Snowflake Inc (SNOW) 2021 Q3 法說會逐字稿

Ladies and gentlemen, thank you for standing by, and welcome to the Snowflake Q3 FY '21 Earnings Call. (Operator Instructions) Please be advised that today's conference is being recorded. (Operator Instructions)

女士們，先生們，感謝你們的支持，歡迎來到 Snowflake Q3'21 財年收益電話會議。 （操作員說明）請注意，今天的會議正在錄製中。 （操作員說明）

I would now like to hand the conference over to your speaker today, Jimmy Sexton, Head of Investor Relations. Thank you. Please go ahead.

我現在想把會議交給今天的演講者，投資者關係主管 Jimmy Sexton。謝謝。請繼續。

Good afternoon, and thank you for joining us on Snowflake's Q3 Fiscal 2021 Earnings Call. Joining me are Frank Slootman, our Chairman and Chief Executive Officer; and Mike Scarpelli, our Chief Financial Officer.

下午好，感謝您加入我們的 Snowflake 2021 財年第三季度財報電話會議。加入我的是我們的董事長兼首席執行官 Frank Slootman；和我們的首席財務官 Mike Scarpelli。

During today's call, we will review our financial results for third quarter fiscal 2021 and discuss our guidance for the fourth quarter and full year fiscal 2021. During today's call, we will make forward-looking statements, including statements related to the expected performance of our business, future financial results, strategy, long-term growth and overall future prospects. These statements are subject to risks and uncertainties, which could cause them to differ materially from actual results. Information concerning those risks is available in our earnings press release distributed after market close today and in our SEC filings, including the Form 10-Q for the quarter ended October 31, 2020, that will be filed with the SEC today. We caution you not to place undue reliance on forward-looking statements and undertake no duty or obligation to update any forward-looking statements as a result of new information, future events or changes in our expectations.

在今天的電話會議上，我們將回顧我們 2021 財年第三季度的財務業績，並討論我們對 2021 財年第四季度和全年的指導。在今天的電話會議上，我們將做出前瞻性陳述，包括與我們預期業績相關的陳述業務、未來財務業績、戰略、長期增長和整體未來前景。這些陳述受風險和不確定因素的影響，可能導致它們與實際結果存在重大差異。有關這些風險的信息可在我們今天收盤後發布的收益新聞稿和我們向美國證券交易委員會提交的文件中找到，包括將於今天向美國證券交易委員會提交的截至 2020 年 10 月 31 日的季度的 10-Q 表。我們告誡您不要過分依賴前瞻性陳述，並且不承擔因新信息、未來事件或我們預期的變化而更新任何前瞻性陳述的責任或義務。

We'd also like to point out that on today's call, we will report both GAAP and non-GAAP results. We use these non-GAAP financial measures internally for financial and operational decision-making purposes and as a means to evaluate period-to-period comparisons. Non-GAAP financial measures are presented in addition to and not as a substitute to -- for financial measures calculated in accordance with GAAP. To see the reconciliation of these non-GAAP measures, please refer to our earnings press release distributed earlier today and our investor presentation, which are posted at investors.snowflake.com. A replay of today's call will also be posted on the website.

我們還想指出，在今天的電話會議上，我們將報告 GAAP 和非 GAAP 結果。我們在內部使用這些非 GAAP 財務措施來進行財務和運營決策，並作為評估期間比較的一種方式。非 GAAP 財務指標是根據 GAAP 計算的財務指標的補充而非替代。要查看這些非 GAAP 措施的協調情況，請參閱我們今天早些時候發布的收益新聞稿和我們在 investors.snowflake.com 上發布的投資者介紹。今天電話會議的重播也將發佈在網站上。

With that, I would now like to turn the call over to Frank.

有了這個，我現在想把電話轉給弗蘭克。

Thanks, Jimmy, and good afternoon, everybody, and thanks for joining us on our inaugural earnings call.

謝謝，吉米，大家下午好，感謝您加入我們的首次財報電話會議。

Let's review the results. We saw strong consumption trends across our customer base in Q3 with product revenue growing 115% year-on-year to $148 million and a net revenue retention rate of 162%. Coupled with this rapid growth, we continue to see improving unit economics, cash flow and operating efficiency.

讓我們回顧一下結果。我們在第三季度的客戶群中看到了強勁的消費趨勢，產品收入同比增長 115% 至 1.48 億美元，淨收入保留率為 162%。加上這種快速增長，我們繼續看到單位經濟、現金流和運營效率的改善。

Our growth is driven by long-term secular trends in data science and analytics enabled by cloud scale computing. With the onslaught of digital transformation, data operations have become the beating heart of the modern enterprise.

我們的增長是由雲規模計算支持的數據科學和分析的長期長期趨勢推動的。隨著數字化轉型的衝擊，數據運營已成為現代企業的核心。

The pandemic has been more or less neutral to our business. Some businesses were negatively affected in terms of demand sentiment, but others stepped up their data strategy given the new complexities of the health crisis and economic effects. It bears repeating that Snowflake is not a SaaS business model. We're a consumption company, and our reported revenue has a direct relationship with the consumption of our platform during the period. The consumption model is variable, not fixed, meaning our model places no limits on how much of our platform a customer can consume, and this contributes to our strong revenue retention rate.

大流行對我們的業務或多或少是中性的。一些企業在需求情緒方面受到了負面影響，但鑑於健康危機和經濟影響的新復雜性，其他企業加強了數據戰略。值得重申的是，Snowflake 不是 SaaS 商業模式。我們是一家消費公司，我們報告的收入與期間我們平台的消費有直接關係。消費模式是可變的，而不是固定的，這意味著我們的模式對客戶可以消費多少我們的平台沒有限制，這有助於我們保持強勁的收入保留率。

The technology is now ahead of people's ability to take advantage of virtually unbounded capacity, scale and performance. Over the past year, Snowflake has augmented its selling motion to campaign some of the largest enterprises and institutions in the world. Snowflake is well represented now in 8 of the Fortune 10, and we added 12 Fortune 500 customers in Q3, including Fiserv and GEICO.

該技術現在領先於人們利用幾乎無限的容量、規模和性能的能力。在過去的一年裡，Snowflake 加強了其營銷活動，以宣傳世界上一些最大的企業和機構。 Snowflake 現在在財富 10 強中的 8 個中都有很好的代表，我們在第三季度增加了 12 個財富 500 強客戶，包括 Fiserv 和 GEICO。

Interest in Snowflake is growing. We hosted our Snowflake Data Cloud Summit 2 weeks ago at over 40,000 registrations, up from 15,000 registrations at our Snowflake summit in June.

人們對 Snowflake 的興趣正在增長。我們在 2 週前舉辦了 Snowflake 數據云峰會，註冊人數超過 40,000，高於 6 月份 Snowflake 峰會的 15,000。

Shifting gears, I'd like to take a moment here and introduce you to the Snowflake data cloud because it's the centerpiece of our mission and strategy. As an industry, we have struggled to mobilize our data, meaning that it's been hard to put data in the service of our enterprise. And we set out to change that. As we see it, we've never had a data cloud in the history of computing. We are used to SaaS applications as application clouds and the massive infrastructure clouds like AWS, Azure and Google Cloud, servers and storage you can consume by the drink. But data lives absolutely everywhere, in millions of places, held hostage by machines, applications, networks and clouds. We have long needed to blend and join disparate data sets. That's why we build data warehouses in the first place. They were expensive, capacity constrained and require tons of data preparation and manipulation prior to use. Only the largest, most demanding data states could afford these platforms, so they were never pervasive.

換檔，我想在這里花點時間向您介紹 Snowflake 數據云，因為它是我們使命和戰略的核心。作為一個行業，我們一直在努力移動我們的數據，這意味著很難將數據用於我們企業的服務。我們著手改變這一點。正如我們所見，我們在計算歷史上從未有過數據云。我們習慣於將 SaaS 應用程序作為應用程序云，以及 AWS、Azure 和谷歌云等龐大的基礎設施雲、服務器和存儲，你可以隨飲隨用。但數據無處不在，存在於數百萬個地方，被機器、應用程序、網絡和雲所挾持。我們長期以來一直需要混合和連接不同的數據集。這就是我們首先構建數據倉庫的原因。它們價格昂貴，容量有限，並且在使用前需要大量的數據準備和操作。只有最大、最苛刻的數據狀態才能負擔得起這些平台，因此它們從未普及。

Snowflake changed that, drastically scaling down to the smallest jobs and radically changing the economics with a highly elastic utility model. Not only could everybody now afford these great powers, Snowflake also removed constraints on data volume, cluster performance and concurrent workload execution. Even high-end users reported being able to cut their existing spend and expand their workloads dramatically at the same time.

Snowflake 改變了這一點，大幅縮減到最小的工作崗位，並通過高度彈性的實用模型從根本上改變了經濟。現在不僅每個人都能負擔得起這些強大的功能，Snowflake 還消除了對數據量、集群性能和並發工作負載執行的限制。即使是高端用戶也報告說他們能夠同時大幅削減現有支出和增加工作量。

As compelling as Snowflake was to turbo existing workloads, old habits die hard. Many customers are still evaluating data platforms one workload at a time, basically limiting data operations to their silos. That's like steering a ship by its wake. Future workload will look different, with machine learning and data science becoming ultimate users. The workload-at-a-time mentality leads to building the silos of the future.

與 Snowflake 對現有工作負載的提升一樣引人注目，舊習慣很難改掉。許多客戶仍在一次評估一個工作負載的數據平台，基本上將數據操作限制在他們的孤島內。這就像靠尾流操縱船。隨著機器學習和數據科學成為最終用戶，未來的工作量將有所不同。一次工作量的心態導致建立未來的孤島。

The Snowflake data cloud is a data universe, a global data orbit, where Snowflake users effortlessly plug in, discover, explore and access data from an incredible growing variety of sources. It's a different way of thinking about the data needs of the future. The Snowflake data cloud combines world-class execution with unfettered data access. Customers need both.

