing to build in the road map. We are continuing to integrate it with Amplitude much more tightly so that if you are on both, which a lot of our customers are, you get the benefits of being able to use data from 1 and the other. And I think a lot of the other thing we are seeing with Statsig is that there is a lot of demand from AI natives in particular. So 1 of the reasons we are really excited to join forces with Statsig is that they-- like, a lot of the way future product development is being run like, people are choosing Statsig for that. So it is engineering first teams that tend to be much more technical. They are building out whole software development harnesses. They wanna manage how stuff is deployed in that harness. And Statsig is set up really, really well to scale. You know, as I mentioned, OpenAI runs a version of that infrastructure internally for themselves. And so, you know, they have tested that, you know, in tons of different ways over there, and, you know, we are doing the same thing, with everyone outside of OpenAI. And so there is a lot there is a lot for us to do in terms of how do you set Statsig up to be a core part of the software development harness for all these bleeding edge AI customers, and it is where kind of everyone wants to go over time. So that is what we are focused on. Scott Berg: Awesome. Thanks for taking my questions. John Lewis Streppa: Of course, Scott. Brent. Thank you, Scott. Operator: Our next question will come from William Fitzsimmons from Piper Sandler followed by Clark Wright from D. A. Davidson. Go ahead, Billy. Billy Fitzsimmons: Hey, guys. Good to see the results and guidance. I think 1 of the exciting things about Statsig is potentially the cross sell opportunity. I know there are some things to do first, but last I looked or last I checked, I think there were 80 of the 400 Statsig customers are on Amplitude already, so there is there is a lot who are not. Can you just help contextualize for us how we should think about the potential cross sell opportunity amplitude into Statsig or potentially vice versa in how we should think about that long through the model long term? Spenser Skates: I think probably the much bigger opportunity is to take Statsig to Amplitude customers. I think Statsig customers, as I mentioned earlier, tend to be much more bleeding edge from an AI innovation standpoint. And so that is where everyone is trying to get their organizations to over the long term. It is a very it is like a more Amplitude is historically focused on product management, and then Statsig is much more tailored towards engineers. Like, has tons of customization. Out of the box. It has, like, all the statistical testing. Now, like I said, those 2 personas are merging, but, you know, it is it is it is early days on that. So I think the opportunity is as more of our traditional Amplitude customers look and try to build like AI natives, introduce, you know, AI to their software development process, try to build out a harness, eventually try to get to self improving products, that all of those are opportunities for us to bring Statsig. Now we definitely do see places where Statsig customers are also very interested in Amplitude. But, you know, it is-- there is a lot more both from a number and ARR basis that are Amplitude. Billy Fitzsimmons: Perfect. And then if I can ask a second 1, can you just contextualize maybe how either your hiring needs have kind of changed year to date or where you are seeing the best ROI from AI driven efficiencies internally within Amplitude? Spenser Skates: Oh, there is there is a ton. On the hiring front, so a few different things. 1, like, it is been-- I have been just very focused on transforming the entire workforce, getting leaders, getting engineers, getting people in other functions that are AI native both by like, hiring that talent, acquiring it, know, hiring executives that have that background. And then in addition to that, retraining and re-educating the workforce that we have here. Like, everyone wants to learn. it is like, yeah. You know, people see, like, hey. The more I can learn how to use AI, the more relevant my skills are gonna be both at Amplitude and other places in the future. So everyone's, like, embracing it, which is great. The few specific areas, I think on yeah, so that is, like, an always ongoing thing. Like, I just-- we were just adding Angela, which we announced today, in marketing. You know, we are always looking at companies and other places to pick up talent. is another great source of very highly leveraged talent. 1 of the funny things I will tell you guys during, you know, downturns or whatever, a lot of companies pull back on university hiring. But if because it is, like, the easiest thing to cut. But if you have the confidence to evaluate who is great from that talent pool, you can get some exceptional folks right out of school, which is awesome. So we have been had that as a big focus here at Amplitude. So that is, like, the primary thing. And then the 1 specific area is Statsig. You know, as you imagine, this is a huge, you know, complex product and code base and architecture. And so our we have taken our existing experimentation team, and they are now running Statsig, which is awesome. But they also need a lot more help, so we are adding, you know, lots of different roles and hiring on that data science leads, or deployed engineers. You know, other engineers who are just familiar with that architecture. We have actually hired 1 person who used to work at Statsig, pre the opening acquisition, and we are continuing to go more there. So there is there is a lot we need to do there. We have kind of I kinda caught the ball, which is good, but now we have to, like, go maximize it. Billy Fitzsimmons: Brent to see. Thanks, guys. John Lewis Streppa: Alright. Thank you, Billy. Operator: Our next question will come from Clark Wright from DA Davidson followed by Koji Ikeda from Bank of America. Clark, go ahead. Clark Wright: Thank you. It was great to see the 30% year over year increase in with over 100 ks in ARR, which looks to be the highest in 2021. Could you potentially break out the adds from Statsig? And what else is helping in terms of the new logo momentum that you are seeing today? Andrew Casey: Sure. So about 40 customers came from the Statsig business itself that we added. And so if you got to do the quick math on that, you are still well in, almost 23, 24% growth in customers that are in that greater than a $100 thousand cohort. And so it is still growing quite nicely and contributing to ARR to revenue growth. So that was really good. And as Spenser mentioned earlier, what we are seeing back when we are talking with customers especially as we have gotten introduced to them for the first time, if they are brand new customers to Amplitude, were formerly Statsig customers, is we are finding that they are, 1, very appreciative of the fact that Amplitude is shepherding and taking forward the road map and showing confidence in our ability to actually give them a future where self improving products is a reality. And they do that through adopting a an experimentation mindset, and they are very confident then to move further with Amplitude in other areas. So that cross sell expansion opportunity is real. I think we talked about it at the time. There was a multi-hundred-million-dollar opportunity for us just in the install base. So we are pretty excited about it. Clark Wright: Got it. And then last quarter, you called out event volume growth being 21%. Year over year. What is that now as you kind of talk about the momentum that you are seeing in all time highs? And how should we think about the ramp of that going forward given agentic workflows and the amount of events that they can process? Andrew Casey: Yeah. it is it is definitely growing faster than both ARR and revenue, and it is 1 of those areas that for us, feels like we have gone through many, many quarters of trying to bring it up and get the entitlements right sized and everything else. it is definitely a leading indicator for us that, you know, 1, we are not gonna have the same types of churn issues like in the past. 2, sales has adopted that value based orientation sale where they are not trying to get everything up upfront. They are trying to get our customers to value quickly and show them a value of an expansion. And like I said, it is it is a it is an indicator that we are gonna see upsells have a larger, meaningful contribution to growth Whereas before, it was a detractor and the predominance of our growth with cross sell. We are just not gonna have those same instances if we have got customers who are bumping up against their entitlements. And getting value from the investment they have made. Clark Wright: Got it. Thank you. John Lewis Streppa: Brent. Thank you, Clark. Operator: Our next question will come from Koji Ikeda from Bank of America followed by Nicholas Altmann. Go ahead, Koji. Koji Ikeda: Yep. Thank you. Thanks, guys. Thanks so much. I wanted to ask a question on Wade. You know, love the demo. Long term vision. I mean, it sounds like it is gonna be awesome for finding problems and you know, finding solutions, generating code, measuring outcomes. I mean, it looks like the full deal here. And so the question really becomes, if Wade is successful in all the things I think it could be, then why would you need the other products from Amplitude like Statsig and product analytics? Analyst: Seems like you could do it all from. Spenser Skates: Yeah. Totally. Totally. Okay. So, yeah, this is I brushed over this architecturally. What Wade does is it takes data from lots of different data sources. So it takes analytics data from Amplitude, experiment data, from Statsig. We are eventually we are planning to make it agnostic long term so it can take data from any analytics thing if you are using Google Analytics or Adobe or something else. It does not matter. And then translate that insight. So you still need a place to get that data. Like, it is not like it can just look at a product and figure out what people are