Amplitude Inc (AMPL) 2025 Q3 法說會逐字稿

(audio in progress), everyone. Welcome to Amplitude's third-quarter 2025 earnings conference call.

（音訊正在播放）各位。歡迎參加 Amplitude 2025 年第三季財報電話會議。

I'm John Streppa, Head of Investor Relations. Joining me today are Spenser Skates, CEO and Co-Founder of Amplitude; and Andrew Casey, Chief Financial Officer.

我是投資者關係主管約翰‧斯特雷帕。今天與我一同出席的有 Amplitude 的執行長兼共同創辦人 Spenser Skates，以及財務長 Andrew Casey。

During today's call, management will make forward-looking statements, including statements regarding our financial outlook for the fourth-quarter and full-year 2025, the expected performance of our products, our expected quarterly and long-term growth, investments, and our overall future prospects.

在今天的電話會議上，管理層將發表前瞻性聲明，包括有關我們對 2025 年第四季度和全年財務展望、我們產品的預期表現、我們預期的季度和長期增長、投資以及我們整體未來前景的聲明。

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.

這些前瞻性陳述是基於當前資訊、假設和預期；並受到風險和不確定性的影響，其中一些風險和不確定性是我們無法控制的，可能導致實際結果與這些陳述中描述的結果有重大差異。

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. We assume no obligation to update these statements after today's call, except as required by law.

有關可能導致實際結果與預期結果存在差異的風險的更多信息，請參閱我們向美國證券交易委員會提交的文件。請注意，不要過度依賴這些前瞻性陳述。除法律另有規定外，我們不承擔在今天的電話會議後更新這些聲明的義務。

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.

今天電話會議中使用的某些財務指標是按非GAAP準則表示的。我們內部使用這些非GAAP財務指標，以便分析我們的財務和業務趨勢，並用於內部規劃和預測。這些非公認會計準則財務指標有其局限性，不應脫離公認會計準則所編製的財務資訊單獨使用，也不應取代後者。

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.

有關這些非GAAP財務指標的更多資訊以及這些GAAP和非GAAP財務指標之間的調節表，請參閱我們的盈利新聞稿和補充財務信息，這些資料可在我們的投資者關係網站 investors.amplitude.com 上找到。

With that, I'll hand the call over to Spenser.

這樣，我就把電話交給史賓塞了。

Good afternoon, everyone. Welcome to Amplitude's third-quarter 2025 earnings call.

大家下午好。歡迎參加 Amplitude 2025 年第三季財報電話會議。

Today, I'm going to cover three things: first, our strong Q3 results and progress in the enterprise; second, the AI opportunity within analytics; third, product innovation and our customers. Let's go ahead and get started with our Q3 results.

今天，我將介紹三件事：第一，我們強勁的第三季業績和企業發展進展；第二，人工智慧在分析領域的機會；第三，產品創新和我們的客戶。接下來，我們開始看一下第三季的業績報告。

We delivered another strong quarter, continuing the acceleration we saw in Q2. We exceeded expectations on our core financial metrics and made solid progress against our enterprise strategy.

我們又迎來了一個強勁的季度，延續了第二季度以來的加速成長動能。我們在核心財務指標方面超越了預期，並在企業策略方面取得了穩步進展。

Our third-quarter revenue was $88.6 million, up 18% year over year and exceeding the high end of our guidance. Annual recurring revenue was $347 million, up 16% year over year and up $12 million from last quarter. Non-GAAP operating income was $0.6 million. Customers with more than $100,000 in ARR grew to 653, an increase of 15% year over year.

我們第三季營收為 8,860 萬美元，年成長 18%，超過了我們預期的上限。年度經常性收入為 3.47 億美元，年增 16%，比上一季成長 1,200 萬美元。非GAAP營業收入為60萬美元。年度經常性收入超過 10 萬美元的客戶數量增至 653 家，年增 15%。

Our Q3 performance reflects our continued execution against our strategy. We are winning simple by bringing Amplitude to everyone with AI. We are winning the enterprise with broad-based success, with both AI natives and traditional enterprises, securing larger multiyear contracts. We're winning the category with multiproduct adoption now representing 71% of our ARR. Finally, we're winning together by leading the shift to being AI native across the entire Amplitude team.

第三季業績反映了我們持續貫徹執行既定策略。我們透過人工智慧將Amplitude帶給每個人，從而贏得勝利。我們憑藉著廣泛的成功贏得了企業市場，無論是人工智慧原生企業還是傳統企業，都獲得了更大的多年合約。我們憑藉多產品採用率在該類別中勝出，目前多產品採用率已占我們年度經常性收入的 71%。最後，我們透過引領整個 Amplitude 團隊向 AI 原生技術轉型，共同取得了勝利。

I wanted to take a little bit of time to talk about how AI is changing how software gets built. Every single product team runs the same loop: build, ship, use, and learn.

我想花點時間談談人工智慧如何改變軟體的建構方式。每個產品團隊都遵循同樣的循環：建立、發布、使用和學習。

The left side of that loop, build and ship, has been transformed by AI. AI coding has made it faster than ever to turn ideas into products. We are now at a point where someone can create a product that's used by millions overnight.

該循環的左側部分（建造和交付）已經因人工智慧而改變。人工智慧程式設計使得將創意轉化為產品的速度比以往任何時候都更快。現在，任何人都可以創造出一夜之間被數百萬人使用的產品。

By contrast, the right side of this loop, use and learn, remains in the stone ages. Companies ask users what they want but actions are more powerful than words. The best way to understand what people want is to watch what they do.

相較之下，這個循環的右邊——使用和學習——仍然停留在石器時代。企業會詢問用戶想要什麼，但行動比言語更有力量。了解人們想要什麼的最好方法就是觀察他們的行為。

This is what Amplitude solves. Our AI analytics platform helps companies understand how people engage in their product, what they like, where they get stuck, and what keeps them coming back. These behavioral signals are the most powerful indicator for what to build. Automating and scaling that understanding is the next frontier.

這就是 Amplitude 要解決的問題。我們的人工智慧分析平台幫助公司了解人們如何使用他們的產品，他們喜歡什麼，他們在哪裡遇到困難，以及是什麼讓他們不斷回來。這些行為訊號是指導產品開發方向的最強指標。將這種理解自動化並擴大其規模是下一個前沿領域。

In this context, analytics is the perfect problem for AI to solve. To use analytics, you have to do a lot of manual work in specifying and setting up your query in between rounds of thinking. AI can handle all of that manual work, freeing up humans to focus on the thinking that leads to great insights.

在此背景下，數據分析正是人工智慧最適合解決的問題。要使用分析功能，你需要在反覆思考的過程中，手動完成大量的查詢指定和設定工作。人工智慧可以處理所有這些人工工作，使人類能夠專注於產生偉大見解的思考。

Amplitude has a unique position to build the AI analytics platform of the future. We have the world's largest database of product behavior. We have spent a decade working with world-class analytics teams.

Amplitude 在建立未來的 AI 分析平台方面擁有獨特的優勢。我們擁有全球最大的產品行為資料庫。我們與世界一流的分析團隊合作了十年。

Over the past year, we've rebuilt the Amplitude team to be AI native. We've reorganized product development twice, and we've acquired four AI companies. We've trained our engineering, product management and design teams deeply in AI.

過去一年，我們對 Amplitude 團隊進行了重組，使其成為人工智慧原生團隊。我們已經兩度重組產品開發部門，並且收購了四家人工智慧公司。我們對工程、產品管理和設計團隊進行了人工智慧的深入培訓。

The company that disrupts the right side of this loop, the use and learn, the fastest will define the future of this space. We are all in here.

能夠最快顛覆這個循環的正確一方（即使用和學習）的公司，將定義這個領域的未來。我們都在這裡。

Let's get into the details on product innovation. In the last few weeks, we have launched several AI-native products here at Amplitude.

讓我們深入探討一下產品創新。在過去的幾周里，我們在 Amplitude 推出了幾款 AI 原生產品。

I want to start with MCP. In October, we announced the public availability of our MCP server, the top requested feature from our customers. MCP is made for data analytics. It exposes all of Amplitude's functionality so an AI agent can interact with it directly. It allows you to use Amplitude without knowing anything about the Amplitude UI or your data taxonomy.

我想先從MCP開始。10 月份，我們宣布 MCP 伺服器正式上線，這是我們客戶最期待的功能。MCP專為資料分析設計。它公開了 Amplitude 的所有功能，以便 AI 代理可以直接與其互動。它允許您在不了解 Amplitude 使用者介面或資料分類的情況下使用 Amplitude。

This is the best MCP use case that I have ever seen. Watching an AI agent think, reason, query Amplitude and then, repeat that process iteratively is magical. It shows what is possible in the AI analytics future I talked about earlier. It brings the power of our data to anyone in any workflow. This opens Amplitude up to an entirely new cohort of nontechnical users, in turn driving our growth.

這是我見過的最好的 MCP 應用案例。看著人工智慧代理思考、推理、查詢 Amplitude，然後迭代地重複這個過程，真是太神奇了。它展現了我之前提到的AI分析未來可能實現的前景。它將我們數據的力量帶給任何工作流程中的任何人。這為 Amplitude 帶來了全新的非技術用戶群體，推動了我們的成長。

Let me show you with a quick demo. MCP lets AI tools interact directly with Amplitude data. You can ask a vague question about your product inside any AI model and have a query Amplitude iteratively.