Snowflake 數據云是一個數據宇宙，一個全球數據軌道，Snowflake 用戶可以在其中毫不費力地插入、發現、探索和訪問來自不斷增長的各種來源的數據。這是對未來數據需求的另一種思考方式。 Snowflake 數據云結合了世界一流的執行力和不受限制的數據訪問。客戶兩者都需要。

We're seeing promising signs of adoption with already 23% of our customers using our data-sharing capabilities. We also continue to onboard new data providers. And in Q3, we added Standard & Poor's Global, Morningstar and CoreLogic, to name a few, and we now have over 100 data providers on our marketplace.

我們已經看到 23% 的客戶正在使用我們的數據共享功能，採用的跡象令人鼓舞。我們還繼續加入新的數據提供商。在第三季度，我們增加了標準普爾全球、晨星和 CoreLogic 等，現在我們的市場上有 100 多家數據提供商。

At the Snowflake Data Cloud Summit, we heard from customers about the impact that the data cloud is having on their business. A retail rewards customer has fully embraced the data cloud. Snowflake allows them to securely share data sets with media partners, empower customer-facing applications to target their end users. Commercial data providers are also turning to Snowflake to reach new customers and monetize our data by making the data available in the Snowflake Data Marketplace. Experian helped retail customers accelerate their digital transformation efforts. Experian's retail customers are now reaching shoppers online with insights garnered from Snowflake's Data Marketplace to reach customers who are no longer shopping in stores.

在 Snowflake 數據云峰會上，我們從客戶那裡聽到了數據云對其業務的影響。零售獎勵客戶已完全接受數據云。 Snowflake 使他們能夠與媒體合作夥伴安全地共享數據集，使面向客戶的應用程序能夠以最終用戶為目標。商業數據提供商也轉向使用 Snowflake 來接觸新客戶，並通過在 Snowflake 數據市場上提供數據來通過我們的數據獲利。 Experian 幫助零售客戶加快了他們的數字化轉型工作。 Experian 的零售客戶現在通過從 Snowflake 的數據市場獲得的見解接觸在線購物者，以接觸不再在商店購物的客戶。

Let's highlight some product announcements from the Snowflake Data Cloud Summit in November. First, we've grown our partnership with Salesforce. The previously announced output connector is now generally available and allows customers to more easily sync Salesforce data with Snowflake. Secondly, we announced Snowpark, our new developer experience. Snowpark will enable users to write code in their preferred language to build data transformations and score machine learning models, all processed by Snowflake. Third, we announced support for unstructured data in addition to our long-standing support for structured and semi-structured data. And lastly, we are enhancing our data governance strategy with the introduction of row-access policies, tagging and column masking. This will help our customers control access by user type in a highly granular fashion. Very important, given the heightened sensitivity around data governance. These capabilities are essential to grow on the data cloud, and you can expect more platform enhancements from us going forward.

讓我們重點介紹 11 月 Snowflake 數據云峰會上發布的一些產品。首先，我們加強了與 Salesforce 的合作夥伴關係。之前宣布的輸出連接器現已普遍可用，使客戶能夠更輕鬆地將 Salesforce 數據與 Snowflake 同步。其次，我們發布了全新的開發者體驗 Snowpark。 Snowpark 將使用戶能夠用他們喜歡的語言編寫代碼，以構建數據轉換和評分機器學習模型，所有這些都由 Snowflake 處理。第三，除了我們長期以來對結構化和半結構化數據的支持外，我們還宣布支持非結構化數據。最後，我們正在通過引入行訪問策略、標記和列屏蔽來增強我們的數據治理策略。這將幫助我們的客戶以高度精細的方式按用戶類型控制訪問。鑑於圍繞數據治理的敏感性提高，這一點非常重要。這些功能對於在數據云上發展至關重要，您可以期待我們未來提供更多平台增強功能。

Before closing, I would like to highlight the upcoming release of our book, the Rise of the Data Cloud. We wrote this book because the data cloud is the centerpiece of our strategy and vision. We showcased many customers in numerous vertical industries with their Snowflake journeys and experiences. It's meant to enlighten and inspire, something we call the art of the possible. The book will be available on December 4.

在結束之前，我想強調一下我們即將出版的新書《數據云的崛起》。我們寫這本書是因為數據云是我們戰略和願景的核心。我們向眾多垂直行業的許多客戶展示了他們的 Snowflake 旅程和經驗。它旨在啟發和啟發，我們稱之為可能性的藝術。該書將於 12 月 4 日上市。

In closing, we're pleased with our quarter and excited about the momentum coming out of the Data Cloud Summit as we head into the final quarter of our fiscal year.

最後，我們對本季度感到滿意，並對數據云峰會在我們進入本財年最後一個季度時產生的勢頭感到興奮。

With that, I will turn the call over to Mike.

有了這個，我會把電話轉給邁克。

Thank you, Frank. Before I discuss our results and guidance, I would like to spend some time discussing our unique and powerful business model. We are not a SaaS model. We are a consumption model. Our business model is a key differentiator for us and is designed to drive customer success. Our customers purchase credits, and when those credits are consumed, we recognize the revenue. Unlike a ratable model, we only recognize revenue if the customer uses our platform. For this reason, there is no shelfware in our revenue.

謝謝你，弗蘭克。在我討論我們的結果和指導之前，我想花一些時間討論我們獨特而強大的商業模式。我們不是 SaaS 模型。我們是一個消費模型。我們的商業模式是我們的關鍵差異化因素，旨在推動客戶成功。我們的客戶購買積分，當這些積分被消耗時，我們確認收入。與評級模型不同，我們僅在客戶使用我們的平台時才確認收入。因此，我們的收入中沒有貨架軟件。

For many customers, it takes several months up -- until they are up and running at full capacity. And this model gives them the flexibility to purchase the amount they plan on using without wasting credits or exceeding their original contract if they consume more than planned. For these reasons, we do not focus on the same metrics that a SaaS business would. We focus on product revenue and remaining performance obligation. Product revenue, which excludes professional services and other revenue, is the most transparent disclosure we offer. It gives full insight into how our customers are actually using our product in the period reported. If a customer purchases credits and does not consume, their revenue will be $0.

對於許多客戶來說，這需要幾個月的時間——直到他們以滿負荷運行。這種模式讓他們可以靈活地購買他們計劃使用的數量，而不會浪費信用或超過他們原來的合同，如果他們消耗超過計劃。由於這些原因，我們關注的指標與 SaaS 業務不同。我們關注產品收入和剩餘履約義務。產品收入（不包括專業服務和其他收入）是我們提供的最透明的披露。它可以全面了解我們的客戶在報告期間如何實際使用我們的產品。如果客戶購買了積分但沒有消費，他們的收入將為 0 美元。

We also focus on remaining performance obligation or RPO. RPO represents all the contracted revenue not yet recognized, including both deferred revenue and noncancelable contracted amounts that will be invoiced and recognized as revenue in future periods.

我們還關注剩餘履約義務或 RPO。 RPO 代表所有尚未確認的合同收入，包括遞延收入和不可取消的合同金額，這些金額將在未來期間開具發票並確認為收入。

Unlike most SaaS businesses, billings is not a meaningful metric for us because it is less correlated to product revenue due to the variability of consumption.

與大多數 SaaS 業務不同，賬單對我們來說不是一個有意義的指標，因為由於消費的可變性，它與產品收入的相關性較低。

I would also like to mention that our GAAP financials will now be available on the Snowflake marketplace, and we encourage all of you to consume our financial information in a new way. Going forward, we will be publishing our quarterly results on the marketplace in conjunction with our earnings.

我還想提一下，我們的 GAAP 財務信息現在將在 Snowflake 市場上提供，我們鼓勵大家以一種新的方式使用我們的財務信息。展望未來，我們將在市場上公佈我們的季度業績和我們的收益。

Now let's turn to our results and guidance. For Q3, product revenues were $148 million, representing 115% year-over-year growth. Our remaining performance obligation was $928 million, representing 240% year-over-year growth with a weighted average life of multiyear contracts of 2.5 years. This strong performance is driven by our customer base realizing the value of our platform for their existing use cases while also embracing the Snowflake data cloud vision.

現在讓我們談談我們的結果和指導。第三季度，產品收入為 1.48 億美元，同比增長 115%。我們剩餘的履約義務為 9.28 億美元，同比增長 240%，多年期合同的加權平均期限為 2.5 年。這種強大的性能是由我們的客戶群推動的，他們意識到我們的平台對他們現有用例的價值，同時也接受了 Snowflake 數據云願景。

As I mentioned earlier, our business model allows our customers to consume their entire contract before the end of the term, which is what we often see. We also continue to see customers willing to make more multiyear commitments with us, which is a direct result of the value our customers can create with us.

正如我之前提到的，我們的商業模式允許我們的客戶在期限結束前消費他們的整個合同，這是我們經常看到的。我們還繼續看到客戶願意與我們做出更多的多年期承諾，這是我們的客戶可以與我們一起創造價值的直接結果。

As we continue to scale, we are increasingly focused on moving upmarket, and you can see the benefits of those investments paying off. In Q3, we saw the number of customers consuming greater than $1 million in trailing 12-month product revenue increase to 65, up from 31 in the same period last year.

隨著我們不斷擴大規模，我們越來越專注於向高端市場發展，您可以看到這些投資帶來的好處。在第三季度，我們看到在過去 12 個月的產品收入中消費超過 100 萬美元的客戶數量從去年同期的 31 個增加到 65 個。

Turning to margins. On a non-GAAP basis, our product gross margin was 70%, positively impacted by onetime credits received from a cloud service provider in connection with our new agreements. Operating margin was negative 30%, benefiting from lower-than-expected employee-related costs. And our adjusted free cash flow margin was negative 23%, positively impacted by prepayments coming in lower than expected and stronger operating margin.