doing it. It actually needs to have that data, from some area. And so it is a nice build where like, hey. Use Amplitude. Use Statsig. The more data sources you put into this thing, the better the output. That you see. 1 of the big learnings from the AI boom is that the power of massive scale of data is just gets you better and more accurate more insightful results. Like, that is just a straight you know, that like, you can see look. The scaling laws look like you can you can grow that almost infinitely. So Amplitude Analytics actually as well as the experimentation and everything else we have play a really important part in being the collection points for that data. Again, though, you know, goal is to be agnostic so we can just plug into whatever system, you know, data warehouse, your own internal thing, you know, other tools, third party tools, kinda build it on top of that. I think another thing is that because we have that data, that gives us the ability to have much greater insight into the right things to build. If you are a startup starting out for the first time and you do not have the massive, you know, multiple petabyte dataset that we have, it is like, okay. How do you even know if what you are recommending is best practice or what leads to something good? And so there is a lot of feedback loops that we have because we have this dataset. We know, okay. Hey. Here's what a great ecommerce app looks like. Here's what a great social media app looks like. Here's what, you know, you know, a fintech app should look like. Here's the, you know, typical workflows for sign up that work well. Here's what message customization should be so and so on. And so because, like, we are 1 of the few companies out there, there is no open source equivalent datasets for it. And so having that allows us to develop a much higher quality, better version of Wade than kinda anyone else out there. So, the other good part is it is not like a you know, it is an alpha, so there are customers using it. it is not using it internally. there is a number of startups. there is a few enterprises that are using it. And so it is it is spinning out real things that you know, frankly, you look at this, and you are just like, holy shit. How did AI come up with this? This is crazy. I am convinced that whoever wins this space, that is gonna be a multibillion dollar business, if not more. And so our thing is, like, let's run forward with that as fast as possible. I think we are well positioned in the opportunity because we are the leader in analytics and a few other areas. Yeah. And, you know, let's let's go let's go build that business as quickly as we can. Koji Ikeda: Got it. Thanks, Spenser. All from me. John Lewis Streppa: Thank you so much. Of course, Koji. Thank you, Koji. Operator: Our next question comes from Nicholas Altmann from BTIG. Followed by YC Wong from Citi. Go ahead, Nick. Nicholas Altmann: Hey. Awesome. Thanks, guys. Just to build off, Koji's last question, I kind of wanted to ask the inverse on Wade of, like, it seems like there is more incentive to adopt the broader platform with Wade. Exactly. And I know it is still very early, but how are those kind of conversations going with customers? Like, are you having more sort of multi-product or platform adoption? Customers as they kind of, you know, look at Wade and this vision of the self improving product. And then the follow-up there is just how should we think about Wade being monetized more so in the near term? Is it kind of indirectly in the sense of it gives customers more incentive to adopt the broader platform, and that is how you sort of plan to monetize it or is it kind of a standalone SKU? Spenser Skates: Yeah. So I you are exactly right, which is the more data sources you feed to this thing, the better. And so we have already I have already seen multiple customers who have gotten on session replay. As well as 1 that signed up for AI feedback specifically because, hey. The stuff that the wave makes it a lot better. And you are absolutely right where, like, it drives, like, the whole platform play or it is like, okay. You have all these individual point things, and then you just they are more data sources. Session replay in particular is very, very powerful. Like, as you imagine, viewing the exact state of UI and where a user clicked is has a lot of value for how it can be better. So that is been that is been awesome to see. And, you know, again, early, you know, there is there is you know, handful customers on it. But, as we grow it out, I think that will that will drive more adoption. And I also do not think, like you know, to my point earlier to Koji, it is like, you know, our goal is to be agnostic with it. We wanna build the most bleeding edge thing. And so if we plug in other sources too, all the better. On the monetization front, we are we are you know, we will charge for it. We absolutely will charge for it. I mean, you think about the value that this creates. Now you go from analytics or data tooling where it is like you have to manually go in, collect an event, or look at ask a particular question, get a result out, think about how to apply that business. And now you are having a whole flow that does it for you. Hey. I have already seen this user is having friction here like that. The docs example I made is like, hey. We see most search queries are failing. Why is that? Well, they are single characters. And we are not waiting till someone types a complete word, so they get this error when in the middle of the typing, that feels bad. And it is like, you know, duh. Okay. Yeah. You should resolve that and make that better. And it is not just that. it is like that times hundreds of things all across all surface areas of your product. 1 of the lessons is like, behavioral data and product surface areas are so large, it is impossible for a team to stay on top of them. And so the fact that this thing is looking all the time for how it can be better, is this just it is magical. Like, it is crazy what it can do. So I think whatever company goes to win that is gonna be multiple billions in revenue, if not more, and we wanna aggressively go And, yes, customers are willing to pay for that. Now, you know, again, early days, we are in alpha, you know, so we have not figured out exactly how we are gonna monetize it, but we absolutely will charge for that capability. that is, like, that is 1 of the great, you know, people are talking about, hey. there is all this money going to AI. Where does it actually come out? And this is 1 where you can draw the line really directly. it is like, look. The customer experience is getting better. They are spending more. there is more revenue. there is less friction. Less downtime. Like, the whole thing is just better. Like, great use from an application standpoint. Nicholas Altmann: Brent. You so much. John Lewis Streppa: For sure. Thank you, Nick. Operator: Our next question will come from Yitchuin Wong from Citi followed by Arjun Bhatia from William Blair. Go ahead, Yitchuin. Your line's open. Yitchuin Wong: Hey. Good evening. Thanks for taking a question here. Spenser and team, like, great to see the fast expanding AI platform here you have, like, every quarter. Like, I wanna touch on agent analytics, which now to measure. it. I love it. Like, agents themselves, right? I mean, where the market that we see is already multiple vendors out there trying to measure prompts, measure latency, hallucination to, like, all the stuff that you can see. But what is the customer problems that the agent analytics could solve that the current observability platform cannot? And then how do you view the market opportunity? Of that problem? Spenser Skates: Yeah. So, I mean, I think first to the extent this replaces most traditional interfaces, then, you know, the market opportunity is now as large, if not larger, Than what is going on traditional user interfaces with session replay and analytics. In terms of our unique positioning, what we offer which I shared a little bit in the customer story about Economist, is that you can connect what is individually happening within a session to the long term impact of your business. So you can say, okay. Hey. You got a successful answer back from the bot. Did that lead to you spending more or signing up or keeping your subscription? Conversely, if you ran into a problem and you got frustrated, did that lead to some negative long term outcome? And that loop is really, really important Most a lot of the engineering specific observability products we have seen in this space just kind of stand alone. it is like, okay. They will just show the traces, and that is kind of it. And you have no idea if it is actually leading to different results down the line. And so that is why we see both, like, traditional, like, enterprises that are transforming their businesses like The Economist, as well as a lot of AI natives. Know, I mentioned 1 of the largest foundational model companies They also are looking at, like, you know, as you imagine, they have a lot of tooling there, but they wanna know, okay. Is this leading to someone to becoming to upselling, all of that sort of stuff long term? And so being able to connect that journey end to end is what we uniquely offer. Yitchuin Wong: That sounds like a more TAM expansion opportunity there. Oh, absolutely. Absolutely. Yeah. I did not cover as much today. We demoed it more on the Q1 earnings call. But, yeah, it is it is it is actually 1 of the things, my chief commercial office and I are very excited about. Yeah. Definitely look forward to hearing more, including Wade. I have a quick follow-up for Andrew as well on the guidance. Like, amplitude growth had definitely been accelerating for the past year or more, right? Even adjusting for the static business this quarter, I think it is still accelerated. But the implied guide that I am looking for Q4 shows about a 2- to 3-point decel. Could we kind of have us double click on the largest step down on the Q4 guide is it more just seasonality or incremental conservatism? Andrew Casey: I would tell you that we