讓我用一個簡單的演示來給你展示一下。MCP 讓 AI 工具直接與 Amplitude 資料互動。你可以在任何 AI 模型中提出關於你產品的模糊問題，並迭代地向 Amplitude 進行查詢。

Our MCP already has native connections to Claude, Cursor and GitHub with more to come soon. For this demo, I'm going to use Claude. I'm going to start with a simple prompt, give me high-level web traffic metrics. Claude will then get contacts, search web traffic metrics and then it's identified that during the week of September 21, we've had a peak. I can then ask follow-up questions to drill down, investigate the September spike.

我們的 MCP 已經與 Claude、Cursor 和 GitHub 建立了原生連接，未來也將支援更多平台。在這個演示中，我將使用克勞德。我先提一個簡單的要求：請提供一些網站流量的進階指標。克勞德隨後會取得聯絡方式，搜尋網站流量指標，然後發現 9 月 21 日那一周，我們的流量達到了高峰。然後我可以提出後續問題，深入調查九月份的高峰。

What's driving this growth? Claude then accesses behavioral insights, checks traffic sources, marketing campaigns and content performance. It shows that our webinar campaigns and the release of our product benchmark report drove this traffic. To get deeper insights, I'm going to ask, what are the downstream growth metric impacts by these campaigns? Claude then queries the campaign data set, downstream conversion funnels and sales force metrics.

是什麼因素推動了這種成長？然後，克勞德會獲取行為洞察，檢查流量來源、行銷活動和內容表現。這表明，我們的網路研討會活動和產品基準報告的發布帶來了這些流量。為了獲得更深入的了解，我想問，這些活動對下游成長指標有何影響？然後，Claude 查詢了行銷活動資料集、下游轉換漏斗和銷售團隊指標。

It concludes that the September campaigns drove a higher number and quality of visitors to the site. Of course, I'm going to want to share these findings so I can prompt it to create an Amplitude notebook for the growth team. So in a few minutes, customers can get deep research, insights and a detailed shareable notebook that allows them to take action.

報告總結稱，9 月的推廣活動為網站帶來了更多更高品質的訪客。當然，我打算分享這些發現，以便促使它為成長團隊創建一個 Amplitude 筆記本。因此，只需幾分鐘，客戶即可獲得深入的研究、見解和詳細的可共享筆記本，從而採取行動。

In addition to the launch of MCP, we expanded the open beta for our AI agents. These agents continually monitor product data, detect anomalies and surface insights automatically. In June, we launched our closed beta. And then two weeks ago, we opened the beta to all customers. Our focus is now on two agents.

除了推出 MCP 之外，我們還擴大了 AI 代理的公開測試範圍。這些代理程式會持續監控產品數據，偵測異常情況並自動提供洞察資訊。六月份，我們啟動了封閉測試。兩週前，我們向所有客戶開放了測試版。我們現在的重點是兩名經紀人。

The first is the Dashboard Agent, which analyzes charts and proactively flag significant changes. And the second is the Session Replay Agent, which reviews thousands of user sessions, detects points of friction and then shows curated clips that highlight issues. Both are powered by the same behavioral data that MCP can access. They are already helping customers uncover opportunities and resolve issues faster.

第一個是儀表板代理，它可以分析圖表並主動標記重大變化。第二個是會話回放代理，它會審查數千個使用者會話，偵測摩擦點，然後顯示精選片段來突出問題。兩者都基於MCP可以存取的相同行為資料。他們已經開始幫助客戶發現機會並更快解決問題。

In addition, last week, we also introduced AI Visibility. As consumers turn to AI tools like ChatGPT, Claude and Google's AI summary when they search, marketers are flying blind. They have no idea how their companies show up or rank within the results produced by these new tools. To solve that problem, we launched AI Visibility for free last week. Think of it as SEO for LLMs.

此外，上週我們也推出了 AI 視覺性。當消費者在搜尋時轉向使用 ChatGPT、Claude 和 Google 的 AI 摘要等 AI 工具時，行銷人員就像在盲目摸索。他們完全不知道自己的公司在這些新工具產生的結果中是如何顯示或排名的。為了解決這個問題，我們上週免費推出了 AI Visibility 功能。你可以把它想像成法學碩士的搜尋引擎優化。

It shows where a brand appears or doesn't across all major AI models, how they rank against competitors and how they can improve their position. We saw a lot of excitement around the launch with our customers and on social media. The conversation about the future of AI Visibility is still going today on Twitter. Let me show you a quick demo of this, too.

它顯示了品牌在所有主要人工智慧模型中的出現情況（或未出現情況），與競爭對手相比的排名，以及如何提高自己的排名。我們看到客戶和社群媒體上對此次發布都非常興奮。關於人工智慧可視性未來的討論至今仍在推特上繼續進行。我也為你做一個簡單的示範。

Understanding how your products appear in AI responses and improving it will be the key to increasing awareness. With AI Visibility, customers can now see the percentage of mentions of their product and AI responses. They can also see competitor mentions versus their own and then topics by visibility. They can dig into prompts to see the exact questions customers are asking and how AI is answering. For example, when people ask LLMs for product-led growth tools, they mention Amplitude 90% of the time.

了解您的產品在人工智慧回應中的呈現方式並加以改進，將是提高品牌知名度的關鍵。借助 AI 可視性，客戶現在可以看到其產品被提及的百分比以及 AI 的回應。他們還可以查看競爭對手提及自己內容的次數與提及次數的對比，以及按可見度劃分的話題。他們可以深入分析提示訊息，了解客戶提出的具體問題以及人工智慧是如何回答的。例如，當人們向LLM（法學碩士）諮詢產品驅動型成長工具時，他們90%的情況下都會提到Amplitude。

Customers can also learn how to improve their ranking. I can use the Analyze page to see how AI interprets the existing content or run a series of simulated changes to test updates before publishing. AI Visibility tracks your brand and helps you turn that visibility into growth.

客戶還可以學習如何提高排名。我可以使用「分析」頁面來查看 AI 如何解釋現有內容，或執行一系列模擬變更來測試更新，然後再發布。AI Visibility 可以追蹤您的品牌，並幫助您將這種知名度轉化為成長。

Finally, next week, we will launch AI Feedback. This is our newest AI-native product based on the core offering from our Kraftful acquisition in July. We're going from acquisition to new Amplitude product launch in four months. AI Feedback takes user feedback and information from multiple sources and turns it into insights a company can use. By bringing feedback, behavior and action into a single platform, it helps teams hear customers and understand them.

最後，下週我們將推出人工智慧回饋功能。這是我們最新的AI原生產品，基於我們7月收購Kraftful的核心產品。我們將在四個月內完成從收購到推出全新 Amplitude 產品的整個過程。AI回饋系統會收集來自多個來源的使用者回饋和訊息，並將其轉化為公司可以使用的洞察。透過將回饋、行為和行動整合到一個平台上，它可以幫助團隊傾聽客戶的聲音並了解客戶。

Let me show you with my last demo.

讓我用我最後的演示來給你展示一下。

AI Feedback is the new way to listen to users at scale and act on their feedback. AI Feedback collects input from all of our customers' feedback sources. You can link Zendesk tickets, Gong call transcriptions, App Store reviews, comments on Reddit and other social media, first-party surveys and more with no engineering help. In this example, I have already set up AI feedback for a mobile app and connected it to reviews from the Apple App Store, as well as Google Play. Agentic AI processes the massive volume of unstructured data and sorts it into categories like you see here.

AI回饋是一種大規模傾聽用戶意見並根據回饋採取行動的新方式。AI回饋收集來自我們所有客戶回饋管道的資訊。無需任何工程協助，即可將 Zendesk 工單、Gong 通話記錄、App Store 評論、Reddit 和其他社交媒體上的評論、第一方調查等連結起來。在這個例子中，我已經為一款行動應用程式設定了 AI 回饋，並將其與 Apple App Store 和 Google Play 的評論連接起來。智能體人工智慧處理大量非結構化數據，並將其分類，就像你在這裡看到的那樣。

Our proprietary AI analysis gives product teams the right level of detail. Users can see feature requests to help build a road map or can filter by topics like complaints to know which issues to address. Here, there are 26 mentions of reliable read, start and alert query. I can click in to see specific comments for more detailed information and subtopics. For example, there are four mentions and notifications not syncing across devices.

我們獨有的AI分析能夠為產品團隊提供恰到好處的細節資訊。使用者可以查看功能請求，以協助制定產品路線圖，或按投訴等主題進行篩選，以了解需要解決哪些問題。這裡提到了 26 次可靠的讀取、啟動和警報查詢。我可以點擊查看特定評論，以獲取更詳細的資訊和子主題。例如，有四條提及和通知未在不同設備間同步。

With Amplitude, customers can then turn that feedback into action. We can create a cohort of these 96 users watching session replays of how they interact with notifications or surveying them for more on what they need.

借助 Amplitude，客戶可以將這些回饋轉化為行動。我們可以建立一個包含這 96 位使用者的群體，觀看他們與通知互動方式的會話回放，或對他們進行調查，以了解他們的需求。

Our innovation will accelerate from here. In addition to what I've just shown, over the next few quarters, we'll introduce new AI-first products like automated insights, global chat assistant and additional agents that extend our reach. These new capabilities expand who can use Amplitude and strengthen the value of the analytics platform overall. Every new product draws on the same behavioral data set and feeds back into it, creating a single system of improvement. That's what makes our use and learn opportunity so large.