轉向利潤率。在非 GAAP 基礎上，我們的產品毛利率為 70%，受到與我們的新協議相關的從雲服務提供商處獲得的一次性信貸的積極影響。營業利潤率為負 30%，這得益於低於預期的員工相關成本。我們調整後的自由現金流利潤率為負 23%，這受到低於預期的預付款和更高的營業利潤率的積極影響。

Going forward, we will report and guide non-GAAP adjusted free cash flow. Adjusted free cash flow will exclude the impact of cash paid for employer payroll tax items on employee stock transactions. This quarter, we saw $800,000 impact from those items. For a detailed bridge of cash flow from operations to adjusted free cash flow, please refer to our investor presentation on our IR website.

展望未來，我們將報告和指導非 GAAP 調整後的自由現金流。調整後的自由現金流將不包括為雇主工資稅項目支付的現金對員工股票交易的影響。本季度，我們看到這些項目產生了 800,000 美元的影響。有關運營現金流與調整後自由現金流的詳細銜接，請參閱我們 IR 網站上的投資者介紹。

We ended the quarter in a strong cash position with approximately $5.1 billion in cash, cash equivalents and short-term and long-term investments. This capital allows us to invest in new strategic initiatives such as Snowflake ventures, which we announced last month. Snowflake Ventures' mission is to enable more organizations to harness the power of the data cloud. To do this, we will invest in growth stage companies that demonstrate a commitment to mobilizing data, providing value to our customers and expand opportunities for the data cloud.

本季度結束時，我們的現金狀況良好，現金、現金等價物以及短期和長期投資約為 51 億美元。這筆資金使我們能夠投資於新的戰略計劃，例如我們上個月宣布的 Snowflake ventures。 Snowflake Ventures 的使命是讓更多組織能夠利用數據云的力量。為此，我們將投資那些致力於移動數據、為我們的客戶提供價值並擴大數據云機會的成長期公司。

Similarly, we will continue to evaluate strategic tuck-in opportunities and M&A focused on talent and technology. Our acquisition strategy aligns with our product strategy. Everything must be done the Snowflake way, and that means delivering as one native product.

同樣，我們將繼續評估以人才和技術為重點的戰略整合機會和併購。我們的收購戰略與我們的產品戰略一致。一切都必須以 Snowflake 的方式完成，這意味著作為一種本地產品進行交付。

Now I would like to give an update on how we view COVID impacting our forecast. Our forecast assumes our employees will continue to be working remotely for the foreseeable future. We have proven our ability to maintain productivity during the pandemic and are in no rush to return back to the office and regular travel. Leveraging Zoom and other collaboration tools, we've been operating at a high level and able to smoothly onboard over 500 employees during the pandemic. We believe we will eventually be back in the office, but until we have new information and can guarantee our employees' safety, we will continue to work remotely.

現在我想更新一下我們如何看待 COVID 影響我們的預測。我們的預測假設我們的員工在可預見的未來將繼續遠程工作。我們已經證明我們有能力在大流行期間保持生產力，並且不急於返回辦公室和定期旅行。利用 Zoom 和其他協作工具，我們一直在高水平運營，並能夠在大流行期間順利地讓 500 多名員工入職。我們相信我們最終會回到辦公室，但在我們獲得新信息並能夠保證員工安全之前，我們將繼續遠程工作。

Now let's turn to guidance for the fourth quarter and full year fiscal 2021. For the fourth quarter ending January 31, 2021, we expect product revenues between $162 million and $167 million, representing year-over-year growth between 97% and 103%.

現在讓我們轉向對 2021 財年第四季度和全年的指導。對於截至 2021 年 1 月 31 日的第四季度，我們預計產品收入在 1.62 億美元至 1.67 億美元之間，同比增長 97% 至 103%。

Turning to margins. We expect on a non-GAAP basis an implied 70% product gross margin, negative 30% operating margin and negative 8% adjusted free cash flow margin, and we expect 283 million weighted average shares outstanding.

轉向利潤率。我們預計在非 GAAP 的基礎上，隱含的產品毛利率為 70%，營業利潤率為負 30%，調整後的自由現金流利潤率為負 8%，我們預計加權平均流通股數為 2.83 億股。

I would like to remind everyone that because of our consumption-based business model, we do not recognize revenue immediately after a deal is booked. For this reason, you may not see a revenue beat flowing through to the next quarter like you would in a ratable business model. Just because a customer consumes in a certain pattern in 1 quarter, it does not necessarily mean they will continue those patterns going forward.

我想提醒大家的是，由於我們以消費為基礎的商業模式，我們不會在交易完成後立即確認收入。出於這個原因，您可能不會像在評級業務模型中那樣看到下一季度的收入增長。僅僅因為客戶在 1 個季度以某種模式消費，並不一定意味著他們將繼續這些模式。

For the full year fiscal 2021, we expect product revenues between $538 million and $543 million, representing year-over-year growth of between 113% and 115%.

對於 2021 財年全年，我們預計產品收入在 5.38 億美元至 5.43 億美元之間，同比增長 113% 至 115%。

Turning to margins. We expect on a non-GAAP basis 68% product gross margin, negative 40% operating margin and negative 18% adjusted free cash flow margin, and we expect 255 million weighted average shares outstanding.

轉向利潤率。我們預計在非美國通用會計準則的基礎上，產品毛利率為 68%，營業利潤率為負 40%，調整後的自由現金流利潤率為負 18%，我們預計加權平均流通股數為 2.55 億股。

With that, operator, you can now open up the line for questions.

有了這個，接線員，你現在可以打開問題熱線了。

(Operator Instructions) Your first question comes from the line of Heather Bellini from Goldman Sachs.

（操作員說明）您的第一個問題來自高盛的 Heather Bellini。

Great. And congratulations on the first quarter out of the gate. I wanted to ask a little bit, you mentioned kind of keeping your employees home as a result of COVID until things are safe. But wondering if you could share with us a little bit about what you've noticed in terms of the pace of consumption trends as the pandemic's been going on and as people prioritize moving to the cloud. Can you share with us any anecdotal data about how customers might be even accelerating their pace of capacity usage with Snowflake?

偉大的。並祝賀第一季度走出大門。我想問一點，您提到過由於 COVID 而讓您的員工留在家中，直到一切安全為止。但是想知道您是否可以與我們分享一下您在大流行病的持續發展以及人們優先考慮遷移到雲端時在消費趨勢方面所注意到的情況。您能否與我們分享任何關於客戶如何使用 Snowflake 加快容量使用速度的軼事數據？

Yes, Heather, it's Frank. I'll give you one example. We have a data set on our Snowflake Data Marketplace that's listed by a company called Starschema, which provides detailed incident of fatality rates. Very, very detailed, and they're updated continually. And we saw almost our entire customer base access that data within days and weeks. And when that happens, it drives consumption. And that access has continued to this day. So sometimes you have catalysts and specific data sets that really help customers overlay data, run models, understand their demand environment better and so on. It's hard to generalize, this is just sort of a single anecdote that kind of stands out to us.

是的，希瑟，是弗蘭克。我給你舉一個例子。我們的 Snowflake 數據市場上有一個數據集，由一家名為 Starschema 的公司列出，該公司提供詳細的死亡率事件。非常非常詳細，並且不斷更新。我們看到幾乎整個客戶群都在幾天和幾週內訪問了該數據。當這種情況發生時，它會推動消費。這種訪問一直持續到今天。所以有時候你有催化劑和特定的數據集，可以真正幫助客戶疊加數據、運行模型、更好地了解他們的需求環境等等。很難一概而論，這只是一個對我們來說很突出的軼事。

I would add, Heather, that we do see in certain industries, like we have some customers that are in the travel industry, we see their consumption down. But we have a lot of customers that are kind of more in the online consumer world that their business is booming, and their consumption is much higher than we're forecasting. So it all depends upon the industry they're in, but on average, we're seeing our customers consume more than we would expect. That's why we ended up beating by what we did. It was a higher beat than I was expecting for the quarter.

希瑟，我要補充一點，我們確實在某些行業看到了，比如我們有一些旅遊行業的客戶，我們看到他們的消費下降了。但我們有很多客戶更多地處於在線消費世界，他們的業務正在蓬勃發展，他們的消費遠高於我們的預測。所以這完全取決於他們所在的行業，但平均而言，我們看到我們的客戶消費的比我們預期的要多。這就是為什麼我們最終被我們所做的擊敗。這比我對本季度的預期要高。

Your next question comes from the line of Raimo Lenschow from Barclays.

你的下一個問題來自巴克萊銀行的 Raimo Lenschow。

Congrats from me as well for the first quarter. And thanks for the presentation as well, a lot of useful information in there. Frank, question for you. You mentioned earlier about the data formats that you're kind of dealing with and that you're now doing also like unstructured data. Can you talk a little bit about the evolution? Because when Snowflake started out, it was a very good relational cloud data warehouse, and then you guys became much broader. Can you talk a little bit like how do you see that evolving? How quickly you see customer adoptions in the other areas of working with data coming through as well? And then I have one follow-up for Mike.

我也祝賀第一季度。也感謝您的介紹，其中提供了很多有用的信息。弗蘭克，向你提問。你之前提到過你正在處理的數據格式，你現在正在做的也像非結構化數據。你能談談進化嗎？因為當 Snowflake 開始的時候，它是一個非常好的關係型雲數據倉庫，然後你們就變得更廣泛了。你能談談你如何看待這種演變嗎？您看到客戶在處理數據的其他領域採用的速度有多快？然後我要跟進 Mike。

Yes. So the overarching theme here is that we have evolved Snowflake from being the data warehouse in the cloud to being a cloud data platform. And the distinction there is a much expanding scope of workloads. For those who have not been following Snowflake that long, we actually got our start processing semi-structured data. That was really a big differentiator for us going back to 2015, '16. Yes. But certainly, structured relational data is a mainstay of our business.