always take a look at what, when we are building our guidance, what we believe is, you know, very strong likelihood to occur. And I mentioned some of the factors earlier about pipeline, how well that pipeline's developed, you know, where we are seeing good demand from our customers. Usually, Q4 is our strongest quarter from an net new ARR perspective, and it is because that is the way we built our comp plans. that is the way enterprise selling cycles run typically in a calendar based company. I would just tell you that our guidance is based upon what we know is out there as far as our pipelines, our RPO, and it is what we are comfortable with. Got it. Yitchuin Wong: Congrats, guys. Andrew Casey: Thank you. John Lewis Streppa: Thank you, YC. Operator: And our last question will come from the line of Arjun Bhatia of William Blair followed by Willow Miller. Willow, your line is open. Willow Miller: Hey, team. Thanks for taking our question. Can we hear your updated thoughts on the 20% plus revenue growth target given the strong growth this quarter and the strong third quarter guide. I am curious to hear how you are thinking about it now considering Statsig and now Wade? Spenser Skates: Oh, yeah. I mean, I think Statsig is an accelerant to our long term plans, which is part of why we Vijay and I agreed Amplitude would be the best home for Statsig long term. You know, as I think the so we put up $19 million in organic growth last quarter in Q2. And so, you know, it is just we are just touching on that 20% You know, it is like the annual number is 410. So if you divide that out, it is like, you know, we are just we are just shy of that 20% growth target when you annualize the quarterly numbers. To me, as I have always said, 20% is kind of bare minimum. Like, we all wanna be making sure to continually hitting and exceeding that 20%. Long term, we are we are we are aiming a good deal higher. We wanna get to 30 and then and beyond that as we continue to grow the business. Obviously, a lot of work between here and there, but that is that is what we are very focused on doing. Willow Miller: Good to hear. Thank you. John Lewis Streppa: Thank you, Willow. That will conclude our second quarter earnings call. Thank you for your time and interest. We look forward to seeing you this quarter on the road as we attend conferences hosted by KeyBanc, Citi, and Piper Sandler. Thank you. Thank you all. Thank you. Before you buy stock in Amplitude, consider this: The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Amplitude wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years. Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $403,337!* Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $1,334,946!* Now, it’s worth noting Stock Advisor’s total average return is 958% — a market-crushing outperformance compared to 214% for the S&P 500. Don't miss the latest top 10 list, available with Stock Advisor, and join an investing community built by individual investors for individual investors. See the 10 stocks » *Stock Advisor returns as of August 12, 2026. This article is a transcript of this conference call produced for The Motley Fool. While we strive for our Foolish Best, there may be errors, omissions, or inaccuracies in this transcript. As with all our articles, The Motley Fool does not assume any responsibility for your use of this content, and we strongly encourage you to do your own research, including listening to the call yourself and reading the company's SEC filings. Please see our Terms and Conditions for additional details, including our Obligatory Capitalized Disclaimers of Liability. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a disclosure policy. Amplitude (AMPL) Q2 2026 Earnings Call Transcript was originally published by The Motley Fool

Find your next quality investment with Simply Wall St's easy and powerful screener, trusted by over 7 million individual investors worldwide. Amplitude (AMPL) drew fresh attention on August 5 after reporting second quarter 2026 results with revenue of $100.89 million, above consensus estimates, and issuing new guidance for the third quarter and full year. See our latest analysis for Amplitude. The earnings beat and fresh guidance have come alongside sharp share price momentum for Amplitude, with a 7 day share price return of 26.8% and a 90 day share price return of 76.2%, even though the 1 year total shareholder return is slightly lower overall. This pattern suggests short term enthusiasm around Amplitude's recent results while longer term holders have seen more modest outcomes. If Amplitude's recent jump has you thinking about where else growth stories could emerge, this is a good moment to scan 68 profitable AI stocks that aren't just burning cash. You might find other AI focused businesses with improving financial profiles. Amplitude now trades below both its analyst price target and an indicated estimate of fair value, even after the recent jump. Is that a bargain, or is it a reflection of the market’s caution toward ongoing losses? The most followed narrative currently places Amplitude's fair value at $11.36 using an 8.56% discount rate, which sits very close to the latest $11.26 close. That keeps attention firmly on the assumptions behind that fair value rather than on any huge gap to the market price. Read the complete narrative. Read the complete narrative. Want to see what sits behind that fair value for Amplitude? The narrative leans heavily on compounded revenue growth, improving margins and a richer mix from higher value contracts. Curious which long range earnings profile and valuation multiple are doing the heavy lifting here? The full narrative unpacks the numbers that support this pricing story. Result: Fair Value of $11.36 (UNDERVALUED) Have a read of the narrative in full and understand what's behind the forecasts. However, Amplitude still faces questions around how and when its AI products will be monetized, as well as whether higher infrastructure costs could limit any margin progress. Find out about the key risks to this Amplitude narrative. The fair value narrative presents Amplitude as almost in line with its $11.26 share price, yet the SWS DCF model points to a future cash flow value of $22.19. That is a very different signal. Is the market underpricing long term cash generation, or are the inputs too optimistic? Look into how the SWS DCF model arrives at its fair value. Mixed messages in the Amplitude story so far. If you want to move quickly and reach your own view, weigh up the 2 key rewards and 1 important warning sign If Amplitude has sharpened your focus, do not stop here. Use the Simply Wall Street Screener to uncover fresh opportunities that match your own approach. Target companies that look mispriced by the market and review 49 high quality undervalued stocks that may align with your return expectations. Strengthen your income stream by checking out 8 dividend fortresses that aim to combine sizeable yields with resilient fundamentals. Prioritise resilience in tougher conditions by focusing on 78 resilient stocks with low risk scores that show more stable risk scores and steadier financial profiles. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Companies discussed in this article include AMPL. Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email [email protected]

This article first appeared on GuruFocus. Release Date: August 05, 2026 For the complete transcript of the earnings call, please refer to the full earnings call transcript. Q2 revenue grew 21% year-over-year to $101 million, with total ARR up 22% to $410 million, including a $17 million contribution from StatSig. Customers with over $100K in ARR increased 30% year-over-year to 824, driven by both AI natives and large enterprises. AI-native transformation is driving efficiency: pull request cycle time cut from 5 hours to 44 minutes, bug reports down 55%, and 5% of PRs now submitted by non-engineers. New pricing and packaging is gaining traction, with 70% of Q2 ARR closed on the new model, leading to higher average ARR, multi-product attach, and longer contract durations. Record quarterly free cash flow of $23.7 million (24% of revenue), and the company returned $69 million via share repurchases. Wave, the self-improving product development tool, is showing early promise, automatically identifying and fixing issues (e.g., reducing search failures by 80% on Amplitude's docs site). Strong customer wins and expansions, including Paramount, Jaguar Land Rover, Domino's Pizza, and Coca-Cola Femsa, which scaled AI campaigns from 2,500 to 690,000 retailers. RPO grew 35% year-over-year to $483 million, with current RPO up 30% and long-term RPO up 47%, indicating strong future revenue visibility. Gross margin pressure is being offset by disciplined operating expense management, with sales and marketing down to 39% of revenue and G&A at 13%. The company raised full-year 2026 revenue and operating income guidance, reflecting confidence in continued growth and profitability. Gross margin declined to 71% in Q2, down 4 points sequentially and year-over-year, due to higher inference costs and StatSig integration. StatSig's gross margin is currently in the low 50s, well below the company's 70%+ target, and optimization will take time. Non-GAAP operating loss was $1.5 million in Q2, indicating the company is still not profitable on an operating basis. Net dollar retention was only 105% on a pro forma basis, suggesting limited expansion from existing customers. Organic ARR growth was $19 million, which annualizes to just under the 20% target, indicating the company is barely meeting its growth goal. The company faces challenges in educating customers about its expanded product suite, as many are unaware of new offerings like StatSig and Wave. Sales and marketing expenses, while down, still represent 39% of revenue, a high level that may limit margin expansion. The integration of StatSig is still in early stages, with the company needing to optimize the new hosting environment and cloud structure. The company expects gross margins to remain in the low 70s