我們的創新將從此加速發展。除了我剛剛展示的內容之外，在接下來的幾個季度裡，我們將推出新的 AI 優先產品，例如自動化洞察、全球聊天助理和更多代理，以擴大我們的覆蓋範圍。這些新功能擴大了 Amplitude 的使用者群體，並增強了分析平台的整體價值。每款新產品都利用相同的行為資料集，並將資料回饋到該資料集中，從而創建一個統一的改進系統。正因如此，我們的使用和學習機會才如此巨大。

Innovation is the biggest driver of long-term growth at Amplitude and our strongest moat in this AI-first world.

創新是 Amplitude 長期成長的最大驅動力，也是我們在人工智慧優先的世界中擁有的最強護城河。

Let's talk about customers. We had a great quarter for new and expansion deals with enterprise customers, including Bentley Systems, FanDuel, Thomson Reuters, Taco Bell, Global Radio, Empower, Granola, Algolia and Gusto, among others. I'm going to highlight how a few of them are putting this all to work. Three examples stand out this quarter, each showing the power of the Amplitude platform in a different way.

我們來談談客戶。本季我們在與企業客戶的新交易和擴展交易方面取得了巨大成功，其中包括 Bentley Systems、FanDuel、Thomson Reuters、Taco Bell、Global Radio、Empower、Granola、Algolia 和 Gusto 等。我將重點介紹他們中的一些人是如何將這一切付諸實踐的。本季有三個例子特別突出，每個例子都以不同的方式展現了 Amplitude 平台的強大功能。

First is FanDuel. They continue to be a great example of platform consolidation at scale. FanDuel is constantly refining its experiencing -- its experiences and tailoring them for millions of fans. Connecting real-time feedback to customer experience is critical to their success, and Amplitude powers that loop. FanDuel uses Amplitude end-to-end across multiple product lines from analytics to guides and surveys to session replay.

首先是 FanDuel。它們仍然是平台大規模整合的絕佳範例。FanDuel 不斷改進其用戶體驗——為數百萬粉絲量身定制用戶體驗。將即時回饋與客戶體驗聯繫起來對他們的成功至關重要，而 Amplitude 正是實現這一循環的動力。FanDuel 在多個產品線中全面使用 Amplitude，從分析到指南和調查再到會話回放。

That unified view helps their teams test, learn and improve faster. Their expansion and renewal patterns remain among the strongest in our base.

這種統一的視角有助於他們的團隊更快地進行測試、學習和改進。它們的擴張和更新模式仍然是我們基地中最強勁的模式之一。

Second, Granola. This fast-growing AI start-up adopted Amplitude before launch after hearing about us through the AI ecosystem. Today, more than half the company uses Amplitude every day to understand how people use their product and where to iterate next. Granola ships new features quickly and relies on real-time feedback to guide product decisions. Their story is a great example of how AI-native companies are choosing Amplitude to accelerate growth and scale with confidence.

其次，格蘭諾拉麥片。這家快速發展的 AI 新創公司在透過 AI 生態系統了解到我們之後，在產品發布前就採用了 Amplitude。如今，該公司超過一半的員工每天都使用 Amplitude 來了解人們如何使用他們的產品以及下一步應該如何迭代。Granola 快速推出新功能，並依靠即時回饋來指導產品決策。他們的故事很好地詮釋了人工智慧原生公司如何選擇 Amplitude 來加速成長並充滿信心地擴大規模。

Third is Bentley Systems, a global leader in design, construction and infrastructure software. Bentley selected Amplitude as a single analytics platform across all products. The company previously relied on siloed legacy tools but needed one system to understand usage, drive adoption and guide feature development. By activating historical data from Databricks and combining it with behavioral insights in Amplitude, Bentley can now test, learn and implement improvements far more quickly across its portfolio.

第三名是 Bentley Systems，一家全球領先的設計、施工和基礎設施軟體公司。賓利選擇 Amplitude 作為其所有產品的單一分析平台。該公司之前依賴各自獨立的傳統工具，但需要一個系統來了解使用情況、推動採用並指導功能開發。透過啟動 Databricks 的歷史數據並將其與 Amplitude 中的行為洞察相結合，Bentley 現在可以更快地在其產品組合中測試、學習和實施改進。

These stories all point to a common theme. From AI start-ups to global enterprises, customers are betting on Amplitude as the AI analytics platform that will help them thrive in this new era.

這些故事都指向一個共同的主題。從人工智慧新創公司到全球企業，客戶都寄望於 Amplitude，將其視為能夠幫助他們在新時代蓬勃發展的 AI 分析平台。

We are at the beginning of redefining analytics as an AI-native system that learns, reasons and acts. Over the next few quarters, we will bring a new wave of AI-native products to market that will reshape how companies use data to build better products. This is just the beginning of the AI era for analytics.

我們正處於重新定義分析的開端，將其打造為一個能夠學習、推理和行動的人工智慧原生系統。在接下來的幾個季度裡，我們將推出新一波人工智慧原生產品，這將重塑公司利用數據打造更好產品的方式。這只是人工智慧在數據分析領域應用的開端。

I'll now hand it over to Andrew to walk through the financials.

現在我將把財務部分交給安德魯來講解。

Thank you, Spenser, and good afternoon, everyone. We've delivered another solid quarter of acceleration in our ARR, improved operational efficiency and created greater durability in our future revenue base. Our customers are increasing their pace of innovation and in turn, need to understand how the changes are being received, how to adapt and how to implement those changes. As such, we believe Amplitude's importance to the enterprise is increasing.

謝謝你，史賓塞，大家下午好。我們的年度經常性收入 (ARR) 又實現了穩健成長，營運效率得到提升，未來收入基礎也更加穩固。我們的客戶正在加快創新步伐，因此，他們需要了解這些變化是如何被接受的，如何適應以及如何實施這些變化。因此，我們認為 Amplitude 對企業的重要性正在不斷提升。

On our business, we have continued to perform against our strategy that we communicated at our Investor Day earlier this year. We've increased the value that our platform can deliver by adding Guides and Surveys, AI agents, our MCP server and others. We've grown the base of our enterprises we are serving, the number of customers that are using multiple products and the full platform. We've done all this while improving operational efficiency of the business.

在我們的業務方面，我們一直按照今年稍早在投資者日上公佈的策略進行營運。我們透過添加指南和調查、人工智慧代理、我們的 MCP 伺服器等功能，提高了我們平台所能提供的價值。我們擴大了服務企業的客戶基礎，增加了使用多種產品和完整平台的客戶數量。我們在提高公司營運效率的同時，也完成了所有這些工作。

We continue to improve the durability of our business as measured by improving our contract duration and remaining performance obligations, or RPO. This quarter, our average contract duration grew to nearly 22 months, up from 19 months just one year ago. Our RPO growth has improved from Q2 with current RPO growth year over year accelerating to 22% from 20% last quarter and long-term RPO growth accelerating to 78% year over year, up from 64% last quarter. This results in total RPO growth of 37%, accelerating from 31% last quarter. The growth in our RPO is a direct result from building a more repeatable and scalable go-to-market strategy, focused on enterprise customers.

我們不斷提高業務的持久性，透過改善合約期限和剩餘履約義務（RPO）來衡量。本季度，我們的平均合約期限成長至近 22 個月，而一年前僅為 19 個月。我們的 RPO 成長較第二季有所改善，目前 RPO 年成長率從上季的 20% 加速至 22%，長期 RPO 年成長率從上季的 64% 加速至 78%。這使得 RPO 總成長率達到 37%，高於上一季的 31%。我們 RPO 的成長直接源於建立了一個更具可重複性和可擴展性的市場進入策略，該策略專注於企業客戶。

Turning to our third-quarter results. As a reminder, all financial results that I'll be discussing with the exception of revenue are non-GAAP. Our GAAP financial results, along with a reconciliation between GAAP and non-GAAP results, can be found in our earnings press release and supplemental financials on the Investor Relations page on our website.

接下來來看看我們第三季的業績。再次提醒大家，除收入外，我將要討論的所有財務表現均為非GAAP財務業績。我們的 GAAP 財務表現以及 GAAP 和非 GAAP 業績的調節表，可以在我們網站的投資者關係頁面上的獲利新聞稿和補充財務報表中找到。

Third-quarter revenue was $88.6 million, up 18% year over year and 6% quarter over quarter. This quarter's growth benefited from better linearity in deal signings earlier in the quarter, growth in our services business and the strong net new ARR growth we had in Q2. Total ARR increased to $347 million exiting the third quarter, an increase of 16% year over year and $12 million sequentially.

第三季營收為 8,860 萬美元，年增 18%，季增 6%。本季的成長得益於本季初交易簽約的良好線性度、服務業務的成長以及第二季強勁的新增淨年度經常性收入成長。第三季末，年度經常性收入總額增至 3.47 億美元，年增 16%，季增 1,200 萬美元。

Here are more details on the key elements of the quarter. We had a strong quarter for both new and expansion deals in the enterprise. Platform sales were also particularly strong. 39% of our customers now have multiple products with 71% of our ARR coming from that cohort. The number of customers representing $100,000 or more of ARR in Q3 grew to 653, an increase of 15% year over year and up 19 customers since last quarter.