是的。因此，這裡的首要主題是我們已經將 Snowflake 從雲中的數據倉庫發展為雲數據平台。區別在於工作負載的範圍大大擴大。對於那些關注 Snowflake 時間不長的人來說，我們實際上已經開始處理半結構化數據。這對我們回到 2015 年、'16 年來說確實是一個很大的區別。是的。但可以肯定的是，結構化關係數據是我們業務的支柱。

But when you're following a cloud data platform strategy, what happens is that our customers are seeking broader workload support, broader data support. And we also announced a couple of quarters ago support for geospatial data, and the uptake of that new data type is just enormous. So there is ferocious appetite in our customer base for us expanding the scope of our capabilities, both in terms of workloads and in terms of data types, our ability to use external services. So it's a very broadly capable platform. Customers don't want a multitude of platforms in their environment. They're very, very intent of bringing as much data as they possibly can onto Snowflake and running as many workloads as they can on Snowflake, and we're running hard to enable that.

但是，當您遵循雲數據平台戰略時，我們的客戶正在尋求更廣泛的工作負載支持、更廣泛的數據支持。我們還在幾個季度前宣布了對地理空間數據的支持，這種新數據類型的採用量非常大。因此，我們的客戶群對我們擴展我們的能力範圍有著強烈的需求，無論是在工作負載方面還是在數據類型方面，我們使用外部服務的能力。所以這是一個功能非常廣泛的平台。客戶不希望他們的環境中有大量平台。他們非常非常有意將盡可能多的數據帶到 Snowflake 上，並在 Snowflake 上運行盡可能多的工作負載，我們正在努力實現這一目標。

Okay. Perfect. And then, Mike, on gross margins, I got the 68% gross margin kind of comment you gave. Can you talk a little bit about the puts and takes in terms of that in the long run? Obviously, with bigger scale, you have more negotiation power with the big cloud vendors. How is that going to change the margins going forward?

好的。完美的。然後，邁克，關於毛利率，我得到了你給出的 68% 的毛利率評論。從長遠來看，你能談談看跌期權和看跌期權嗎？顯然，規模越大，你與大型雲供應商的談判能力就越大。這將如何改變未來的利潤率？

Sure. So as you saw for the most recent quarter, we just did 70% gross margin. And the implied for the full year is 68%, but we're actually going to do 70% margin in Q4. As we talked about when we were going public, I do think longer term, in terms of model, we can get to the mid-70s.

當然。因此，正如您在最近一個季度看到的那樣，我們的毛利率僅為 70%。全年的隱含利潤率為 68%，但我們實際上將在第四季度實現 70% 的利潤率。正如我們談到上市時間，我確實認為從長遠來看，就模型而言，我們可以達到 70 年代中期。

And it's really driven by a few things. One is better pricing with our cloud vendors. We did just renegotiate deals with 2 of our cloud vendors, AWS and Azure, who are the majority of virtually all of our businesses running there today. And I do think as we continue to grow, we'll be able to renegotiate those again. Scale, we have a lot of deployments around the world where we're not even close to being at scale. And especially as EMEA is starting to take off for us, we'll get more scale in those, which will drive better margins for us.

它真的是由幾件事驅動的。一是我們的雲供應商提供更好的定價。我們確實剛剛與我們的 2 個雲供應商 AWS 和 Azure 重新談判了交易，它們幾乎是我們今天在那裡運營的所有業務的大部分。而且我確實認為，隨著我們繼續發展，我們將能夠再次重新談判。規模，我們在世界各地有很多部署，我們甚至離規模還差得很遠。特別是隨著 EMEA 開始為我們騰飛，我們將在這些領域獲得更大的規模，這將為我們帶來更高的利潤。

And then also, we're seeing a lot better discipline in our field around discounting. And if you see the average price per credit we're getting, it continues to increase. So those are the 3 things that are really going to drive that margin.

然後，我們看到我們的領域在折扣方面有了更好的紀律。如果您看到我們獲得的每學分平均價格，它會繼續增加。所以這些是真正推動利潤率的三件事。

Your next question comes from Brent Bracelin from Piper Sandler.

您的下一個問題來自 Piper Sandler 的 Brent Bracelin。

One for Frank and a quick follow-up for Mike here. Frank, we're starting to pick up broader interest for Snowflake in the insurance industry, which makes sense, given this industry tends to be more data-intensive. But I guess could you talk about the opportunity you see for Snowflake in insurance or any other vertical maybe that stood out this quarter where you're seeing outsized traction?

一個是給 Frank 的，另一個是 Mike 的快速跟進。弗蘭克，我們開始對保險行業的 Snowflake 產生更廣泛的興趣，這是有道理的，因為這個行業往往是數據密集型的。但我想你能談談你在保險業或任何其他垂直領域看到的 Snowflake 在本季度脫穎而出的機會嗎？

Yes. I've been involved in a lot of insurance campaigns, and they're very keen on transformation more so than just modernization. Some of the -- many of the larger insurance companies have very broad cross-selling capabilities but do not have the systems to -- from an analytical data standpoint, to support that. So they're very, very intent on sort of dislodging themselves from their historical on-premise systems and really gain the promise of data sciences and machine learning. And you need to have platforms like Snowflake to be able to enable that.

是的。我參與了很多保險活動，他們非常熱衷於轉型，而不僅僅是現代化。一些 - 許多較大的保險公司具有非常廣泛的交叉銷售能力，但沒有系統 - 從分析數據的角度來看，支持它。因此，他們非常非常有意將自己從他們的歷史本地系統中移除，並真正獲得數據科學和機器學習的希望。而且您需要擁有像 Snowflake 這樣的平台才能實現這一點。

So yes, we announced a number of insurance accounts this quarter, and we love that industry because, as you said, they're very data-rich. There's enormous potential for us to really digitize, if you will, really bring digital transformation to the insurance industry. So super exciting.

所以是的，我們本季度宣布了一些保險賬戶，我們喜歡這個行業，因為正如你所說，它們的數據非常豐富。如果你願意的話，我們真正數字化的潛力巨大，真正為保險業帶來數字化轉型。太令人興奮了。

Great. And then Mike, just as we think about the RPO momentum this quarter, I mean, much stronger than I think we had kind of thought it would be. And I know you had the benefit of a very large contract last quarter. So what drove the acceleration in kind of new bookings this quarter and that upside in RPO?

偉大的。然後邁克，就像我們考慮本季度的 RPO 勢頭一樣，我的意思是，比我認為的要強得多。我知道你上個季度獲得了一份非常大的合同。那麼，是什麼推動了本季度新預訂的加速增長以及 RPO 的上升？

As we're moving more into large enterprises, large enterprises really want to do multiyear deals. They're not interested in having to go to procurement every year. And so we saw a number of large enterprises commit to multiyear deals with us, and we think that is going to be a trend that will continue. And I will say it wasn't until this year that our sales force really started pushing more 3-year deals, and we're going to continue to do that going forward in the future.

隨著我們越來越多地進入大型企業，大型企業確實希望進行多年交易。他們對每年都必須去採購不感興趣。因此，我們看到許多大型企業承諾與我們達成多年交易，我們認為這將成為一種持續的趨勢。我要說的是，直到今年我們的銷售團隊才真正開始推動更多 3 年期交易，我們將在未來繼續這樣做。

Your next question comes from the line of Patrick Colville from Deutsche Bank.

你的下一個問題來自德意志銀行的 Patrick Colville。

Congrats on the quarter, I mean, very impressive. Can I talk about the competitive environment in my first question? Just what do you guys see -- who do you see as the kind of most formidable competitors right now? And I guess what's happening in the on-premise world? Is that still kind of low-hanging fruit?

祝賀這個季度，我的意思是，非常令人印象深刻。我可以在第一個問題中談談競爭環境嗎？你們怎麼看 - 您認為誰是目前最強大的競爭對手？我想在內部部署世界中發生了什麼？那仍然是一種唾手可得的果實嗎？

Yes, Patrick, it's Frank. Our competitive environment is very much dominated by the public cloud vendors, I think we said that over and over, and it really hasn't changed. The only time that we're dealing with on-premise environments, as customers are trying to figure out how to modernize and move off of those platforms, they're really not viewed as options going forward. So it may be that our filter is biased, but where -- our competitive dynamic is very much centered on the 3 public cloud platforms. That is the vast majority of competitive interaction that we have.

是的，帕特里克，是弗蘭克。我們的競爭環境在很大程度上由公共雲供應商主導，我想我們一遍又一遍地說過，而且它確實沒有改變。我們唯一一次處理本地環境，因為客戶正試圖弄清楚如何實現這些平台的現代化和遷移，他們真的不被視為未來的選擇。因此，我們的過濾器可能有偏見，但我們的競爭動態主要集中在 3 個公共雲平台上。這是我們擁有的絕大多數競爭互動。

I would say the only time we really come across the on-prem is where they're the incumbent, and they're really not considering keeping them, and they're evaluating with us and the other public cloud players. That's why we don't necessarily see them as competitive. But they are definitely the incumbent in many of the cases.

我想說的是，我們唯一一次真正遇到本地部署是他們在位，他們真的沒有考慮保留它們，他們正在與我們和其他公共雲玩家一起評估。這就是為什麼我們不一定認為它們具有競爭力。但在許多情況下，他們絕對是現任者。

Got it. That's very clear. And I guess my second question is around the support for unstructured data. I mean that's a really interesting announcement. I guess what kind of use cases are you expecting, I guess, in that category in the near term? What kind of things that you think customers will likely -- what unstructured data will they likely start with?