for now, which could pressure long-term profitability targets. The Q4 revenue guidance implies a deceleration in growth, which may raise concerns about sustainability. Warning! GuruFocus has detected 4 Warning Sign with AMPL. Is AMPL fairly valued? Test your thesis with our free DCF calculator. Q: Can you elaborate on the vision for Wave and how it might shift the buyer and addressable market, potentially moving away from bespoke agents toward a broader AI-native product development platform? A: Spencer Skates (CEO and Co-founder): Wave operates at a higher level than bespoke agents by continuously analyzing all data sources to recommend what to build next, plan those changes, and even execute them. We're seeing a convergence of engineers, product managers, and designers into an "AI builder" persona. While the core problem we solve remains the samehelping build better productsWave automates more of the process, making software self-improving. This doesn't change the executive buyer but transforms how digital product development is executed, with roles merging and data-driven recommendations replacing manual analysis. Q: The full-year guidance was raised by more than two times the beat for revenue and operating income. What are the key drivers of this increased growth expectation, and how are you managing margin leverage given COGS pressure and internal token spend? A: Andrew Casey (CFO): The guidance raise is driven by strong bookings reflected in our RPO, which provides better revenue predictability, and a pipeline that is progressing faster through stages due to new product capabilities, pricing, and packaging. On margins, we're focused on optimizing the StatSig hosting environment (currently in the low 50s gross margin) over time, while managing operating expenses lower. We're seeing strong upsell momentum as data ingestion versus entitlements is at an all-time high, which portends future expansions. Q: Given the strong organic ARR acceleration, how should we think about the impact of driving more operating leverage on the income statement, and what effect will that have on organic growth? A: Andrew Casey (CFO): Revenue growth will be the primary driver of increasing operating income. We expect gross margins to improve over time as we optimize costs, but it takes time, especially with the demand inflection and increased data ingestion. We're managing sales and marketing below 40% of revenue and G&A to the low teens, with room for further reductions. R&D will continue to be invested in for innovation, but we expect greater efficiencies as the team adopts AI capabilities. Q: Customers seem unaware of the full suite of modules and innovations rolled out this year, including the StatSig acquisition. Where are you in the sales enablement journey, and when will the salesforce be fully ramped? A: Spencer Skates (CEO and Co-founder): It's frustrating that many still bucket us as just an analytics company. We're investing heavily in educating our field team and customers about StatSig, Wave, and other products like session replay and AI feedback. We recently held a kickoff to showcase these capabilities. While we see customers moving from one to multiple products, it's slower than we'd like. The good news is customers are looking for proof we're at the bleeding edge, and our demos are resonating, even if they're not ready to adopt everything immediately. Q: Can you contextualize the cross-sell opportunity between Amplitude and StatSig, and how should we think about that flowing through the model long-term? A: Spencer Skates (CEO and Co-founder): The bigger opportunity is taking StatSig to Amplitude's customer base, as StatSig customers tend to be more bleeding-edge AI innovators. As traditional Amplitude customers look to build AI-native development processes and self-improving products, that's where StatSig fits. While there is some interest from StatSig customers in Amplitude, the Amplitude install base is much larger in both number and ARR, presenting a multi-hundred-million-dollar opportunity. Q: How have your hiring needs changed, and where are you seeing the best ROI from AI-driven efficiencies internally? A: Spencer Skates (CEO and Co-founder): We're focused on transforming the workforce by hiring AI-native talent, acquiring expertise, and retraining existing employees. Everyone is eager to learn AI to stay relevant. We're also leveraging new grads as a source of highly leveraged talent. Specifically for StatSig, we're adding data science leads and engineers familiar with that architecture. Internally, AI has shortened our closing process, reduced bug reports by 55%, and increased pull requests threefold, with 5% now submitted by non-engineers. Q: The 30% year-over-year increase in customers with over $100K ARR is impressive. Can you break out the adds from StatSig and what else is driving new logo momentum? A: Andrew Casey (CFO): About 40 customers came from the StatSig business, but even excluding those, we're still seeing nearly 23-24% growth in that cohort. These customers appreciate Amplitude's stewardship of the StatSig roadmap and are confident in expanding with us. The cross-sell opportunity is real, and we're excited about the multi-hundred-million-dollar potential in the install base. Q: If Wave is successful in finding problems, generating code, and measuring outcomes, why would customers need other Amplitude products like StatSig and product analytics? A: Spencer Skates (CEO and Co-founder): Wave relies on data from various sources, including Amplitude analytics and StatSig experimentation. It's not a standalone solution; it needs data to generate insights. The more data sources you feed it, the better the output. We plan to make Wave agnostic long-term, but having Amplitude's massive dataset gives us a competitive advantage in training Wave to recommend best practices. This creates a flywheel where Wave drives adoption of the broader platform, and the platform improves Wave's recommendations. Q: How are conversations going with customers about Wave driving platform adoption, and how should we think about Wave's monetization in the near term? A: Spencer Skates (CEO and Co-founder): Wave is already driving multi-product adoption, with customers signing up for session replay and AI feedback to feed Wave more data. We will absolutely charge for Wave, as the value it creates is immenseautomating the entire product development loop. While we're in alpha and haven't finalized pricing, customers are willing to pay for the direct line to better customer experience and revenue. We believe whoever wins this space will build a multi-billion-dollar business, and we're aggressively pursuing it. Q: What customer problems does Agent Analytics solve that current observability platforms cannot, and how do you view the market opportunity? A: Spencer Skates (CEO and Co-founder): Our unique positioning is connecting what happens within an AI session to long-term business impact. We can show whether For the complete transcript of the earnings call, please refer to the full earnings call transcript.

Annual Recurring Revenue of $410 million, up 22% year-over-year Remaining Performance Obligations of $483 million, up 35% year-over-year Second quarter revenue of $100.9 million, up 21% year-over-year Second quarter net cash provided by operations of $25.6 million and Free Cash Flow of $23.7 million SAN FRANCISCO, August 05, 2026--(BUSINESS WIRE)--Amplitude, Inc. (Nasdaq: AMPL), the leading AI analytics platform, today announced financial results for its second quarter ended June 30, 2026. "We have transformed to an AI Analytics company through our culture, our products, and how we’re working with our customers. We are closer than ever to self-improving products. Statsig & Amplitude is a powerful combination to measure what ships and ship what matters," said Spenser Skates, co-founder and CEO of Amplitude. "Our customers are using more of our AI solutions and looking to us to learn how to engage AI to accelerate their own development." "We delivered another quarter of solid execution with the integration of Statsig and core execution of Amplitude with each adding $17M and $19M in ARR, respectively," said Andrew Casey, CFO of Amplitude. "We are focused on driving innovation, delivering greater value, and making it easier for customers to work with Amplitude as we accelerate growth with leverage." Non-GAAP income (loss) from operations and non-GAAP net income (loss) per share exclude expenses related to stock-based compensation expense and related employer payroll taxes, amortization of acquired intangible assets, acquisition-related costs, and non-recurring costs such as restructuring and other related charges. Stock-based compensation expense and the related employer payroll taxes were $27.4 million in the second quarter of 2026 compared to $25.3 million in the second quarter of 2025. Amortization of acquired intangible assets was $1.0 million in the second quarter of 2026 compared to $0.3 million in the second quarter of 2025. Acquisition-related costs were $3.2 million in the second quarter of 2026, representing transition and integration expenses paid to third-parties. Non-GAAP financial measures for periods prior to the second quarter of 2026 were not adjusted to exclude acquisition-related costs, as such costs were not material to the Company's results of operations for those periods. Restructuring and other related charges were $2.1 million in the second quarter of 2026 and there were no restructuring and other related charges in the second quarter of 2025. Free cash flow is GAAP net cash provided by (used in) operating activities, less cash used for purchases of property and equipment and capitalized internal-use software costs. The section titled "Non-GAAP Financial Measures" below contains a description of the non-GAAP financial measures. Reconciliations of historical GAAP to non-GAAP information are presented in the accompanying tables. Second Quarter and Recent Business Highlights: Expanded Global Agent, a system-wide AI Agent that continuously understands customer behavior across