以下是本季關鍵要素的更多詳情。本季企業的新交易和擴張交易都表現強勁。平台銷售也表現特別強勁。目前，39% 的客戶擁有多種產品，而我們 71% 的年度經常性收入 (ARR) 都來自這部分客戶。第三季度，年經常性收入 (ARR) 達到 10 萬美元或以上的客戶數量增至 653 人，年增 15%，比上一季增加了 19 人。

In-period NRR progressed to 104%, led by cross-sell expansions. Gross margin was 76% for the third quarter, down 1 point from the third quarter of 2024 but up 1 point since last quarter. We continue to make progress on optimizing our hosting costs, driving multiproduct contracts and monetizing services engagements. And we will continue to look for opportunities to incrementally improve our gross margin over time.

期中淨收入率 (NRR) 提升至 104%，主要得益於交叉銷售的擴張。第三季毛利率為 76%，比 2024 年第三季下降 1 個百分點，但比上一季上升 1 個百分點。我們在優化託管成本、推動多產品合約和服務合作貨幣化方面持續取得進展。我們將繼續尋找機會，逐步提高毛利率。

Sales and marketing expenses were 43% of revenue, a decrease of 1 point from the second quarter. We continue to focus on improving sales efficiencies, driving improvement through our changes in process, coverage and expansion of enterprise customers. At the same time, we are investing for future growth, while balancing this incremental investment with efficiency gains. G&A was 13% of revenue, down 3 points from the third quarter of 2024. We expect G&A to improve as a percentage of revenue over time.

銷售和行銷費用佔收入的 43%，比第二季下降了 1 個百分點。我們將繼續專注於提高銷售效率，透過流程改善、擴大覆蓋範圍和拓展企業客戶來推動績效提升。同時，我們正在為未來的成長進行投資，同時努力平衡這種增量投資與效率提升之間的關係。一般及行政費用佔收入的 13%，比 2024 年第三季下降了 3 個百分點。我們預期管理費用佔收入的比例會隨著時間的推移而改善。

R&D was 19% of revenue, up 3 points from the third quarter of 2024. We expect to continue to invest in the talent and the capabilities of our team to drive greater innovation in the future. Total operating expenses were $67 million or 75% of revenue, down 1 point sequentially.

研發支出佔營收的 19%，比 2024 年第三季成長了 3 個百分點。我們將繼續投資團隊的人才和能力，以推動未來更大的創新。總營運支出為 6,700 萬美元，佔營收的 75%，較上季下降 1 個百分點。

Operating income was $0.6 million or 0.6% of revenue. Net income per share was $0.02 based on 143.2 million diluted shares compared to net income per share of $0.03 with 131.3 million diluted shares a year ago.

營業收入為 60 萬美元，佔總收入的 0.6%。根據 1.432 億股稀釋股份計算，每股淨收益為 0.02 美元，而去年同期，根據 1.313 億股稀釋股份計算，每股淨收益為 0.03 美元。

Free cash flow in the quarter was $3.4 million or 4% of revenue compared to $4.5 million or 6% of revenue during the same period last year. In the third quarter, we managed our cash collections and made meaningful progress, shifting to contracts with annual payments in advance.

本季自由現金流為 340 萬美元，佔營收的 4%，去年同期為 450 萬美元，佔營收的 6%。第三季度，我們管理了現金回收工作，並取得了實質進展，轉向簽訂預付年款的合約。

Now, turning to our outlook. As Spenser laid out, the world of development, test and ship is changing rapidly. Analytics and the use of data to understand outcomes and drive action will be more important than ever for enterprises. Our strategy remains consistent with our go-to-market. We will continue to focus on gaining new enterprise customers and driving cross-platform sales with our existing customer base.

現在，讓我們來看看我們的展望。正如斯賓塞所闡述的那樣，研發、測試和交付領域正在迅速變化。對於企業而言，分析以及利用數據來了解結果和推動行動將比以往任何時候都更重要。我們的策略與我們的市場推廣策略保持一致。我們將繼續專注於獲取新的企業客戶，並利用現有客戶群推動跨平台銷售。

We also believe that with the release of our AI capabilities, the monetization of data ingested into our platform and cross-sell opportunities of new products gives us the right strategy to align the value of our customers receive with our growth opportunities and to grow our business in a profitable way.

我們也相信，隨著人工智慧能力的發布，將我們平台吸收的數據貨幣化，以及新產品的交叉銷售機會，為我們提供了正確的策略，使客戶獲得的價值與我們的成長機會保持一致，並以盈利的方式發展我們的業務。

For the fourth quarter of 2025, we expect revenue to be between $89 million and $91 million, representing an annual growth rate of 15% at the midpoint. We expect non-GAAP operating income to be between $3.5 million and $5.5 million. And we expect non-GAAP net income per share to be between $0.04 and $0.05, assuming diluted weighted average shares outstanding of approximately 142.6 million.

我們預計 2025 年第四季的營收將在 8,900 萬美元至 9,100 萬美元之間，中位數年增長率為 15%。我們預計非GAAP營業收入將在350萬美元至550萬美元之間。我們預計，假設稀釋後的加權平均流通股約為 1.426 億股，則非 GAAP 每股淨收益將在 0.04 美元至 0.05 美元之間。

For the full-year 2025, we are raising our revenue expectation for the full year due to the quarter's positive performance. We expect full-year revenue to be between $340.8 million and $342.8 million, an annual growth rate of 14% at the midpoint. We are adjusting our range for the full-year non-GAAP operating income to be between $0.5 million and $2.5 million, reflecting growth investments. We expect non-GAAP net income per share to be between $0.06 and $0.08, assuming weighted average shares outstanding of approximately 142 million as measured on a fully diluted basis.

由於本季業績表現良好，我們上調了 2025 年全年營收預期。我們預計全年營收將在 3.408 億美元至 3.428 億美元之間，年增長率中位數為 14%。我們將全年非GAAP營業收入範圍調整為50萬美元至250萬美元，以反映成長投資。我們預計，以完全稀釋基準計算的加權平均流通股約為 1.42 億股，非 GAAP 每股淨收益將在 0.06 美元至 0.08 美元之間。

In closing, we continue to execute our strategy of growing our enterprise customer base, expanding multiproduct attach with our customers and growing with additional leverage in our business model. This has only occurred through the focused execution of our employees and our relentless drive towards creating value for our customers.

最後，我們將繼續執行我們的策略，即擴大我們的企業客戶群，擴大與客戶的多產品捆綁銷售，並在我們的商業模式中獲得更多槓桿作用，從而實現成長。這完全得益於我們員工的專注執行和我們為客戶創造價值的不懈努力。

With that, we'll open it up for Q&A. Over to you, John.

接下來，我們將進入問答環節。接下來該你了，約翰。

Thank you, Andrew. We will now turn to Q&A.

謝謝你，安德魯。接下來進入問答環節。

(Operator Instructions)

（操作說明）

Koji Ikeda, Bank of America; followed by Patrick Schulz.

Koji Ikeda，美國銀行；緊隨其後的是 Patrick Schulz。

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

我想問一下關於RPO的問題。我看了 ARR，成長不錯，但 RPO 的成長速度非常快，達到了 37%，這是很長一段時間以來連續成長的大部分。Andrew，我完全理解你所說的執行過程中可重複性和可擴展性的企業級方面的問題。但我希望您能按企業、中型市場、垂直行業，甚至年度合約規模和合約期限進行更細緻的劃分。真正推動這37%成長的因素是什麼？

You may recall, Koji, that back in the beginning of the year, we made a lot of efforts at resegmenting our customers, refocusing our sales coverage on the enterprise group of clients. And we even have a stratification that's even larger than that, we call, [Strat] in the enterprise. And for those who don't remember, we define enterprise clients as anyone who has 1,000 employees or more or over $100 million in revenue.

浩二，你可能還記得，今年年初的時候，我們做了很多努力來重新劃分客戶群，並將銷售覆蓋範圍重新聚焦於企業客戶群。我們甚至還有比這更大的分層，我們稱之為企業中的 [Strat]。對於那些不記得的人來說，我們將企業客戶定義為擁有 1000 名或以上員工或年收入超過 1 億美元的任何公司。

And when we did that, we really had a lot of marketing efforts, focused efforts to show how we are consolidating the space, how we could increasingly -- by customers, increasingly leverage the power of the Amplitude platform, how they get greater value. And I would tell you, when you have those conversations with clients, they often look to not just a single tool replacement, but rather a multiyear journey, how they're going to continue to drive value as their business changes, as their business grows.

當我們這樣做的時候，我們確實投入了大量的行銷精力，專注於展示我們是如何整合這個領域的，我們如何讓客戶越來越多地利用 Amplitude 平台的力量，讓他們獲得更大的價值。我想告訴你，當你和客戶進行這些對話時，他們通常考慮的不僅僅是更換單一工具，而是一個多年的發展歷程，即隨著業務的變化和成長，他們將如何繼續創造價值。

And that's led to more strategic conversations and thus the deal constructs, which have more duration to them. I mentioned earlier, our contract duration has increased overall to 22 months. I will tell you, in the enterprise space, it's even larger. And the reason is because so many of those multiyear -- million-dollar contracts result in multiyear commitments, and that's driving our RPO.