知道了。這很清楚。我想我的第二個問題是關於對非結構化數據的支持。我的意思是這是一個非常有趣的公告。我猜你在短期內期待什麼樣的用例？您認為客戶可能會做什麼樣的事情——他們可能會從哪些非結構化數據開始？

Well, for sure, image data, video data, I mean, PDFs, social media. And by the way, this is also where ML services are going to become -- machine learning services are going to be really interesting because, say, I have image scans from webcams somewhere in the city, and I'm able to shoot that over to an external service, have it scanned, too, whether that's a recognizable, known person. There's going to be enormous potential for this. And we're -- as I said earlier, we're getting pushed by our customers to really bring these different data types onto our platform because they're just part of the types of analytical processes that they want to run. So that's sort of where we see these initially going. And these data types are large. This will definitely add to the storage side of the equation as well.

嗯，當然，圖像數據、視頻數據，我的意思是 PDF，社交媒體。順便說一下，這也是 ML 服務將要發展的地方——機器學習服務將變得非常有趣，因為，比如說，我有來自城市某處網絡攝像頭的圖像掃描，而且我能夠拍攝它到外部服務，也對其進行掃描，看它是否是可識別的、已知的人。這將有巨大的潛力。而且我們 - 正如我之前所說，我們正在被客戶推動真正將這些不同的數據類型帶到我們的平台上，因為它們只是他們想要運行的分析過程類型的一部分。所以這就是我們最初看到這些的地方。而且這些數據類型很大。這肯定也會增加等式的存儲方面。

Your next question comes from the line of Keith Weiss from Morgan Stanley.

你的下一個問題來自摩根士丹利的 Keith Weiss。

Excellent. I wanted to talk a little bit about Snowpark, another kind of recent announcement that you guys made. One, in terms of how does this evolve kind of the broader story in terms of overall Snowflake and sort of get more people engaged with the overall platform? Then if we think about the monetization strategy for something like Snowpark -- and I guess the same makes sense to sort of like the overall marketplace. Is this all in the service of just like sort of the more workloads you could get on the platform, the more consumption of that data, just more compute, and that's really how you get paid on all of these?

出色的。我想談談 Snowpark，這是你們最近發布的另一種公告。第一，就整體 Snowflake 而言，這如何演變出更廣泛的故事，以及如何讓更多人參與整個平台？然後，如果我們考慮像 Snowpark 這樣的東西的貨幣化策略——我想這對整個市場來說也是有意義的。這一切都是為了您可以在平台上獲得更多的工作負載、更多的數據消耗、更多的計算，而這就是您在所有這些方面獲得報酬的方式嗎？

Yes. Keith, it's Frank. Basically, we're enabling a whole different range of users on the Snowflake query end, right? I mean they are the data engineers that use the SQL language to interrogate data. And then there's a whole another world out there that interrogates data through their language of choice, notably Java and Python, and they use things like data frames to process their data. It's a very different mode. It's highly programmatic. A lot of data transformations, a lot of machine learning type of processes are executed through these languages.

是的。基思，是弗蘭克。基本上，我們在 Snowflake 查詢端啟用了完全不同範圍的用戶，對吧？我的意思是他們是使用 SQL 語言查詢數據的數據工程師。然後是另一個世界，通過他們選擇的語言查詢數據，特別是 Java 和 Python，他們使用數據框架之類的東西來處理他們的數據。這是一種非常不同的模式。它是高度程序化的。很多數據轉換，很多機器學習類型的過程都是通過這些語言執行的。

So what Snowpark will do is we will start hosting the language run times inside the Snowflake platform so it becomes a completely optimized experience. It dramatically expands the workload scope of Snowflake, so it's a very, very important direction for us.

所以 Snowpark 要做的是，我們將開始在 Snowflake 平台內託管語言運行時，使其成為一種完全優化的體驗。它極大地擴展了 Snowflake 的工作負載範圍，因此這對我們來說是一個非常非常重要的方向。

And you're correct in terms of how does this help. Our entire business model, as we've said over and over, is based on consumption. So anything that drives consumption of our query engine and our platform accrues to our business model. So our whole strategy is driven to move the dial on consumption. And this is definitely going to do it.

就這有何幫助而言，您是正確的。正如我們一再說過的，我們的整個商業模式都是基於消費。因此，任何推動我們查詢引擎和平台消費的因素都會影響我們的業務模型。因此，我們的整個戰略都是為了推動消費。這肯定會做到。

We have many large customers who said that this is really, really important to them because what Snowflake will bring to these environments is highly optimized efficiency in terms of the economics. Secondly, very, very highly optimized performance, and performance and efficiency are highly related. And the third one, super important, is governance, right? And this relates to privacy and security.

我們有許多大客戶表示，這對他們來說真的非常重要，因為 Snowflake 將為這些環境帶來的是在經濟方面高度優化的效率。其次，非常非常高度優化的性能，性能和效率高度相關。第三個非常重要的是治理，對嗎？這涉及隱私和安全。

So for customers, they really want to lock down their environment from a governance standpoint with a single platform. So to the extent that we can enable these workloads, we're real -- and consolidating these workloads onto Snowflake, that's really helping them.

因此，對於客戶而言，他們真的希望從單一平台的治理角度鎖定他們的環境。因此，就我們能夠啟用這些工作負載而言，我們是真實的——並將這些工作負載整合到 Snowflake 上，這確實對他們有幫助。

Got it. And maybe if I could sneak in one follow-up. In terms of the partnerships that you guys have been signing, any ones in particular that have been ramping up more aggressively than others or maybe helping you guys with the new customer acquisition and moving upmarket that we should be keeping an eye on?

知道了。也許我可以偷偷跟進一次。就你們簽署的合作夥伴關係而言，有沒有比其他合作夥伴更積極地發展或者可能幫助你們獲得新客戶和向高端市場轉移的合作夥伴關係，我們應該關注這些合作夥伴關係？

Well, the #1 partner that has helped stimulate tons of activity has been the relationship with Salesforce. And we knew that was going to happen because the Salesforce data is incredibly prominent in the Snowflake world because that data typically gets overlaid with all kinds of different types of marketing data. Salesforce is not an island. And I think that's one of the reasons why our relationship with Salesforce evolved so productively because they understood that the data gets blended and overlaid with data coming from other sources, and that really then translates into new insight, new signals that help drive the business. So Salesforce has driven a lot of new looks and new interest in our combined offerings.

好吧，幫助刺激大量活動的排名第一的合作夥伴是與 Salesforce 的關係。我們知道這會發生，因為 Salesforce 數據在 Snowflake 世界中非常突出，因為該數據通常會與各種不同類型的營銷數據重疊。 Salesforce 不是一座孤島。我認為這就是我們與 Salesforce 的關係發展如此富有成效的原因之一，因為他們了解數據會與來自其他來源的數據混合和疊加，然後真正轉化為有助於推動業務發展的新洞察力和新信號。因此，Salesforce 為我們的組合產品帶來了很多新面貌和新興趣。

Your next question comes from the line of Brad Reback from Stifel.

您的下一個問題來自 Stifel 的 Brad Reback。

Great. Mike, your comment earlier around less discounting, how much of that is a function of better execution in the field by the sales force versus customers just being much more comfortable migrating to the cloud and you being able to take advantage of that?

偉大的。邁克，你之前關於減少折扣的評論，其中有多少是銷售人員在現場更好執行的功能，而客戶只是更願意遷移到雲並且你能夠利用它？

I would say a lot of it is our better discipline in our sales force, but then also given the reference customers we have and what customers are seeing, they're more willing to move to Snowflake as well too, which makes the procurement process easier.

我想說的是，這在很大程度上是因為我們在銷售團隊中有更好的紀律，但考慮到我們擁有的參考客戶和客戶所看到的，他們也更願意轉向 Snowflake，這使得採購過程更加容易.

But what I will also tell you today, the product we're delivering today is so much better than what it was 3 years ago or 2 years ago, continues, and it becomes more -- the performance on it every year gets better and better. And as a result, customers should pay more for it.

但我今天還要告訴你的是，我們今天提供的產品比 3 年前或 2 年前的產品要好得多，而且還在繼續，而且它變得更多——它的性能每年都變得越來越好.結果，客戶應該為此支付更多費用。

[Customer statement.]

[客戶聲明。]

Yes, correct.

是，對的。

Your next question comes from Mark Murphy from JPMorgan.

你的下一個問題來自摩根大通的馬克墨菲。

I'll add my congrats. Frank, where do you think we are in the cycle of COVID impacts, specifically on the new logo bookings piece? I think Chris Degnan had said recently that customers that were hesitant to start their cloud journey are moving faster now. And so it looks like a bit better quarter for your customer adds. Are you feeling that incremental improvement in the new logo bookings kind of relative to where that was in the March and April time frame?

我會加上我的祝賀。弗蘭克，您認為我們處於 COVID 影響週期的哪個階段，特別是在新徽標預訂方面？我認為 Chris Degnan 最近曾說過，對開始雲之旅猶豫不決的客戶現在正在加快步伐。因此，對於您的客戶來說，這似乎是一個更好的季度。您是否覺得新徽標預訂的增量改進與 3 月和 4 月的時間框架相比有所改善？

Yes. I think that the demand sentiment was stronger in this period than it was in the first half of the year. And COVID is definitely one aspect to it. I certainly think that our public market debut also added to sort of the general energy and notoriety, if you will. It just was -- became kind of a catalyst for a lot of people wanting to find out more and really take the relationship to the next level.

是的。我認為這段時期的需求情緒比上半年要強。 COVID 絕對是它的一個方面。我當然認為，如果您願意的話，我們在公開市場的首次亮相也增加了一般能量和聲名狼藉。它只是 - 成為許多想要了解更多信息並真正將這種關係提升到一個新水平的人的催化劑。

So it was a tailwind in many ways, and that certainly was one of the reasons why we want to take the company public, is to really raise the stature of the company in the marketplace because we sell to the largest institutions, enterprises in the world, and we're also competing as the largest ones in the world also. So these things are important.