charts, experiments, and sessions, answers questions, explains why metrics move, and takes action in real time. We also shipped Specialized Agents that asynchronously work to track performance, monitor conversion funnels, and analyze user sentiment while pushing updates into email or Slack. Expanded Model Context Protocol (MCP), a shared behavioral intelligence layer that brings trusted Amplitude insights directly into tools like Claude, Cursor, Slack, and Figma, enabling teams to act on customer data without leaving their workflow. Introduced Agent Analytics, a new analytics system that bridges product analytics and LLM observability, enabling teams to measure AI agent quality at scale, trace failures to root cause across prompts, tools, and context, and directly connect agent performance to business outcomes like retention, conversion, and revenue. Introduced Wave, an AI-driven system that continuously analyzes signals across analytics, session replays, feedback, and experiments to surface evidence-backed product opportunities. Each with a priority score, expected impact, and an execution plan teams or coding agents can act on directly, closing the loop from insight to shipped, measured work. Annual Recurring Revenue was $410 million, an increase of 22% year-over-year and an increase of $75 million compared to the second quarter of 2025. GAAP Net loss per share was $(0.27), based on 129.4 million basic shares, compared to a loss of $(0.19) per share, based on 131.4 million basic shares, in the second quarter of 2025. Non-GAAP Net loss per share was $(0.01), based on 129.4 million basic shares, compared to $0.01 net income per share, based on 140.2 million diluted shares, in the second quarter of 2025. Net cash provided by operating activities was $25.6 million, a $5.5 million increase year-over-year. Free Cash Flow was $23.7 million, a $5.5 million increase year-over-year. The number of customers with $100,000 or greater in ARR increased to 824, a 30% year-over-year growth. Financial Outlook: The third quarter and full year 2026 outlook information provided below is based on Amplitude’s current estimates and is not a guarantee of future performance. These statements are forward-looking and actual results may differ materially. Refer to the "Forward-Looking Statements" section below for information on the factors that could cause Amplitude’s actual results to differ materially from these forward-looking statements. For the third quarter and full year 2026, the Company expects: An outlook for GAAP income (loss) from operations, GAAP net income (loss), GAAP net income (loss) per share and a reconciliation of expected non-GAAP income (loss) from operations to GAAP income (loss) from operations, expected non-GAAP net income (loss) to GAAP net income (loss), and expected non-GAAP net income (loss) per share to GAAP net income (loss) per share have not been provided as the quantification of certain items included in the calculation of GAAP income (loss) from operations, GAAP net income (loss) and GAAP net income (loss) per share cannot be reasonably calculated or predicted at this time without unreasonable efforts. For example, the non-GAAP adjustment for stock-based compensation expense requires additional inputs such as the number and value of awards granted that are not currently ascertainable, and the non-GAAP adjustment for amortization of acquired intangible assets depends on the timing and value of intangible assets acquired that cannot be accurately forecasted. Conference Call Information: Amplitude will host a live video webcast to discuss its financial results for its second quarter ended June 30, 2026, as well as the financial outlook for its third quarter and full year 2026 today at 2:00 PM Pacific Time / 5:00 PM Eastern Time. Interested parties may access the webcast, earnings press release, and investor presentation on the events section of Amplitude’s investor relations website at investors.amplitude.com. A replay will be available in the same location a few hours after the conclusion of the live webcast. Forward-Looking Statements: This press release contains express and implied "forward-looking statements" within the meaning of the Private Securities Litigation Reform Act of 1995, including statements regarding the Company’s financial outlook for the third quarter and full year 2026, the opportunity for the use of AI to drive value for the Company going forward, the Company’s growth strategy and business aspirations and the Company's market position and market opportunity. These statements are often, but not always, made through the use of words or phrases such as "may," "should," "could," "predict," "potential," "believe," "expect," "continue," "will," "anticipate," "seek," "estimate," "intend," "plan," "projection," "would," and "outlook," or the negative version of those words or phrases or other comparable words or phrases of a future or forward-looking nature. These forward-looking statements are not statements of historical fact, and are based on current expectations, estimates, and projections about the Company’s industry as well as certain assumptions made by management, many of which, by their nature, are inherently uncertain and beyond the Company’s control. These statements are subject to numerous uncertainties and risks that could cause actual results, performance, or achievement to differ materially and adversely from those anticipated or implied in the statements, including risks related to: the Company’s limited operating history and rapid growth over the last several years, which makes it difficult to forecast the Company’s future results of operations; the Company’s history of losses; any decline in the Company’s customer retention or expansion of its commercial relationships with existing customers or an inability to attract new customers; expected fluctuations in the Company’s financial results, making it difficult to project future results; the highly competitive market in which the Company operates and developments in technology, including the deployment of AI in the Company’s products; the Company’s focus on sales to larger organizations and potentially increased dependency on those relationships, which may increase the variability of the Company’s sales cycles and results of operations; downturns or upturns in new sales, which may not be immediately reflected in the Company’s results of operations and may be difficult to discern; unfavorable conditions in the Company’s industry or the global economy, including as a result of the imposition of tariffs or other trade protection measures, or reductions in information technology spending, which could limit the Company’s ability to grow its business; the market for SaaS applications, which may develop more slowly than the Company expects or decline; the Company’s intellectual property rights, which may not protect its business or provide the Company with a competitive advantage; and evolving privacy and other data-related laws; and the impact of sanctions related to Russia on the Company’s ability to collect receivables. Additional risks and uncertainties that could cause actual outcomes and results to differ materially from those contemplated by the forward-looking statements are or will be included under the caption "Risk Factors" and elsewhere in the reports and other documents that the Company files with the Securities and Exchange Commission from time to time, including the Company’s Quarterly Report on Form 10-Q being filed at or around the date hereof. The forward-looking statements made in this press release relate only to events as of the date on which the statements are made. The Company undertakes no obligation to update any forward-looking statements made in this press release to reflect events or circumstances after the date of this press release or to reflect new information or the occurrence of unanticipated events, except as required by law. Non-GAAP Financial Measures: This press release includes financial information that has not been prepared in accordance with GAAP. The Company uses non-GAAP financial measures internally in analyzing its financial results and believes they are useful to investors, as a supplement to GAAP measures, in evaluating the Company’s ongoing operational performance. The Company believes that the use of these non-GAAP financial measures provides an additional tool for investors to use in evaluating ongoing operating results and trends and in comparing the Company’s financial results with other companies in the industry, many of which present similar non-GAAP financial measures to investors. There are a number of limitations related to the use of non-GAAP financial measures versus comparable financial measures determined under GAAP. For example, other companies in the Company’s industry may calculate these non-GAAP financial measures differently or may use other measures to evaluate their performance. In addition, free cash flow does not reflect the Company’s future contractual commitments and the total increase or decrease of its cash balance for a given period. Non-GAAP financial measures should not be considered in isolation from, or as a substitute for, financial information prepared in accordance with GAAP. A reconciliation of the Company’s non-GAAP financial measures to their most directly comparable GAAP measures has been provided in the financial statement tables included below in this press release. Investors are encouraged to review the reconciliation of these non-GAAP financial measures to their most directly comparable GAAP financial measures below. Non-GAAP Gross Profit, Non-GAAP Gross Margin, Non-GAAP Operating Expenses, Non-GAAP Income (Loss) from Operations, Non-GAAP Operating Margin, Non-GAAP Net Income (Loss), and Non-GAAP Net Income (Loss) per Share: The Company defines these non-GAAP financial measures as their respective GAAP measures, excluding expenses related to stock-based compensation expense and related employer payroll taxes, amortization of acquired intangible assets, acquisition related cost, and non-recurring costs such as