這促成了更多策略性對話，從而形成了持續時間更長的交易結構。我之前提到過，我們的合約期限總體上已增加到 22 個月。我可以告訴你，在企業領域，這個數字甚至更大。原因在於，許多多年期——數百萬美元的合約都會導致多年的承諾，而這正是我們RPO（招募點目標）的驅動因素。

Now, you don't do that without getting the sales teams very focused in an execution way and aligning incentives [proportionately] to drive those outcomes. And I would tell you, they've done a great job in multiyear contracts and making sure that our RPO is growing quite rapidly.

要做到這一點，就必須讓銷售團隊在執行上非常專注，並（按比例）調整激勵措施來推動這些結果。我可以告訴你，他們在多年合約方面做得非常出色，並確保我們的招募流程外包 (RPO) 業務快速成長。

And maybe a question here for Spenser. In the presentation, you talked about this, I'll call it, the build, ship, use and learn circle of life here. Where are enterprises today --

或許這裡有個問題想問斯賓塞。在演講中，你談到了這個，我稱之為「建構、交付、使用和學習的生命週期」。如今的企業在哪裡？--

Product circle of life.

產品生命週期。

Product circle of life. Yes. Where are enterprises today? Where are they investing now? And where are they really going to be investing in the future?

產品生命週期。是的。如今的企業在哪裡？他們現在投資的領域是什麼？那麼，他們未來究竟會在哪裡投資呢？

You mean, in product or in analytics?

你是說產品方面還是分析方面？

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

在那個圈子裡。他們是否在建造過程和運輸過程中投入了更多資金？他們是否還沒有真正開始投入使用和學習方面？而這才是你們真正的機會所在？

I think it's much earlier on the use and learn side, right? If you look at the state-of-the-art for how companies do this, it's literally you go ask, talk to a bunch of customers, you do a focus group, you send out a survey, you're getting lots of qualitative feedback.

我覺得現在還處於使用和學習的早期階段，對吧？如果你看看目前企業是如何做到這一點的，你會發現他們實際上是去詢問、與很多客戶交談、組織焦點小組、發放調查問卷，從而獲得大量的定性回饋。

The point I am trying to make is that if you can master that quantitatively, that is so much more powerful because you can -- actions are much more powerful than words. Users are great at describing the problem they have. But it's like that old great Henry Ford quote, if you just listen directly to what they do, they'd ask you for faster horses.

我想表達的觀點是，如果你能量化地掌握這一點，那將會更加強大，因為行動比言語更有力量。用戶非常擅長描述他們遇到的問題。但這就像亨利福特那句偉大的名言一樣，如果你直接聽他們是怎麼做的，他們就會要求你提供更快的馬。

And so the companies like the Facebooks or the Netflixes of the world that have done a great job of that has this incredible edge over anyone else. And so we see ourselves as bringing that infrastructure much broadly.

因此，像 Facebook 或 Netflix 這樣的公司，如果在這方面做得非常出色，就比其他任何公司都擁有巨大的優勢。因此，我們認為我們正在更廣泛地推廣這種基礎設施。

Now, to your question, it's much, much earlier there. I think we see a lot of excitement. Like I was just in Europe a few weeks ago, and every single customer wants to talk about, yes, how is my learning side going to get completely disrupted by AI. Like we're already on coding. They're having the developers use Cursor and Claude Code and a whole bunch of other coding -- AI coding tools.

現在回答你的問題，那邊的情況要早得多。我認為我們看到了很多興奮的情緒。就像我幾週前剛去過歐洲一樣，每個客戶都想談論人工智慧將如何徹底顛覆我的學習方式。就像我們已經在寫程式了一樣。他們讓開發人員使用 Cursor 和 Claude Code 以及一大堆其他的編碼——人工智慧編碼工具。

They want to know how the same is going to happen in analytics. And so what I was presenting is like, hey, what's our vision for that future?

他們想知道同樣的情況在數據分析領域將如何發生。所以我當時提出的問題是：嘿，我們對未來的願景是什麼？

Patrick Schulz, R.W. Baird; followed by Elizabeth Porter, Morgan Stanley.

Patrick Schulz，R.W. Baird；緊隨其後的是 Elizabeth Porter，摩根士丹利。

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

首先，我們不妨考慮一下營收和年度經常性收入的成長，又是一個非常強勁的季度。從第四季業績指引來看，其中暗示著營收成長速度將有所放緩。我想問一下，能否更詳細地介紹一下這份預測報告的製定過程？更廣泛地說，投資成長和追求利潤之間總是存在某種權衡。但我很想知道，在你們邁入明年之際，你們將如何平衡這兩者，特別是考慮到你們目前所看到的創新速度。

So I'd tell you that our guidance is always based upon the lens of execution for us. And as we've gotten better and better at executing our enterprise play, that's given us a lot more visibility into future revenue, and it shows up in our RPO. And so rather than go back on what has worked very well for us as we progressed this year, we're going to stick with that guidance pattern and stick with what we know we can go execute in the market, and we believe that will continue to deliver benefits for us.

所以我想說，我們的指導始終以執行的角度出發。隨著我們在執行企業策略方面越來越得心應手，我們對未來的收入有了更清晰的了解，這體現在我們的 RPO 上。因此，我們不會放棄今年以來行之有效的策略，而是會堅持這種指導模式，堅持我們認為可以在市場上執行的策略，我們相信這將繼續為我們帶來收益。

Now, on balancing growth with leverage, if you were a fly on the wall within the Amplitude offices, you'd find that we're often making debates -- we have debates about when to make the right investment, how much leverage can we expect from it, and then how can we make sure that we are continuing to drive towards the expectations we set at Investor Day back in March. And so it's always a little bit of a difficult conversation.

現在，關於如何在成長和槓桿之間取得平衡，如果你是 Amplitude 辦公室裡的一隻蒼蠅，你會發現我們經常進行辯論——我們辯論何時進行正確的投資，我們可以從中獲得多少槓桿，然後我們如何確保我們繼續朝著我們在 3 月份投資者日上設定的預期目標前進。所以這始終是一場有點棘手的對話。

But I think the teams have learned to manage within those constructs, and we're making the investments that really matter while still delivering progressions on our growth with leverage plan.

但我認為團隊已經學會了在這些框架內進行管理，我們正在進行真正重要的投資，同時透過槓桿計畫來推進我們的成長。

Yeah. Patrick, I'll say you don't find -- the bottleneck to growth is actually not a lot of time spend. It's about how can I retrain this team to be more effective. So Andrew and I and with Thomas have been looking at sales productivity and how do we drive that for next year. The teams have really stepped up and done a good job of how do we be really effective.

是的。派崔克，我想說你不會發現——成長的瓶頸其實並不是投入太多時間。關鍵在於如何重新培訓這個團隊，使其更有效率。所以，我和安德魯還有湯瑪斯一直在研究銷售效率，以及我們明年如何提高銷售效率。各個團隊都表現出色，在如何提高效率方面做得很好。

You can get a lot of leverage from AI tooling in this world without a crazy amount of spend.

在這個世界上，你無需投入巨額資金就能從人工智慧工具中獲得巨大的優勢。

Okay. That's very helpful. Maybe just one quick follow-up, too. Very impressive list of customer wins during the quarter. And one of your goals over the past year has been to improve the enterprise go-to-market motion.

好的。那很有幫助。或許還需要一個簡短的後續問題。本季成功贏得眾多客戶，成績斐然。過去一年，你的目標之一就是改善企業市場推廣流程。

Just can you maybe talk about how some of these improvements have impacted the trends with initial deal wins? What are you seeing in terms of change to sales cycles, size of initial lands and maybe landing with multiple products?

您能否談談這些改進措施對初期交易成功趨勢的影響？您觀察到銷售週期、初始市場規模以及是否推出多種產品等方面有哪些變化？

Yeah. We're -- as I outlined in all three examples, I think we're doing everything across the board way better than we were a year or two ago. You're seeing many more multiyears, which is reflected in the RPO growth. You're seeing 71% on multiple products. That's a huge [fr****ng] deal.

是的。正如我在所有三個例子中所概述的那樣，我認為我們現在在各個方面都比一兩年前做得好得多。你會看到更多多年期合約，這反映在招募流程外包 (RPO) 的成長上。您在多個產品上都看到了 71% 的折扣。那可是件大事。

You're seeing customers willing to just invest in analytics, invest in the whole platform. They're very excited about what we're doing on the AI side as well. And so I got to give a lot of credit to the go-to-market teams for how they've built much stronger relationships with those. Even though I didn't speak to it too much, they've done a phenomenal job, and that's why you see ARR reacceleration, as well as all those other numbers.

你會看到客戶願意投資分析，投資整個平台。他們對我們在人工智慧領域所做的工作也感到非常興奮。因此，我要高度讚揚市場推廣團隊，感謝他們與這些客戶建立了更牢固的關係。雖然我沒有過多談論此事，但他們做得非常出色，這就是為什麼你會看到 ARR 再次加速成長，以及所有其他數據。

One other just data point to call out, we had a really broad-based set of seven-figure wins. It was about -- it was five seven-figure wins in Q3, which was just fantastic to see, everything from some of the enterprises, the very traditional enterprises I called out, all the way to -- we actually had a foundational model company that we can't disclose who it is but sign for Amplitude. So it's just exciting to see , hey, across the full spectrum, we're doing well.