所以這在很多方面都是順風，這當然是我們想要讓公司上市的原因之一，是為了真正提高公司在市場上的地位，因為我們向世界上最大的機構和企業銷售產品，而且我們也在競爭世界上最大的公司。所以這些東西很重要。

As a quick follow-up, could you help us understand how aggressive your ambitions are going to be in the data science arena? You've touched on it a bit. But for building machine learning models and AI algorithms and also for handling log data or machine data, is there equal customer pull in both areas? Or is it stronger in one or the other?

作為快速跟進，您能否幫助我們了解您在數據科學領域的雄心壯志？你已經談到了一點。但是對於構建機器學習模型和 AI 算法以及處理日誌數據或機器數據，這兩個領域的客戶拉動是否相等？還是其中一個更強？

We do a ton of work in machine data and log data. I mean security data lakes is a growing use case that has a ton of interest. And we already have very, very large deployments of those. So that's an area that is very exciting.

我們在機器數據和日誌數據方面做了大量工作。我的意思是安全數據湖是一個不斷增長的用例，引起了人們的極大興趣。我們已經對這些進行了非常非常大的部署。所以這是一個非常令人興奮的領域。

As far as machine learning goes, what we are doing is we're really enabling ourselves architecturally to really accommodate machine learning services so that we can really take advantage of all the technology that is out there. What you're not going to see from Snowflake is that we're going to go buy something and then go it alone and sort of shut out our partners. I mean our architecture and our strategy is very much on embracing and enabling all the capabilities that are out there. Customers have tons and tons of choice. They can use ready-made services. They can use the tooling for building new services. And that is in contrast to some of the competitors that we have in the marketplace. So we have very specifically chosen for that path, but we're going to be super, super active in data science. Why? Because they are the ultimate consumer of the Snowflake cloud data platform.

就機器學習而言，我們正在做的是我們真正在架構上使自己能夠真正適應機器學習服務，這樣我們才能真正利用現有的所有技術。你不會從 Snowflake 看到的是，我們將去購買一些東西，然後單獨行動，並將我們的合作夥伴拒之門外。我的意思是我們的架構和我們的戰略非常注重擁抱和啟用所有現有的功能。客戶有無數的選擇。他們可以使用現成的服務。他們可以使用該工具來構建新服務。這與我們在市場上的一些競爭對手形成鮮明對比。因此，我們非常明確地選擇了這條道路，但我們將在數據科學領域非常非常活躍。為什麼？因為他們是雪花雲數據平台的最終消費者。

Your next question comes from the line of Patrick Walravens from JMP.

您的下一個問題來自 JMP 的 Patrick Walravens。

Great. And let me add my congratulations. So Frank, you mentioned at the beginning that you're very focused on moving upmarket. And I'm just wondering if you could provide some more color on what that entails from an operational perspective for you guys?

偉大的。讓我表示祝賀。所以弗蘭克，你一開始就提到你非常專注於向高端市場發展。我只是想知道你們是否可以從運營的角度為你們提供更多關於這需要什麼的顏色？

Yes. So we talked about this quite a bit during the road show, but when we joined the company, Snowflake was mostly a sort of a commercial selling, high density, relatively small contracts with high volume and fast sales cycles, quick adoption, and the company really liked that model. But us coming in says, we just know that in order to win in markets, you have to knock down the biggest, most iconic logos in whatever city, state, country or region that you're in.

是的。所以我們在路演期間談了很多這個，但當我們加入公司時，Snowflake 主要是一種商業銷售，高密度，相對較小的合同，大批量和快速銷售週期，快速採用，公司真的很喜歡那個模型。但是我們進來說，我們只知道為了贏得市場，你必須在你所在的任何城市、州、國家或地區拆除最大、最具標誌性的標誌。

So we really have to pivot our organization, or I should say, enhance the organization to layer in a selling strategy and a sales motion that campaigns these very large institutions. And we went as far -- and we were a private company at the time, of course. We did open heart surgery on our sales organization, and we separated it between sales organization that campaigns the largest 250 accounts in the world and then sort of the rest of the large enterprises. And then we're segmented even more on the low end also. And that's because the type of salespeople that we have to hire, the type of legal contractual posture that we have, the security team that we have, the type of compensation plans that we need to have is all different when you're comparing these large accounts because they are long campaigns. They're very political. They're very challenging. It requires tons of senior management involvement.

因此，我們真的必須調整我們的組織，或者我應該說，加強組織，以在銷售策略和銷售活動中分層，以宣傳這些非常大的機構。我們做到了——當然，我們當時是一家私營公司。我們對我們的銷售組織進行了心臟直視手術，並將其分為在全球擁有最大 250 個客戶的銷售組織和其他大型企業之間。然後我們在低端也進行了更多細分。那是因為當你比較這些大型公司時，我們必須僱用的銷售人員類型、我們擁有的法律合同狀態類型、我們擁有的安全團隊以及我們需要的薪酬計劃類型都是不同的帳戶，因為它們是長期的活動。他們非常政治化。他們非常具有挑戰性。它需要大量高級管理人員的參與。

So we've been working on is now for well over a year. And as Mike pointed out in his prepared remarks, we made a ton of progress, and we expect to become very heavily weighted over time to sort of that part of our business. Because these large accounts, I mean, the amount of money that they will spend in these types of services is going to be much larger than anybody is currently really understanding because this is becoming so important, so core to how they do things.

所以我們一直致力於 is 現在一年多了。正如邁克在他準備好的發言中指出的那樣，我們取得了很大的進步，我們希望隨著時間的推移，我們的業務的這一部分會變得非常重要。因為這些大客戶，我的意思是，他們將在這些類型的服務上花費的金額將比任何人目前真正理解的要多得多，因為這變得如此重要，成為他們做事方式的核心。

So yes, it's a very important shift or evolution, whatever word you want to use, so that we are very aggressively oriented towards the largest companies and institutions in the world.

所以是的，這是一個非常重要的轉變或演變，無論你想用什麼詞，所以我們非常積極地面向世界上最大的公司和機構。

Your next question comes from the line of Tyler Radke from Citi.

你的下一個問題來自花旗銀行的 Tyler Radke。

And congratulations on the first quarter here. I wanted to ask you a little bit about the guidance for Q4. Obviously, you saw really strong RPO growth in Q3. And I'm curious if there were any factors that had perhaps a short-term negative impact on the Q4 revenue guidance. I know oftentimes, when you sign these big deals, customers through volume-based discounts, get effectively a lower consumption credit rate. So I'm wondering, I guess, if almost the RPO strength that you saw this quarter and the large commitments that were signed, if that had any type of negative impact on your expected growth rate for revenue in Q4?

祝賀第一季度。我想問你一些關於第四季度指南的問題。顯然，您在第三季度看到了非常強勁的 RPO 增長。我很好奇是否有任何因素可能對第四季度收入指引產生短期負面影響。我知道很多時候，當你簽署這些大交易時，客戶通過基於數量的折扣，有效地獲得較低的消費信用率。所以我想知道，如果您在本季度看到的 RPO 強度幾乎和簽署的大量承諾，是否對您在第四季度的預期收入增長率產生任何類型的負面影響？

No. You have to remember, a lot of that RPO are new deals that we were booking. And as I said before, it takes customers to -- we have a lot of big on-prem migrations that are going on. And until those ramp up, and it could take 6 months plus, you don't really see any revenue from that. And so most -- a lot of that won't flow through until next fiscal year.

不，你必須記住，很多 RPO 都是我們預訂的新交易。正如我之前所說，它需要客戶——我們有很多正在進行的大型本地遷移。在這些增加之前，可能需要 6 個月以上的時間，你真的看不到任何收入。所以大多數 - 其中很多要到下一個財政年度才會流出。

Got it. Helpful. And on data sharing, I think you talked about this pretty healthy mix of your customers that are using Snowflake for data sharing. I guess a couple of questions there. What are you seeing more at this point? Is it kind of the internal data-sharing use case? Or is it the external? I know you did talk about over 100 data providers. And then secondly, I mean, I know it's still early, but have you seen any turn -- any type of trends where once customers use data sharing, you see consumption rise by orders of magnitude? Or just help us think through how much that consumption potential is once customers move over to a data sharing use case?

知道了。有幫助。關於數據共享，我想你談到了使用 Snowflake 進行數據共享的客戶的這種非常健康的組合。我想那裡有幾個問題。你現在看到的更多是什麼？它是一種內部數據共享用例嗎？還是外在的？我知道您確實談到了 100 多家數據提供商。其次，我的意思是，我知道現在還早，但你有沒有看到任何轉變——任何類型的趨勢，一旦客戶使用數據共享，你就會看到消費量呈數量級增長？或者只是幫助我們思考一旦客戶轉向數據共享用例，消費潛力有多大？

This is Frank. The important thing to understand is that both gaining and providing data access to external sources or whether they are inside an institution or whether they're external is becoming a main part of data operations. Historically, it hasn't been -- we used file transfer protocols, APIs to move data from ADB. It was logistically incredibly hard. It was a very governance challenge. People did it because they had to, but they absolutely didn't like it.

這是弗蘭克。需要理解的重要一點是，獲取和提供對外部來源的數據訪問，或者它們是在機構內部還是外部，正在成為數據操作的主要部分。從歷史上看，它並沒有——我們使用文件傳輸協議、API 從 ADB 移動數據。這在邏輯上非常困難。這是一個非常治理的挑戰。人們這樣做是因為他們不得不這樣做，但他們絕對不喜歡它。

So here comes Snowflake, what a frictionless, seamless data sharing model, and all of a sudden, that's like, hey, we -- part of our data operations is that we both gain and provide access to, in the case of large financial institutions, they have hundreds and hundreds of data sets that they gain access to and provide access to. So data sharing is part of data operations. We're just, for the first time now, really providing an extremely strong model, operational model to be able to do that.