restructuring and other related charges. The Company excludes stock-based compensation expense and related employer payroll taxes, which is a non-cash expense, from certain of its non-GAAP financial measures because it believes that excluding this item provides meaningful supplemental information regarding operational performance. The Company excludes amortization of intangible assets, which is a non-cash expense, related to business combinations from certain of its non-GAAP financial measures because such expenses are related to business combinations and have no direct correlation to the operation of the Company’s business. The Company excludes acquisition-related costs because they are directly attributable to the acquisition, are not reflective of the Company's ongoing cost structure, and are inconsistent in amount and frequency with the operation of its business. Although the Company excludes these expenses from certain non-GAAP financial measures, the revenue from acquired companies subsequent to the date of acquisition is reflected in these measures and the acquired intangible assets contribute to the Company’s revenue generation. The Company excludes non-recurring costs from certain of its non-GAAP financial measures because such expenses do not repeat period-over-period and are not reflective of the ongoing operation of the Company’s business. The Company uses non-GAAP gross profit, non-GAAP gross margin, non-GAAP operating expenses, non-GAAP income (loss) from operations, non-GAAP operating margin, non-GAAP net income (loss), and non-GAAP net income (loss) per share in conjunction with its traditional GAAP measures to evaluate the Company’s financial performance. The Company believes that these measures provide its management and investors consistency and comparability with its past financial performance and facilitate period-to-period comparisons of operations. Free Cash Flow and Free Cash Flow Margin: The Company defines free cash flow as net cash provided by (used in) operating activities, less cash used for purchases of property and equipment and capitalized internal-use software costs. Free cash flow margin is calculated as free cash flow divided by total revenue. The Company believes that free cash flow and free cash flow margin are useful indicators of liquidity that provide its management and investors with information about its potential ability to generate or use cash to enhance the strength of its balance sheet and further invest in its business and pursue potential strategic initiatives. Definitions of Business Metrics: Annual Recurring Revenue The Company defines Annual Recurring Revenue ("ARR") as the annual recurring revenue of subscription agreements at a point in time based on the terms of customers’ contracts, including certain premium services that are subject to contractual subscription terms and Plus customers that it expects to recur. ARR should be viewed independently of revenue, and does not represent the Company’s GAAP revenue on an annualized basis, as it is an operating metric that can be impacted by contract start and end dates and renewal rates. ARR is also not intended to be a forecast of revenue. Dollar-Based Net Retention Rate The Company calculates dollar-based net retention rate as of a period end by starting with the ARR from the cohort of all customers as of 12 months prior to such period-end (the "Prior Period ARR"). The Company then calculates the ARR from these same customers as of the current period-end (the "Current Period ARR"). Current Period ARR includes any expansion and is net of contraction or attrition over the last 12 months, but excludes ARR from new customers as well as any overage charges in the current period. The Company then divides the total Current Period ARR by the total Prior Period ARR to arrive at the dollar-based net retention rate ("NRR"). The Company then calculates the average of the trailing 12-month dollar-based net retention rates, to arrive at the dollar-based net retention rate ("NRR (TTM)"). Pro Forma Dollar-Based Net Retention Rate The Company also calculates a supplemental measure, Pro Forma Dollar-Based Net Retention Rate ("Pro Forma NRR"), which includes ARR from customers acquired through business combinations or asset acquisitions in both Current Period ARR and Prior Period ARR, as though the acquisition had occurred at the beginning of the prior period. The Company believes this supplemental measure provides useful information about the combined retention and expansion trends across the business. Pro Forma NRR and Pro Forma NRR (TTM) should not be considered in isolation from, or as a substitute for, the dollar-based net retention rate described above. About Amplitude: Amplitude is the leading AI analytics platform, helping over 5,200 paying customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 in Product Analytics for 24 consecutive quarters in G2's Summer 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com. View source version on businesswire.com: https://www.businesswire.com/news/home/20260805442643/en/ Contacts Investor RelationsJohn [email protected] Media [email protected]

Interested in Amplitude, Inc.? Here are five stocks we like better. Strong Q2 growth: Revenue rose 21% year over year to $100.9 million, while ARR increased 22% to $410 million, supported by enterprise expansion and $17 million of ARR from the Statsig acquisition. Free cash flow reached a record $23.7 million, though the company reported a $1.5 million non-GAAP operating loss. AI and product expansion remain central: Amplitude said AI agents now generate more than 40% of insights, while its Amplitude, Statsig and early-stage Wave products target analytics, experimentation and automated product development workflows. Enterprise customers represented more than 68% of ARR, and multi-product adoption continued to rise. 2026 outlook raised: Amplitude lifted its full-year revenue forecast to $407.2 million-$411.2 million and its non-GAAP operating income outlook to $6.3 million-$9.3 million. Gross margin fell to 71% because of AI inference costs and Statsig’s lower-margin hosting business, which the company expects to improve over time. Is Amplitude an AI Sleeper Stock in the Making for 2025? Amplitude (NASDAQ:AMPL) reported second-quarter 2026 revenue of $100.9 million, up 21% from a year earlier and 8% sequentially, as the product analytics company highlighted growth in enterprise customers, adoption of AI tools and the contribution from its Statsig acquisition. Total annual recurring revenue reached $410 million, increasing 22% year over year and $36 million from the first quarter. The sequential increase included $17 million in ARR from Statsig and $19 million in organic ARR growth. Customers generating more than $100,000 in ARR rose 30% year over year to 824. → SpaceX’s First Earnings Report Could Decide Whether Shorts or Bulls Have Control Non-GAAP operating loss was $1.5 million, while free cash flow reached a quarterly record of $23.7 million, or 24% of revenue. The company ended the quarter with about $162 million in cash and investments and repurchased $69 million of shares during the period. Amplitude said it has spent the past two years reshaping its organization around AI, including hiring AI-focused engineers and leaders with technical and founder backgrounds, acquiring AI expertise and retraining employees through internal programs. Spenser said the effort has resulted in three times as many pull requests over six months, a reduction in pull-request cycle time to 44 minutes from five hours, and a 55% decline in bug reports. → 3 Drone Stocks That Should Soar After the Summer Slump The company said 5% of pull requests are now submitted by designers and product managers without engineering involvement. Amplitude also used AI to shorten its financial close process by one day and to build customer-health dashboards combining its own data with Salesforce and other information sources. Amplitude outlined three products intended to support product-development workflows: Amplitude: Product analytics and AI agents designed to help users analyze product data and identify root causes of customer issues. Statsig: Feature management and experimentation technology that operates with cloud data warehouses, including Snowflake, BigQuery, Databricks and Redshift. Wave: An early product designed to synthesize data from analytics, experiments, session replay, surveys and other sources to recommend and help implement product changes. → The Bitcoin Comeback May Already Be Underway—2 ETFs for Exposure According to Spenser, Amplitude’s Global Agent handles 1.3 million interactions weekly and identifies the root cause behind 75% of customer questions. More than 40% of insights now come from AI agents rather than human users, the company said. Wave remains in alpha or limited beta, but Amplitude demonstrated an internal use case involving its documentation website. The product identified failed searches caused by a search feature that returned empty results while users typed. Wave recommended a minimum three-character search threshold and a 200-millisecond delay, generated a pull request, and helped deploy the change. The company said the update resulted in a substantial decline in search failures. Enterprise customers accounted for more than 68% of Amplitude’s ARR. During the quarter, the company cited new or expanded relationships with Paramount Global, Jaguar Land Rover, Domino’s Pizza, Teladoc Health, Chime, Disney Ad Platforms, F5 Networks, Coursera, Grammarly, Kraken and Crunch Fitness, among others. Amplitude said more than 40 AI-native companies pay it more than $100,000 annually, including Harvey, Midjourney and Character.ai, as well as an unnamed foundation-model company. The company also highlighted customer use cases. Coca-Cola FEMSA used Amplitude to measure AI-generated retailer recommendations, reporting an 11% click-through rate that was four times higher than its prior approach. Following a pilot involving 2,500 stores, Coca-Cola FEMSA expanded the effort to 690,000 retailers, Amplitude said. Replit uses