另一個值得一提的數據點是，我們獲得了一系列數額龐大的七位數獎金。第三季我們贏得了五筆七位數的交易，這真是太棒了，從我提到的那些非常傳統的企業，到——我們實際上與一家基礎模型公司簽約，我們不能透露它是誰，但它與 Amplitude 簽約了。所以令人振奮的是，我們看到，在各方面，我們都做得很好。

Elizabeth Porter, Morgan Stanley; followed by Willow Miller, William Blair.

伊莉莎白·波特，摩根士丹利；緊隨其後的是威洛·米勒，威廉·布萊爾。

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

驚人的。我認為 Agents 最令人興奮的地方之一在於它能夠將 Amplitude 平台上的多個產品連接起來。我們是否應該預期多產品採用率會出現階躍式成長？我知道它佔 ARR 的 70% 左右，但客戶群仍然低於 70%，也就是 -40%，這是一個很大的機會。那麼，代理策略如何從整體上加速更廣泛的平台策略中的這種組合轉變呢？

Okay. So there's what we're doing today and then there's future. What we're doing today, we are focused on the analytics adoption piece because more people using analytics, the more people sending us data, the more people querying that data, the more value we create, and that will naturally expand and lead to a whole bunch of these other use cases.

好的。所以，這是我們今天正在做的事情，然後還有未來。我們今天所做的事情，重點是分析技術的採用，因為使用分析技術的人越多，向我們發送資料的人越多，查詢這些資料的人越多，我們創造的價值就越大，這自然會擴展並帶來許多其他用例。

So the two agents I talked about, the dashboard monitoring agent as well as the session replay agent, those are all insights-level agents. Now, what we do have coming and will be in next year is we're going to be doing a lot more on the action side, so suggested experiments, as we showed in June on the last earnings call, where we come up with a strategy for how you can improve conversion on your website, suggested guides for you to send out to users, hey, you don't have a new user onboarding guide.

所以我提到的兩個代理，儀表板監控代理和會話重播代理，都是洞察級別的代理。現在，我們接下來將在明年推出更多行動方案，例如建議實驗，就像我們在 6 月的上次財報電話會議上展示的那樣，我們會提出一些策略，幫助您提高網站的轉換率，並提供一些建議指南供您發送給用戶，例如，如果您還沒有新用戶入門指南。

We've created one for you. Do you want to go ahead and deploy that? Suggested cohorts of users to target with messaging. So I'd say today, on the Agents front, we're specifically focusing on the analytics and insight layer because that's where we're hearing the most pull from customers, but we'll add a whole bunch of action layer stuff as a fast follow-up.

我們為您創建了一個。你想繼續部署嗎？建議向特定用戶群體發送訊息。所以我想說，今天在代理商方面，我們特別關注分析和洞察層，因為我們從客戶那裡聽到的需求最多，但我們很快就會跟進添加大量操作層的內容。

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

偉大的。然後，作為後續補充，再談談財務方面的問題。隨著 Amplitude 進一步向高端市場拓展，考慮到某些季度企業交易量較大，我們是否應該預期季度內淨收入會出現季節性波動？那麼，您會如何描述 NRR 趨勢的節奏以及它在一年中的演變？

So I'd say that everything is better with -- in the enterprise. Our NRR is much higher than the overall average for the business. We still have cohorts in the SMB and mid-market that have higher churn rates. But as we get more -- a higher and higher percentage of our ARR in the enterprise, NRR will continue to progress. And we expect that we'll see a continued progression in our enterprise content.

所以我覺得，在企業裡，一切都變得更好了。我們的淨收入率遠高於行業平均。我們仍然有一些中小企業和中端市場的客戶群流失率較高。但隨著我們在企業中獲得的 ARR 比例越來越高，NRR 也將持續成長。我們預計企業內容將持續發展。

As we delineated at our Investor Day back in March, we'll see that progression continue to go up. That drives better gross retention as well. And so although we didn't see a big progression this quarter, the reality is, we have a lot of faith in our long-term expectations of being that 115% that I talked about last quarter.

正如我們在三月的投資者日上所闡述的那樣，我們將看到這一進展繼續上升。這也有助於提高毛留存率。因此，儘管本季度我們沒有看到很大的進展，但實際上，我們對實現上個季度我所說的 115% 的長期預期充滿信心。

Willow Miller, William Blair; followed by Ian Black, Needham.

Willow Miller，William Blair；其次是 Ian Black，Needham。

I'm Willow, on for Arjun Bhatia.

我是Willow，替Arjun Bhatia報道。

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

我相信，您在事先準備好的演講稿中提到，您認為像 MCP 和 Agents 這樣的新 AI 功能可以讓非技術用戶也能使用 Amplitude。您能否就此發表更多評論？這能否擴大您的市場機會？

Absolutely. The hard part -- there's two hard parts in analytics today. One is, you have to learn an analytics product. And so as easy as we made it with Amplitude, you still have to learn our interface, what drop-downs, what type of charts to use, all of that stuff. The other thing you have to learn, and this is the biggest bottleneck in analytics, is the data taxonomy that you have.

絕對地。難點在於──如今的數據分析有兩個難點。第一，你必須學習使用分析產品。所以，儘管我們讓 Amplitude 的操作變得簡單，但你仍然需要學習我們的介面、下拉式選單、圖表類型等等。你還需要學習另一件事，這也是分析中最大的瓶頸，那就是你擁有的資料分類法。

And the problem with particularly product data taxonomies is they are huge. Like the average product has thousands of different things you can do in it. So no one is going to be able to keep that in their head. The huge leverage point you get, which I showed in the MCP demo, is that you can start with a very vague question, like show me my onboarding funnel, and then it will look across your data set to see, okay, which are likely the onboarding events, let me construct a funnel with them. And then, if you're not happy with the result, you can iterate with it.

而產品資料分類法的問題在於，它們非常龐大。就像普通產品一樣，你可以用它來做成千上萬種不同的事情。所以沒人能把那件事記在腦子裡。我在 MCP 演示中展示了它帶來的巨大優勢，那就是你可以從一個非常模糊的問題開始，例如“顯示我的用戶引導流程”，然後它會查看你的資料集，看看哪些可能是用戶引導事件，然後用它們建立一個流程。然後，如果你對結果不滿意，你可以進行迭代改進。

But the point is, you're not having to learn our interface or any analytics interface. You're also not really having to learn your data taxonomy. It's leveraging -- it's doing the thinking and reasoning for you on specifying the query and constructing it and putting that back in a chart. So you're just getting the result and then going back and forth with it. So I -- so the answer is, highly yes.

但重點是，您無需學習我們的介面或任何分析介面。你也不需要真正學習資料分類法。它利用了槓桿作用——它會為你思考和推理，指定查詢並建立查詢，然後將其放回圖表中。所以你只是得到了結果，然後反覆修改。所以——所以答案是，非常肯定。

We've set really aggressive internal targets for next year for what we expect the -- how we expect the adoption of Amplitude to grow because of what we're building.

我們已經為明年設定了非常激進的內部目標，即我們預期 Amplitude 的採用率會如何成長，這要歸功於我們正在建立的產品。

Ian Black, Needham; followed by Claire Gerdes, UBS.

Ian Black，Needham；其次是 Claire Gerdes，瑞銀集團。

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

恭喜你們本季業績出色。你們去年開始逐步過渡到多年期合同，這對銷售效率有影響嗎？

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

不，我不這麼認為──我們當然會從毛利和淨利兩方面來檢視銷售效率。但我認為，我們繼續在現有客戶群中推動業務擴張的機會遠不止 1.5 億美元。我們在投資者日那天也說過類似的話，當時我們的客戶甚至更少。我們在拓展新創企業客戶方面做得相當不錯。即使以我們目前的成長速度，我們仍然認為每個領域都有很大的發展空間，可以展現出巨大的擴張機會。

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

驚人的。然後，您提到客戶越來越將您視為重要的策略合作夥伴。隨著您客戶群的不斷深入，是否有機會拓展您的服務合作夥伴網路？

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

是的。這是我們目前尚處於萌芽階段的另一個成長引擎。我認為，隨著 Amplitude 對企業客戶的重要性日益增加，你會看到越來越多的合作夥伴開始考慮如何利用我們的平台進行開發，並創造他們自己的增值服務。我們相信，隨著時間的推移，這種情況將會發生。

Claire Gerdes, UBS; followed by Jackson Ader, KeyBanc.

瑞銀集團的克萊爾·格德斯；緊隨其後的是凱基銀行的傑克遜·阿德。

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

我是克萊爾，代泰勒‧麥金尼斯為您報道。今天看到結果真是太好了。我想諮詢一下貴公司目前推出的一些新型人工智慧產品。我知道有些產品還在測試階段。但當我們思考您目前在這些方面的情況，以及未來如何在推廣和盈利之間取得平衡時，我知道，現在還處於非常早期的階段，但您是否更希望客戶能夠接受並熟悉這些功能，而我們目前可以期待更多免費功能？或者，你現在是怎麼想的？

Yeah. Adoption is our key focus. Like they drive a bunch of value. Customers will track more data. They'll use that data a lot more broadly across more users, and that will very naturally lead to more value and upsells and everything else.

是的。領養是我們工作的重點。它們創造了很多價值。客戶將追蹤更多數據。他們將更廣泛地利用這些數據，覆蓋更多用戶，這自然會帶來更多價值、追加銷售以及其他一切。

If you look at our ASP, we're hovering around $400,000 a year. In a lot of companies, we are the largest spend after their cloud hosting. So we have no problems already commanding a premium price point. The key is to be able to consistently deliver value and make that barrier lower and lower, which is what we're doing with MCP and Agents and all of the stuff that's targeted at nontechnical users.