所以 Snowflake 來了，這是一個多麼無摩擦、無縫的數據共享模型，突然之間，就像，嘿，我們的數據操作的一部分是我們獲得併提供對大型金融機構的訪問權限，他們擁有成百上千的數據集，他們可以訪問並提供訪問權限。所以數據共享是數據運營的一部分。我們只是第一次真正提供了一個非常強大的模型，能夠做到這一點的運營模型。

And I know historically, people just didn't do as much of this because it was so damn hard. Now I will tell you that job 1 for most of our customers is, well, first, I got to get my data to the cloud. Then I got to do to database migrations, which is really the biggest part of the transition. This is just modernization.

而且我知道，從歷史上看，人們並沒有做那麼多，因為它太難了。現在我會告訴你，對於我們大多數客戶來說，第 1 項工作是，首先，我必須將我的數據傳輸到雲端。然後我要做數據庫遷移，這實際上是過渡中最重要的部分。這只是現代化。

And then we start thinking about transformations in terms of running processes that we've never run before, things that are now possible that couldn't be done before. And typically, data sharing and -- is sort of the frontier, if you will, of the new things that are now possible that people have never even considered before. I mean it was not even an option, and they were so preoccupied with just doing things in terms of blocking and tackling, that they had never gotten around to really fully examining and understanding what is now possible.

然後我們開始根據我們以前從未運行過的運行流程來考慮轉換，現在可以做以前無法完成的事情。通常情況下，數據共享和——如果你願意的話，是人們以前從未考慮過的現在可能出現的新事物的前沿。我的意思是，這甚至都不是一個選擇，他們太專注於僅僅在攔截和搶斷方面做事，以至於他們從來沒有抽出時間真正全面地檢查和理解現在可能發生的事情。

So it's usually -- data sharing is really not the first part of the conversation. It's something that sort of evolves over time. And what we are seeing, though, is that we're now getting into deals, deals where people already have strong incumbents on the cloud relative to existing workloads. And the data cloud and our data sharing capabilities are busting open accounts where normally on a workload basis, we would not really have that much opportunity or the customer incentive to even look at us. So the Salesforce loves that about it. It's a conversation where we're hitting 1,000, okay, that just never fails to trigger new interest. So we like it for all of those reasons.

所以通常 - 數據共享真的不是對話的第一部分。這是隨著時間的推移而演變的東西。不過，我們所看到的是，我們現在正在進行交易，交易中人們已經在雲上擁有相對於現有工作負載的強大現任者。數據云和我們的數據共享能力正在破壞通常基於工作負載的開放賬戶，我們真的沒有那麼多機會或客戶動機甚至看我們。所以 Salesforce 喜歡它。這是一個我們達到 1,000 的對話，好吧，它永遠不會引發新的興趣。因此，出於所有這些原因，我們喜歡它。

Your next question comes from the line of Ittai Kidron from Oppenheimer & Co.

您的下一個問題來自 Oppenheimer & Co. 的 Ittai Kidron。

Again, congrats on the first great quarter out of the gate. A couple of questions for me. Maybe one for you first, Frank. I want to go back to the machine learning comments you made earlier. I just want to make sure I understand this and get this right. Do you intend or not intend on moving into the machine learning algorithm space like Databricks or DataRobot? I want to make sure I understand your interaction with machine learning. Are you going to be an enabler? Or are you actually going to provide a full stack platform for machine learning?

再次祝賀第一個偉大的季度走出大門。問我幾個問題。也許先給你一個，弗蘭克。我想回到你之前發表的機器學習評論。我只是想確保我理解這一點並且做對了。您是否打算進入 Databricks 或 DataRobot 等機器學習算法領域？我想確保我了解您與機器學習的互動。你要成為推動者嗎？或者你們真的要為機器學習提供一個全棧平台嗎？

Well, we're going to do both. I mean what I did say was, like, we don't just sort of want to go to the marketplace and say, you're going to have to use ours, and that's it. There's enough people that operate in that mode. So we're going to have a much richer, wider, broader set of choices for customers. Certainly, one of -- my comments about Snowpark, I mean, considering that we're going to have Java, Python language run times in our platform, that's going to be a key enabler for people to develop these kind of capabilities and use the kind of capabilities that they're already using today. So to really bring those workloads that are already -- that already exist or that are being newly developed, to bring that inside the Snowflake platform.

好吧，我們將兩者都做。我的意思是我的意思是，就像，我們不只是想去市場說，你將不得不使用我們的，僅此而已。有足夠多的人在這種模式下運作。因此，我們將為客戶提供更豐富、更廣泛、更廣泛的選擇。當然，我對 Snowpark 的評論之一，我的意思是，考慮到我們將在我們的平台中使用 Java、Python 語言運行時，這將成為人們開發此類功能並使用他們今天已經在使用的一種功能。因此，要真正將那些已經存在或正在新開發的工作負載帶入 Snowflake 平台。

So we're not going to be a company where we have our own flavor of everything and our partners are all going to be secondary. We want to actively encourage development on our platform, participation on our platform because, again, we're a consumption company. So the way we drive our strategy is to drive activity on our platform, right? I mean if we get activity on our platform, whether our product drives it or a partner drives it, it yields the same result, right? So we'd be crazy to -- because the way our model works, we don't have to prioritize our own products.

因此，我們不會成為一家對所有事情都有自己的看法而我們的合作夥伴都將處於次要地位的公司。我們希望積極鼓勵在我們平台上的發展，在我們平台上的參與，因為我們是一家消費公司。所以我們推動戰略的方式是推動我們平台上的活動，對嗎？我的意思是，如果我們在我們的平台上獲得活動，無論是我們的產品驅動它還是合作夥伴驅動它，它都會產生相同的結果，對嗎？所以我們會很瘋狂——因為我們的模型運作的方式，我們不必優先考慮我們自己的產品。

Got it. And maybe flipping into the other side of the chain then. Clearly, your economics get much better and better the more and more data resides on your platform. And so moving data into your platform is absolutely critical for you. How do you think about the data integration layer, which is highly fragmented and has multiple layers to it? How far down the data integration side do you want to move in order to enable better and faster and smoother movement of data into your platform?

知道了。然後可能會跳到鏈條的另一端。顯然，隨著越來越多的數據駐留在您的平台上，您的經濟效益會越來越好。因此，將數據移至您的平台對您來說絕對至關重要。您如何看待高度分散且具有多層的數據集成層？為了更好、更快、更順暢地將數據移動到您的平台中，您希望將數據集成端向下移動多遠？

Well, this -- the data engineering side of our business is already a huge part of what drives the consumption on our platform. And we're -- everything that we're doing with Snowpark is obviously focused on that as well because so much of that work is going to be data transformation-oriented. So no, it's a huge thing.

嗯，這 - 我們業務的數據工程方面已經是推動我們平台消費的重要組成部分。而且我們 - 我們與 Snowpark 所做的一切顯然也專注於此，因為其中大部分工作將以數據轉換為導向。所以不，這是一件大事。

But we're going to do things that are Snowflake optimized, right? The sort of processes that run all the way from ingestion, transformation, bringing data on the platform, running analytical process to make that as seamless and as frictionless as possible. And our partners in the ecosystem, they serve many masters. We only serve one, and that's Snowflake.

但是我們要做的事情是 Snowflake 優化的，對吧？從攝取、轉換、將數據帶到平台、運行分析過程以使其盡可能無縫和無摩擦的過程。而我們在生態系統中的合作夥伴，他們服務於眾多的高手。我們只提供一個，那就是雪花。

Your next question comes from the line of Gregg Moskowitz from Mizuho.

你的下一個問題來自 Mizuho 的 Gregg Moskowitz。

Okay. And I'll add my congratulations as well. I wanted to go back, if I could, to the topic of bringing unstructured data into the Snowflake platform. Frank, as you mentioned, Snowflake began its life as a semi-structured data company. And I'm curious how much of a technical challenge it is or has been for you to support and to transact on images, videos, PDFs, et cetera, and to do so at scale.

好的。我還要表示祝賀。如果可以的話，我想回到將非結構化數據引入 Snowflake 平台的話題。弗蘭克，正如你提到的，Snowflake 最初是一家半結構化數據公司。而且我很好奇，支持和處理圖像、視頻、PDF 等，以及大規模地進行這些操作，對您來說是或曾經面臨的技術挑戰有多大。

Well, it obviously is not a no-brainer. Otherwise, we probably would have done it a long time ago. But we -- our technical teams are now heavily invested in making this happen. I mean our announcement was very much the very first time we've talked about this openly. I expect that in our next Snowflake summit event, which is in June of next year, we will have extensive technical details and presentations on this topic. So we'll be communicating on this topic in full detail at that time. We're certainly not prepared or ready to do that right now.

好吧，這顯然不是一件容易的事。否則，我們可能早就這麼做了。但是我們 - 我們的技術團隊現在正在大力投資以實現這一目標。我的意思是我們的公告是我們第一次公開談論這個。我希望在明年 6 月舉行的下一次 Snowflake 峰會活動中，我們將提供有關該主題的廣泛技術細節和演示。因此，屆時我們將就此主題進行詳細溝通。我們現在當然還沒有準備好或準備這樣做。

Look forward to that. And then just as a follow-up, so 23% of customers already using data sharing, really impressive for a service that, frankly, hasn't been available all that long. How does this uptake compare to what your expectations were at this stage? And then also where can this go longer term?

期待那個。然後作為後續行動，23% 的客戶已經在使用數據共享，坦率地說，對於一項服務來說，這確實令人印象深刻，但一直以來都沒有提供。與您現階段的預期相比，這種吸收情況如何？從長遠來看，這還能在哪裡發展？

Yes. I think longer term, I mean we -- I think everybody is going to be doing this. As I said earlier, this is going to become core to data operations. This is -- the whole notion of a data cloud is you're not just running data sciences against your own data silos. You're going to be running it across disparate data sets, meaning data that lives inside your world, outside of your world. That's really what data science is all about, is to build these highly descriptive models that can then be used predictably and prescriptively to really get closer to business outcomes.