Amplitude AI Feedback with sources including Zendesk, App Store reviews, Twitter and Reddit to identify customer issues affecting retention and engagement. The Economist uses Amplitude Agent Analytics to evaluate its Lens AI assistant. Amplitude said Lens has a 96.9% task-success rate and weekly failures have fallen 84%. Chief Financial Officer Andrew Casey said Amplitude’s new pricing and packaging model is gaining adoption. Seventy percent of ARR closed in the second quarter used the new model, compared with 25% in the first quarter. The new pricing structure represented 28% of total ARR at quarter-end. Casey said the model uses a single meter, is intended to make product additions simpler for enterprise customers and has supported higher average ARR, greater multi-product adoption and longer contract durations. Forty-eight percent of customers now use multiple products, representing 80% of ARR. More than 26% of ARR came from customers using five or more products, double the level from a year earlier. Net dollar retention was 105% on a pro forma basis, including both Amplitude and Statsig customers. Remaining performance obligations increased 35% year over year to $483 million. Gross margin was 71%, down about four percentage points year over year and sequentially. Casey attributed the decline to rising inference costs tied to AI-tool usage and the integration of Statsig’s hosting environment. He said the Statsig business currently has gross margins in the low 50% range, with Amplitude working toward a 70%-plus long-term expectation for that business. Sales and marketing expense declined to 39% of revenue from 44% a year earlier, while general and administrative expense was 13% of revenue. Research and development expense rose to 21% of revenue as Amplitude invested in Statsig and product innovation. For the third quarter, Amplitude forecast revenue of $105.6 million to $108 million, representing 21% growth at the midpoint. It expects non-GAAP operating income of $2.5 million to $4.5 million and non-GAAP earnings per share of $0.02 to $0.03. For the full year, the company raised its revenue outlook to $407.2 million to $411.2 million, implying 19% growth at the midpoint. It also increased its forecast for non-GAAP operating income to $6.3 million to $9.3 million and projected non-GAAP earnings per share of $0.06 to $0.08. Casey said Amplitude expects to manage operating expenses lower as a percentage of revenue while continuing to invest in research and development. Spenser reiterated a long-term objective of building a business with operating margins above 20%, while stating that the company aims to exceed 20% revenue growth and ultimately target growth closer to 30% and above. Amplitude, Inc is a software company specializing in digital analytics and product intelligence solutions for businesses seeking to optimize user engagement and drive growth. Its core offering, the Amplitude Analytics platform, enables customers to collect and analyze behavioral data from web and mobile applications in real time. The platform provides advanced segmentation, funnel analysis, retention tracking and pathfinding tools that help product, marketing and data teams understand user journeys, identify friction points and measure the impact of new features. Founded in 2012 by Spenser Skates, Curtis Liu and Jeffrey Wang, Amplitude is headquartered in Redwood City, California, with additional offices spanning North America, Europe and Asia. This instant news alert was generated by narrative science technology and financial data from MarketBeat in order to provide readers with the fastest reporting and unbiased coverage. Please send any questions or comments about this story to [email protected]. The article "Amplitude Q2 Earnings Call Highlights" was originally published by MarketBeat. View MarketBeat's top stocks for August 2026.

The market expects Red Cat Holdings, Inc. (RCAT) to deliver a year-over-year decline in earnings on higher revenues when it reports results for the quarter ended June 2026. This widely-known consensus outlook is important in assessing the company's earnings picture, but a powerful factor that might influence its near-term stock price is how the actual results compare to these estimates. The stock might move higher if these key numbers top expectations in the upcoming earnings report, which is expected to be released on August 6. On the other hand, if they miss, the stock may move lower. While the sustainability of the immediate price change and future earnings expectations will mostly depend on management's discussion of business conditions on the earnings call, it's worth handicapping the probability of a positive EPS surprise. This company is expected to post quarterly loss of $0.21 per share in its upcoming report, which represents a year-over-year change of -50%. Revenues are expected to be $22.31 million, up 592.9% from the year-ago quarter. The consensus EPS estimate for the quarter has remained unchanged over the last 30 days. This is essentially a reflection of how the covering analysts have collectively reassessed their initial estimates over this period. Investors should keep in mind that an aggregate change may not always reflect the direction of estimate revisions by each of the covering analysts. Price, Consensus and EPS Surprise Estimate revisions ahead of a company's earnings release offer clues to the business conditions for the period whose results are coming out. Our proprietary surprise prediction model -- the Zacks Earnings ESP (Expected Surprise Prediction) -- has this insight at its core. The Zacks Earnings ESP compares the Most Accurate Estimate to the Zacks Consensus Estimate for the quarter; the Most Accurate Estimate is a more recent version of the Zacks Consensus EPS estimate. The idea here is that analysts revising their estimates right before an earnings release have the latest information, which could potentially be more accurate than what they and others contributing to the consensus had predicted earlier. Thus, a positive or negative Earnings ESP reading theoretically indicates the likely deviation of the actual earnings from the consensus estimate. However, the model's predictive power is significant for positive ESP readings only. A positive Earnings ESP is a strong predictor of an earnings beat, particularly when combined with a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold). Our research shows that stocks with this combination produce a positive surprise nearly 70% of the time, and a solid Zacks Rank actually increases the predictive power of Earnings ESP. Please note that a negative Earnings ESP reading is not indicative of an earnings miss. Our research shows that it is difficult to predict an earnings beat with any degree of confidence for stocks with negative Earnings ESP readings and/or Zacks Rank of 4 (Sell) or 5 (Strong Sell). For Red Cat, the Most Accurate Estimate is lower than the Zacks Consensus Estimate, suggesting that analysts have recently become bearish on the company's earnings prospects. This has resulted in an Earnings ESP of -1.61%. On the other hand, the stock currently carries a Zacks Rank of #3. So, this combination makes it difficult to conclusively predict that Red Cat will beat the consensus EPS estimate. Analysts often consider to what extent a company has been able to match consensus estimates in the past while calculating their estimates for its future earnings. So, it's worth taking a look at the surprise history for gauging its influence on the upcoming number. For the last reported quarter, it was expected that Red Cat would post a loss of$0.14 per share when it actually produced a loss of -$0.22, delivering a surprise of -57.14%. The company has not been able to beat consensus EPS estimates in any of the last four quarters. An earnings beat or miss may not be the sole basis for a stock moving higher or lower. Many stocks end up losing ground despite an earnings beat due to other factors that disappoint investors. Similarly, unforeseen catalysts help a number of stocks gain despite an earnings miss. That said, betting on stocks that are expected to beat earnings expectations does increase the odds of success. This is why it's worth checking a company's Earnings ESP and Zacks Rank ahead of its quarterly release. Make sure to utilize our Earnings ESP Filter to uncover the best stocks to buy or sell before they've reported. Red Cat doesn't appear a compelling earnings-beat candidate. However, investors should pay attention to other factors too for betting on this stock or staying away from it ahead of its earnings release. Amplitude, Inc. (AMPL), another stock in the Zacks Technology Services industry, is expected to report loss per share of $0.01 for the quarter ended June 2026. This estimate points to a year-over-year change of -200%. Revenues for the quarter are expected to be $97.81 million, up 17.5% from the year-ago quarter. The consensus EPS estimate for Amplitude has been revised 0.4% higher over the last 30 days to the current level. However, a higher Most Accurate Estimate has resulted in an Earnings ESP of +12.50%. When combined with a Zacks Rank of #3 (Hold), this Earnings ESP indicates that Amplitude will most likely beat the consensus EPS estimate. Over the last four quarters, the company surpassed EPS estimates just once. Stay on top of upcoming earnings announcements with the Zacks Earnings Calendar. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Red Cat Holdings, Inc. (RCAT) : Free Stock Analysis Report Amplitude, Inc. (AMPL) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research