從我們的平均售價來看，我們每年的收入徘徊在 40 萬美元左右。在許多公司裡，我們的支出僅次於雲端託管。因此，我們完全有能力收取高價。關鍵在於能夠持續地提供價值，並不斷降低門檻，這就是我們透過 MCP、代理商以及所有面向非技術用戶的產品所做的事情。

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

然後，或許可以再快速問一個更廣泛的問題，您能否談談目前的銷售環境？顯然，現在還有很多事情要處理，但你的加速表現非常出色。如果您能就此發表一下意見，那就太好了。

Yeah. I think there's been -- I don't think there's any change quarter to quarter. There's a continued cost consciousness among all customers, the same way it's been for the last few years. I think what they're really excited to see is like, hey, does this AI stuff work? Is it legit?

是的。我認為——我認為季度之間沒有任何變化。與過去幾年一樣，所有顧客仍然保持著成本意識。我認為他們真正興奮的是，嘿，人工智慧到底有沒有用？這是真的嗎？

Every B2B company under the sun is like pitching them on AI this, that or the other thing. And so what I always say is show me the demo. So that's why I did that on today's call. And they're really, really -- yes, a lot of customers are very, very excited about that. They want to know how can I get 5, 10, even more times leverage with leveraging AI Agents, MCP, get a lot more insights than I would doing all of that work manually.

幾乎所有B2B公司都在向他們推銷人工智慧這、那或其他什麼東西。所以我總是說，給我看看演示。所以這就是我今天在電話會議上這麼做的原因。是的，很多顧客對此都非常非常興奮。他們想知道如何利用 AI 代理、MCP 等工具，將效率提高 5 倍、10 倍甚至更多，從而獲得比手動完成所有這些工作更多的見解。

Jackson Ader, KeyBanc; followed by [Yichuan Wang], Citi.

傑克森·阿德爾，KeyBanc；緊隨其後的是[王一川]，花旗銀行。

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

第一個問題是關於產品的問題。如果要稱之為一項重大舉措的話，弗朗索瓦的主要舉措之一是將客戶反饋與產品路線圖更緊密地結合起來，並啟動這一良性循環。所以我很好奇，客戶——代理商是如何推出的。您擁有人工智慧的特性和功能。展望 2026 年，客戶希望獲得什麼，才能繼續保持我們已經看到的成長動能？

Yeah. Look, just to be really clear, we're in the really early days of Amplitude in this category. I think -- let's see what would I call out. So first, take all the AI stuff and set it to the side. Just with the enterprise execution, plus the expanding breadth of the platform, that already, we expect to continue to accelerate us to the ranges that we talked about on the Investor Day earlier this year so beyond the 20%, which, in my mind, is the bare minimum for this category.

是的。說實話，Amplitude 在這個領域還處於非常早期的階段。我想——讓我想想我會喊些什麼。首先，把所有人工智慧相關的內容放到一邊。僅憑企業執行力，加上平台不斷擴大的覆蓋範圍，我們預計就能繼續加速實現我們在今年早些時候投資者日上談到的目標，即超過 20%，在我看來，20% 是該類別的最低要求。

And then, you add how this category gets dramatically reshaped by AI, as I've been outlining, like the same thing that happened to software engineering with Cursor and with a whole bunch of other AI coding products, that is going to happen in analytics, and we see what that opportunity is. We're going to go really aggressive after it, and there is a lot of appetite to adopt that. So I'm very excited and bullish on it. And I think as we see customers adopt and use and get value on that, that will all translate downstream to Amplitude revenue growth.

然後，正如我一直概述的那樣，人工智慧將如何徹底改變這個類別，就像 Cursor 和許多其他人工智慧編碼產品為軟體工程帶來的變化一樣，這種情況也將發生在分析領域，我們看到了其中的機會。我們將採取非常積極的措施來推進這項工作，而且許多人也對此表示歡迎。所以我對此非常興奮，也很看好它。我認為，隨著客戶採用、使用並從中獲得價值，所有這些都將轉化為 Amplitude 的收入成長。

Okay. All right. Great. And then, the follow-up question is just on the split between -- or not split, but just product analytics versus marketing analytics. I know we're getting into new budget territories with the marketing piece.

好的。好的。偉大的。然後，後續問題是關於產品分析與市場分析之間的區別——或者說，不區分，而是只區分產品分析與市場分析。我知道我們在行銷方面要進入新的預算領域了。

At what point does that split become material enough to where [I'm sure] that the high growth rates coming from marketing analytics is able to contribute to like a material amount of your overall revenue? Or are we there already?

行銷分析帶來的高成長率要達到什麼程度，才能對整體收入做出實質貢獻？或者我們已經到達目的地了？

No, no. It's early on it. There's customers that have switched off of legacy marketing analytics products and moved wholesale to Amplitude. Like DECATHLON is one. [Realtor] is another.

不，不。現在還處於早期階段。一些客戶已經放棄了傳統的行銷分析產品，全面轉向 Amplitude。比如迪卡儂就是其中之一。 [房地產經紀人]也是另一個。

There's a few that have that -- that do that, that are like saying, Hey, Google Analytics or Adobe is not working well enough. So let me move on to something like an Amplitude. Now, there's still more for us to build there, and we're going to be -- we haven't really talked about what we're going to be doing there, but there's -- yes, we're going to be doing a lot in 2026 that will allow us to capture a significant amount of the marketing budget and have that contribute to growth.

有些軟體確實有這種功能——它們會說：“嘿，Google Analytics 或 Adob​​e 的功能還不夠完善。”接下來，我來談談振幅之類的概念。現在，我們還有更多東西需要在那裡建設，我們將——我們還沒有真正談論過我們將在那裡做什麼，但是——是的，我們將在 2026 年做很多事情，這將使我們能夠獲得相當一部分營銷預算，並使其為增長做出貢獻。

Yichuan Wang, Citi; followed by Clark Wright, D.A. Davidson.

王一川，花旗集團；緊隨其後的是克拉克·賴特，D.A.戴維森律師事務所。

Spenser, the AI Agents launch over the summer was like pretty big [fun for OSF]. So today, with better availability, could you give us an update how has customer adoption been? What are some of the most effective use cases you are seeing and the ROI from customers? And then, also if there's any update on pricing monetization effort for AI Agents as it goes better?

史賓塞，今年夏天人工智慧代理的發布規模相當大。[OSF 的樂趣]。如今，隨著產品供應的改善，您能否向我們介紹客戶採納？您目前看到的最有效的用例有哪些？客戶的投資報酬率是多少？另外，如果人工智慧代理的定價獲利模式進展順利，是否有任何更新資訊？

Yeah. So let me hit the pricing one first. So as I said to Claire earlier, focus is just let's make Amplitude more valuable. Like we command already an extraordinarily high price point with a lot of our customers. And so we're not looking to squeeze them for more.

是的。那麼，我先來說說價格問題。正如我之前對克萊爾所說，重點就是讓 Amplitude 更有價值。就像我們很多客戶已經習慣了非常高的價格。因此，我們並不打算向他們榨取更多利益。

We just want to give them a lot of value. So I think it's a common misconception -- sorry, misunderstanding about our business relative to other SaaS is, we already command like very, very high price points, which is great, but you obviously want to make sure you're consistent about delivering the value.

我們只是想給他們創造很多價值。所以我覺得這是一個常見的誤解——抱歉，是對我們業務相對於其他 SaaS 的誤解——那就是，我們已經擁有非常非常高的價格，這很好，但你顯然要確保你在提供價值方面保持一致。

In terms of what use cases work very well, so the two I highlighted, dashboard monitoring and session replay are the big ones that customers use a lot of. They -- I think customers are not ready to trust AI agents to come up with a whole strategy of wholesale for them and then recommend a series of actions. But they are very excited about using things that can monitor the data and just proactively tell them -- like this is, in a lot of ways, the holy grail of analytics, like can you tell me when something has changed in my data and deliver that insight as to why it changed?

就哪些用例效果非常好而言，我重點介紹的兩個用例，即儀錶板監控和會話回放，是客戶經常使用的主要用例。我認為客戶還沒有準備好信任人工智慧代理，讓他們為他們制定一整套批發策略，然後推薦一系列行動。但他們非常興奮地使用能夠監控數據並主動告知他們的工具——這在許多方面都是分析的聖杯，例如，你能告訴我數據中何時發生了變化，並提供變化原因的見解嗎？

And so in the MCP demo, we have a -- I didn't do the demo today, but we have a dashboard monitoring agent that can do the exact same thing at that, deliver a root cause analysis saying, Hey, you had a spike in September and here are the particular causes the product benchmark report and this other launch that you did. And that customers are using and getting a bunch of value, and that's what our focus is in the short term.

因此，在 MCP 演示中，我們有一個——我今天沒有做演示，但我們有一個儀表板監控代理，它可以做同樣的事情，提供根本原因分析，例如，嘿，你在 9 月份出現了一個峰值，以下是產品基準報告和你進行的其他發布的具體原因。而客戶正在使用並從中獲得大量價值，這就是我們短期內的關注點。

And then, same with session replay. With session replay, you'll have often millions of sessions, and it's like you can't watch them all. So how can you have AI summarize the highlights for you? And then, you can maybe watch three or four that are relevant you're like, Oh, okay, I can see how the product experience can improve if we make these changes to the app.