Wall Street expects a year-over-year decline in earnings on higher revenues when Amplitude, Inc. (AMPL) reports results for the quarter ended June 2026. While this widely-known consensus outlook is important in gauging the company's earnings picture, a powerful factor that could impact its near-term stock price is how the actual results compare to these estimates. The earnings report, which is expected to be released on August 5, might help the stock move higher if these key numbers are better than expectations. On the other hand, if they miss, the stock may move lower. While management's discussion of business conditions on the earnings call will mostly determine the sustainability of the immediate price change and future earnings expectations, it's worth having a handicapping insight into the odds of a positive EPS surprise. This company is expected to post quarterly loss of $0.01 per share in its upcoming report, which represents a year-over-year change of -200%. Revenues are expected to be $97.81 million, up 17.5% from the year-ago quarter. The consensus EPS estimate for the quarter has been revised 0.38% higher over the last 30 days to the current level. This is essentially a reflection of how the covering analysts have collectively reassessed their initial estimates over this period. Investors should keep in mind that the direction of estimate revisions by each of the covering analysts may not always get reflected in the aggregate change. Price, Consensus and EPS Surprise Estimate revisions ahead of a company's earnings release offer clues to the business conditions for the period whose results are coming out. This insight is at the core of our proprietary surprise prediction model -- the Zacks Earnings ESP (Expected Surprise Prediction). The Zacks Earnings ESP compares the Most Accurate Estimate to the Zacks Consensus Estimate for the quarter; the Most Accurate Estimate is a more recent version of the Zacks Consensus EPS estimate. The idea here is that analysts revising their estimates right before an earnings release have the latest information, which could potentially be more accurate than what they and others contributing to the consensus had predicted earlier. Thus, a positive or negative Earnings ESP reading theoretically indicates the likely deviation of the actual earnings from the consensus estimate. However, the model's predictive power is significant for positive ESP readings only. A positive Earnings ESP is a strong predictor of an earnings beat, particularly when combined with a Zacks Rank #1 (Strong Buy), 2 (Buy) or 3 (Hold). Our research shows that stocks with this combination produce a positive surprise nearly 70% of the time, and a solid Zacks Rank actually increases the predictive power of Earnings ESP. Please note that a negative Earnings ESP reading is not indicative of an earnings miss. Our research shows that it is difficult to predict an earnings beat with any degree of confidence for stocks with negative Earnings ESP readings and/or Zacks Rank of 4 (Sell) or 5 (Strong Sell). For Amplitude, the Most Accurate Estimate is higher than the Zacks Consensus Estimate, suggesting that analysts have recently become bullish on the company's earnings prospects. This has resulted in an Earnings ESP of +12.50%. On the other hand, the stock currently carries a Zacks Rank of #3. So, this combination indicates that Amplitude will most likely beat the consensus EPS estimate. While calculating estimates for a company's future earnings, analysts often consider to what extent it has been able to match past consensus estimates. So, it's worth taking a look at the surprise history for gauging its influence on the upcoming number. For the last reported quarter, it was expected that Amplitude would post a loss of$0.01 per share when it actually produced a loss of -$0.02, delivering a surprise of -100.00%. Over the last four quarters, the company has beaten consensus EPS estimates just once. An earnings beat or miss may not be the sole basis for a stock moving higher or lower. Many stocks end up losing ground despite an earnings beat due to other factors that disappoint investors. Similarly, unforeseen catalysts help a number of stocks gain despite an earnings miss. That said, betting on stocks that are expected to beat earnings expectations does increase the odds of success. This is why it's worth checking a company's Earnings ESP and Zacks Rank ahead of its quarterly release. Make sure to utilize our Earnings ESP Filter to uncover the best stocks to buy or sell before they've reported. Amplitude appears a compelling earnings-beat candidate. However, investors should pay attention to other factors too for betting on this stock or staying away from it ahead of its earnings release. Among the stocks in the Zacks Technology Services industry, Enpro (NPO), is soon expected to post earnings of $2.3 per share for the quarter ended June 2026. This estimate indicates a year-over-year change of +13.3%. This quarter's revenue is expected to be $322.9 million, up 12.1% from the year-ago quarter. The consensus EPS estimate for Enpro has been revised 0.3% higher over the last 30 days to the current level. However, a higher Most Accurate Estimate has resulted in an Earnings ESP of +0.87%. When combined with a Zacks Rank of #2 (Buy), this Earnings ESP indicates that Enpro will most likely beat the consensus EPS estimate. Over the last four quarters, the company surpassed consensus EPS estimates three times. Stay on top of upcoming earnings announcements with the Zacks Earnings Calendar. Want the latest recommendations from Zacks Investment Research? Today, you can download 7 Best Stocks for the Next 30 Days. Click to get this free report Amplitude, Inc. (AMPL) : Free Stock Analysis Report Enpro Inc. (NPO) : Free Stock Analysis Report This article originally published on Zacks Investment Research (zacks.com). Zacks Investment Research

Amplitude’s first quarter was marked by robust revenue growth and incremental operational improvements, but the market responded negatively due to persistent losses and increased cost pressures. Management attributed the quarter’s results to rapid adoption of new AI-driven capabilities, expanded multiproduct usage among enterprise clients, and significant organizational shifts. CEO Spenser Skates noted that “90% of the code our team ships today is written by AI,” emphasizing how quickly the company is transforming its development process. However, increased AI usage has driven up inference costs, pressuring gross margins and contributing to a non-GAAP operating loss. Is now the time to buy AMPL? Find out in our full research report (it’s free). Revenue: $93.49 million vs analyst estimates of $92.94 million (16.9% year-on-year growth, 0.6% beat) Adjusted EPS: -$0.02 vs analyst estimates of -$0.01 ($0.01 miss) Adjusted Operating Income: -$3.12 million vs analyst estimates of -$3.29 million (-3.3% margin, relatively in line) The company lifted its revenue guidance for the full year to $400 million at the midpoint from $394 million, a 1.5% increase Management lowered its full-year Adjusted EPS guidance to $0.05 at the midpoint, a 57.1% decrease Operating Margin: -25.8%, up from -30.3% in the same quarter last year Customers: 727 customers paying more than $100,000 annually Net Revenue Retention Rate: 106%, up from 104% in the previous quarter Annual Recurring Revenue: $374 million vs analyst estimates of $372.7 million (16.9% year-on-year growth, in line) Billings: $105 million at quarter end, up 20.3% year on year Market Capitalization: $819.6 million While we enjoy listening to the management's commentary, our favorite part of earnings calls are the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention. Taylor McGinnis (UBS): Asked why OpenAI chose to transfer the Statsig business and whether Amplitude’s organic growth guidance was reduced. CEO Spenser Skates explained OpenAI will retain Statsig for internal use, while CFO Andrew Casey clarified that accounting adjustments, not underlying performance, affected the reported growth rates. Robert Oliver (R.W. Baird): Questioned the impact of the new pricing model and whether Statsig’s integration would further pressure margins. Casey highlighted positive early results from the pricing changes, and Skates acknowledged that integration costs would be better understood in subsequent quarters. Jackson Ader (KeyBanc): Inquired about balancing frictionless AI-driven adoption with the need for technical support in the enterprise segment. Skates noted that while AI automation accelerates initial setup, human expertise is still essential for large, traditional customers seeking education and integration assistance. Clark Wright (D.A. Davidson): Sought details on how the new pricing curve supports enterprise scaling and what the Statsig partnership unlocks. Casey described favorable customer feedback on cost predictability, while Skates emphasized new access to data warehouse budgets and enhanced experimentation tools. Scott Berg (Needham): Asked about gross margin pressures from AI inference costs and the role of open source models. Skates said most customers prefer the latest models for accuracy, which are more expensive, but over time, Amplitude will optimize model choices to balance cost and performance. In the coming quarters, the StockStory team will watch (1) how quickly Statsig’s integration delivers incremental ARR and meaningful cross-sell, (2) the pace of customer migration to Amplitude’s new pricing and packaging model, and (3) whether gross margin stabilizes as AI adoption matures and infrastructure optimization efforts take hold. Additionally, the evolution of AI-native features and client feedback on workflow automation will be key indicators of future performance. Amplitude currently trades at $6.19, down from $7.52 just before the earnings. Is the company at an inflection point that warrants a buy or sell? Find out in our full research report (it’s free for active Edge members). ONE MORE THING: Top 5 Growth Stocks. The biggest stock winners almost always had one thing in common before they ran. Revenue growing like crazy. Meta. CrowdStrike. Broadcom. Our AI flagged all three. They returned 315%, 314%, and 455%, respectively. Find out which 5 stocks it's flagging for this month - FREE. Get Our Top 5 Growth Stocks for Free HERE. Stocks that have made our list include now familiar names such as Nvidia (+1,326% between June 2020 and June 2025) as well as under-the-radar businesses like the once-micro-cap company Tecnoglass (+1,754% five-year return). Find your next big winner with StockStory today.