會話回放也是如此。使用會話回放功能，通常會有數百萬個會話，你根本無法全部觀看。那麼，要如何讓人工智慧為你總結要點呢？然後，你可能會看三四個相關的視頻，然後你會想，哦，好的，我明白瞭如果我們對應用程序進行這些更改，產品體驗會如何改進。

Got it. That's clear. And Andrew, maybe one for you. I think the guide implies like a stronger momentum going into Q4. Can you help us understand the dynamic that you're seeing that have made you raise the guide bigger than [a bit] in the quarter and how much conservatism you see in the guide and how is the pipeline going to year end?

知道了。這一點很清楚。安德魯，也許這件也適合你。我認為這份指南暗示著第四季將迎來更強勁的成長勢頭。您能否幫助我們了解您觀察到的促使您在季度中將業績指引上調幅度超過[略微]的動態因素，以及您在業績指引中看到了多少保守因素，以及到年底的銷售計劃將如何？

Well, as we moved our business more towards pursuing enterprise opportunities, you still -- you have a pattern like many enterprise companies, and we're a calendar year company. So all of our reps have end-of-year incentives to achieve and exceed their targets. And so we typically have our strongest quarter in Q4. So that's the first thing. Pipelines and the maturity of those pipelines are something we look at very closely when we're putting together our guidance.

隨著我們業務更多地轉向追求企業機會，你們仍然——你們的模式與許多企業公司一樣，而我們是一家按日曆年運營的公司。因此，我們所有的銷售代表都有年終獎金，以激勵他們完成並超越目標。因此，我們通常在第四季度業績最好。這是第一點。在製定指導方針時，我們會非常密切地關注管道及其成熟度。

What we've seen so far, that gives us confidence. And it would be remiss of me if I didn't say the RPO gives us great visibility into future revenue periods. And the more that the sales team executes on driving greater relationships with clients, more strategic agreements, we're getting those multiyear agreements booked. And so, as I said earlier, the guidance is based on the lens of execution for us, and we've pursued that same philosophy throughout this year, and it's led to strong performances. So we're going to continue that.

目前為止我們所看到的，給了我們信心。如果我不說 RPO 讓我們對未來的營收週期有了更清晰的了解，那就太失職了。銷售團隊越是努力與客戶建立更緊密的聯繫，達成更多策略協議，我們就能獲得越多多年的合約。因此，正如我之前所說，我們的指導方針是基於執行情況的，我們今年一直秉持著同樣的理念，並取得了良好的業績。所以我們會繼續這樣做。

Congrats on the great result.

恭喜取得如此佳績！

Clark Wright, D.A. Davidson.

克拉克·賴特，D.A.戴維森。

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

史賓塞，你的產品團隊這季一直都很努力。

Every quarter. But yes, we're accelerating.

每季一次。是的，我們正在加速發展。

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

是的。創新步伐之快令人欣喜。我想請您談談，為了維持目前的創新速度，您現在是如何看待自主研發和購買漸進式能力之間的關係的。

Yeah. So you always want to be able to do both. Like I think experiment -- we actually looked for a while for the right team to come in but ended up deciding to be able to build was the faster way to get that to market because there wasn't a company at the time that was the right fit. Conversely, like we bought when we think it makes sense, so Activation back in 2022, Guides and Surveys, now AI Feedback, that made a ton of sense. So you're always doing both.

是的。所以你總是希望兩者兼顧。就像我認為的實驗——我們其實找了一段時間才找到合適的團隊，但最終決定自己動手是把產品推向市場的最快方法，因為當時還沒有合適的公司。反過來，就像我們只有在認為合適的時候才會購買一樣，所以 2022 年的 Activation、指南和調查，以及現在的 AI 回饋，都非常有意義。所以你總是同時做這兩件事。

I think the important part is we're not religious. And so whatever gives us the shortest path to market, like with AI Feedback, that would have taken us a year -- I'd like to say only a year, but the reality is probably more like two to get to the same point a state-of-the-art product like Kraftful was. And the same with Command on Guides and Surveys, that would have taken us two to three years, no question, at least to build internally. So it's just a much faster path to market. So we're always looking at both.

我認為最重要的是我們沒有宗教信仰。因此，任何能讓我們以最短路徑進入市場的方法，例如人工智慧回饋，都需要一年的時間——我希望說只需要一年，但實際上可能需要兩年才能達到像 Kraftful 那樣的尖端產品水平。對於指南和調查的指揮系統也是如此，毫無疑問，至少在內部建立該系統需要兩到三年的時間。所以，這是一種更快的上市途徑。所以我們始終都在關注這兩方面。

The other thing I want to point out is that I think -- I've been really excited to work with the founders that we have. Yana on -- from Kraftful has done a phenomenal job of educating me about AI and educating a lot of the rest of the company. Same with Enzo and Ferruccio from June, same from Frank and Eric from Inari, like they've all done a phenomenal job of like they've been building in this space in an AI-native way for a bunch of years. And so, as we're looking to change the makeup of the team to be able to build -- to look much more like an AI start-up, then like they're the tip of the spear on that. And so the explosion of products you've seen has come from ideas seeded by different folks from that group.

我想指出的另一點是，我認為——我非常高興能與我們的創辦人團隊一起工作。來自 Kraftful 的 Yana 在人工智慧領域做出了卓越的貢獻，她不僅讓我了解了人工智慧，還為公司其他許多員工普及了相關知識。Enzo 和 Ferruccio（來自 June）也是如此，Frank 和 Eric（來自 Inari）也是如此，他們都做得非常出色，多年來一直以人工智慧原生的方式在這個領域進行建設。因此，我們正在尋求改變團隊的組成，以便能夠建立——使其看起來更像人工智慧新創公司，而不是像他們是這方面的先鋒。因此，你所看到的爆炸式增長的產品，都源自於該群體中不同人士提出的想法。

So just as an example, like AI Agents was led by James Evans from Command, and then now Frank from Inari is taking it. And then, like Yana is working on LLM analytics, as well as a bunch of automated insights that we haven't even got to talk about yet. And then, you combine that with folks who have been at Amplitude for a long time and you get just incredible results. So like, yes, you -- you pair a lot of long-time product veterans at Amplitude with some folks who have been in the AI ecosystem and you're just able to be really aggressive about the innovation.

舉個例子，AI Agents 最初是由 Command 公司的 James Evans 領導的，現在由 Inari 公司的 Frank 接手。然後，就像 Yana 正在研究 LLM 分析，以及一大堆我們還來不及討論的自動化洞察。再加上那些在 Amplitude 工作多年的員工，就能取得令人難以置信的成果。所以，沒錯，你們——你們把 Amplitude 的許多資深產品專家與一些在人工智慧生態系統中工作過的人結合起來，你們就能在創新方面非常積極進取。

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

驚人的。然後，就獲利模式而言，您提到您將免費提供其中一些功能。您認為——未來是否會以活動為分母，從而真正考慮定價和包裝？或者，我們應該考慮採用其他方式來思考這個問題？

Okay. So this is a topic I'm very passionate about. A lot of people in the AI space talk about outcomes-based pricing. I think it is an awful idea because you spend out a lot of time arguing with your customers about, was that a good outcome? It's like -- what works much better is the same meter-based pricing that you had in SaaS.

好的。這是我非常熱衷的話題。人工智慧領域的許多人都在談論基於結果的定價。我認為這是一個糟糕的主意，因為你會花很多時間與客戶爭論，這個結果是否理想？這就好比——SaaS 中那種按量計費的定價方式效果要好得多。

So whether that's, in our case, events, some seats, some cases like tickets handles or size of customer base or what have you. But the customers have been most receptive. Like they don't want to feel like they're getting screwed. And like whenever you try to introduce a new metric or a new way of doing pricing, it raises a huge number of red flags. Whereas if you go with something they've already been used to using like events and data volume, like they're extremely comfortable with that.

所以，無論是像我們這裡提到的活動、一些座位，還是像門票處理量或客戶群規模之類的情況。但顧客的接受度非常高。好像他們不想覺得自己被坑了。就像每當你嘗試引入新的指標或新的定價方式時，都會引發大量的擔憂。而如果你使用他們已經習慣使用的東西，例如事件和數據量，他們就會感到非常得心應手。

And so we're not -- yes, we're not planning -- while I think there are things we're going to continue to improve about our pricing to better make sure we have a fair exchange of value between us and our customers, we don't want to -- we actually are looking to simplify our meters, and that's something we're going to be coming out with next year where we're just going to focus on the events piece.

所以，我們目前沒有——是的，我們沒有計劃——雖然我認為我們會繼續改進定價，以更好地確保我們與客戶之間實現公平的價值交換，但我們不想——我們實際上正在尋求簡化我們的計量表，這是我們明年將要推出的產品，屆時我們將只專注於活動部分。

Great. Thank you, Clark.

偉大的。謝謝你，克拉克。

That will conclude our third-quarter earnings call. Thank you for your time and interest.

我們的第三季財報電話會議到此結束。感謝您抽出寶貴時間並對此感興趣。

awe look forward to seeing you on the road this quarter as we attend conferences hosted by UBS and Needham. Thank you.

我們期待在本季與您在路上見面，我們將參加由瑞銀集團和尼德姆公司主辦的會議。謝謝。

Thank you, guys.

謝謝大家。