是的。我認為從長遠來看，我的意思是我們 - 我認為每個人都會這樣做。正如我之前所說，這將成為數據運營的核心。這是——數據云的整個概念是，你不僅僅是在針對自己的數據孤島運行數據科學。你將在不同的數據集上運行它，這意味著數據存在於你的世界之內，你的世界之外。這就是數據科學的真正意義所在，就是構建這些高度描述性的模型，然後可以以可預測和規範的方式使用這些模型，以真正接近業務成果。

So in order for the data cloud to really happen as a concept, this is going to become incredibly mainstream. That is our general strategic assumption about data. It is not going to stay where it has been historically because we were essentially encumbered by technology, and we're not anymore. It's wide open.

因此，為了讓數據云真正成為一個概念，這將成為令人難以置信的主流。這是我們對數據的一般戰略假設。它不會停留在歷史上的位置，因為我們基本上受到技術的阻礙，而我們不再是了。它是敞開的。

So I think customers are learning and slowly sort of gaining an appreciation of what all the new possibilities are. I mean I said in my prepared remarks, technology is now well ahead of people's ability to use it, right? And people are scratching their heads like, wow, this is just unbelievable, the scale, the scope, the power that we have. How do we use it? And that's sort of where we are. Really exciting, but nobody sort of has the playbook ready to throw at it. So it's a bit of a journey that we're on, everybody will be on.

所以我認為客戶正在學習並慢慢了解所有新的可能性。我的意思是我在準備好的發言中說過，技術現在已經遠遠超過了人們使用它的能力，對嗎？人們撓頭說，哇，這簡直令人難以置信，我們擁有的規模、範圍和力量。我們如何使用它？這就是我們所處的位置。真的很令人興奮，但沒有人準備好投入其中。所以這是一段我們正在進行的旅程，每個人都會繼續。

Your next question comes from the line of Derrick Wood from Cowen & Company.

你的下一個問題來自 Cowen & Company 的 Derrick Wood。

Great. And congrats on a strong quarter. My first question, I wanted to ask about a couple of different regions. First, on Europe. I think you guys have been building out a major accounts focus there. I would love to hear about how that's tracking versus kind of what you've been experiencing in the U.S. And then in the U.S. regarding the Fed, I think you guys have received some new FedRAMP certifications this year. Can you just talk about how you're thinking about the opportunity with the government looking out over the next couple of years?

偉大的。並祝賀一個強勁的季度。我的第一個問題，我想問幾個不同的地區。首先，關於歐洲。我認為你們一直在那裡建立一個主要的客戶重點。我很想听聽這是如何跟踪與你們在美國經歷過的事情的對比。然後在美國，關於美聯儲，我想你們今年已經獲得了一些新的 FedRAMP 認證。你能談談你是如何考慮政府在未來幾年展望的機會嗎？

Yes. We're -- we had a really good quarter in Europe. I was very excited about that. Europe was definitely a region where we had to sort of rerack ourselves in terms of our large account orientation. I mean Europe is even more sensitive to major account campaigning because that's sort of how these markets operate. They really look to their own iconic enterprises to see what kind of decisions they make, and then the whole market kind of follow. So you simply cannot afford to be in those markets and not campaign those large enterprises.

是的。我們 - 我們在歐洲有一個非常好的季度。我對此感到非常興奮。歐洲絕對是一個我們必須在大客戶定位方面重新調整自己的地區。我的意思是歐洲對大客戶競選活動更加敏感，因為這就是這些市場的運作方式。他們真的在關注自己的標誌性企業，看看他們做出了什麼樣的決定，然後整個市場都會效仿。所以你根本不能進入那些市場而不去競選那些大企業。

So it's a fairly substantial sort of reboot for us to be able to have that posture, but we're seeing it pay off. And I have very high expectations and high hope for Europe. And we're going to be spending time there when we can travel again to help campaign those institutions, a very, very good opportunity.

因此，對於我們來說，能夠擁有這種姿態是一種相當重要的重啟，但我們看到它得到了回報。我對歐洲抱有很高的期望和希望。當我們可以再次旅行以幫助宣傳這些機構時，我們將在那裡度過一段時間，這是一個非常非常好的機會。

As far as the Fed goes, the hard part about federal government is always getting them on the cloud. They just have historically been incredibly slow to move to the cloud for all kinds of reasons. So the FedRAMP certifications that -- we have achieved some certifications that are helping. We need higher level of certifications to really enable that business further. And that is really sort of the gating factor, if you will, for the Fed really becoming a solid contributor to the business, which they're not yet.

就美聯儲而言，聯邦政府最困難的部分總是讓他們上雲。由於各種原因，從歷史上看，他們遷移到雲端的速度非常慢。因此，FedRAMP 認證——我們已經獲得了一些有幫助的認證。我們需要更高級別的認證才能真正使該業務進一步發展。如果你願意的話，這確實是一種門控因素，因為美聯儲真的成為了企業的堅實貢獻者，但他們還沒有。

Got it. And then maybe one for Mike. You had a nice rebound in net revenue retention rates, but it has bumped around a bunch over the last few quarters. So can you just walk us through the mechanical drivers in terms of what you've seen in the last couple of quarters and maybe how to think about how you see those numbers settling out over the next couple of quarters?

知道了。然後也許是給邁克的。您的淨收入保留率出現了不錯的反彈，但在過去幾個季度中出現了大幅波動。那麼，您能否根據您在過去幾個季度所看到的情況，向我們介紹機械驅動因素，以及如何考慮您如何看待這些數字在接下來的幾個季度內穩定下來？

Well, when we were going public, we had mentioned that we fully expect it would be above 160% this quarter. So it kind of came into where we were expecting. These are extremely high net revenue retention rates. I think over time, it will come down, but I'm not expecting a steep decline. And I think it's going to be pretty stable for the next little while. It's not something we're going to be guiding to. I just knew after last quarter that this quarter was going to go higher because it was a cohort that had just come in from the 2 year ago period that it was just the nature of some of those customers.

好吧，當我們上市時，我們曾提到我們完全預計本季度將超過 160%。所以它有點進入我們期待的地方。這些是極高的淨收入保留率。我認為隨著時間的推移，它會下降，但我預計不會急劇下降。而且我認為在接下來的一段時間內它會非常穩定。這不是我們要指導的事情。我只是在上個季度之後才知道這個季度會更高，因為這是 2 年前剛剛進入的人群，這只是其中一些客戶的性質。

Your next question comes from the line of Gray Powell from BTIG.

你的下一個問題來自 BTIG 的 Gray Powell。

Great. And yes, I'll echo my congratulations on the results. So maybe a couple of questions for Mike. As you look at your growth forecast over the next 12 months, how much of it do you feel like you have visibility on from the installed base today, the customers you just won in natural growth in usage? And then how much do you think you have to go out and win?

偉大的。是的，我將對結果表示祝賀。所以也許有幾個問題要問邁克。當您審視未來 12 個月的增長預測時，您認為今天的安裝基礎有多少，您剛剛贏得的使用自然增長的客戶有多少？然後你認為你必須出去贏多少錢？

First of all, going into a quarter, virtually all of our revenue is coming from our existing customers. Very little comes from customers that are landed in the quarter, and it's less than 5% come from on-demand customers. Over the next 12 months, it's still the vast majority of our revenue is coming from our existing customers that we have. And we do see the growth in those customers. Sure, we need to sell them more, but most of our growth is coming from our existing customers over the next 12 months. Longer term, it's super important that we acquire new customers because those will be the growth drivers in 2, 3 years or so.

首先，進入一個季度，我們幾乎所有的收入都來自我們現有的客戶。很少有來自本季度登陸的客戶，只有不到 5% 來自按需客戶。在接下來的 12 個月裡，我們的絕大部分收入仍然來自我們現有的客戶。我們確實看到了這些客戶的增長。當然，我們需要賣得更多，但我們的大部分增長都來自未來 12 個月的現有客戶。從長遠來看，我們獲得新客戶非常重要，因為這些將成為 2、3 年左右的增長動力。

Got it. Okay. And I just want to make sure I'm thinking about the Q4 guidance correctly. So if I just look at the last 2 quarters, product revenue increased by about $23 million sequentially in both Q2 and Q3. I would think that usage is seasonally stronger in Q4. So is there any reason why product revenue would only grow by $16 million sequentially in the quarter? How should I -- how should we think through that?

知道了。好的。我只是想確保我正確地考慮了 Q4 指南。因此，如果我只看過去兩個季度，第二季度和第三季度的產品收入環比增長了約 2300 萬美元。我認為第四季度的使用量季節性更強。那麼，為什麼產品收入在本季度環比僅增長 1600 萬美元，有什麼原因嗎？我應該如何 - 我們應該如何思考？

It all depends upon the type of customer you are and depending upon what you're doing. There's also a number of our large customers that we've given that are getting more mature right now, too, and their growth has slowed down somewhat with some of these large customers. But there is seasonality within our customer base. And I would not assume Q4 is what's driving their consumption at all. Quite frankly, in Q4, there's a lot of holidays. You have Thanksgiving, you have Christmas, and you do see decrease in the New Year. You do see decreases because employees aren't in the office driving analytics.

這完全取決於您的客戶類型以及您在做什麼。我們還提供了一些大客戶，他們現在也變得更加成熟，其中一些大客戶的增長有所放緩。但我們的客戶群存在季節性。而且我不認為第四季度是推動他們消費的因素。坦率地說，在第四季度，有很多假期。你有感恩節，你有聖誕節，你確實看到新年有所減少。你確實看到了減少，因為員工不在辦公室駕駛分析。

Your next question comes from the line of David Hynes from Canaccord.

您的下一個問題來自 Canaccord 的 David Hynes。

I want to ask a follow-up on the strong net revenue expansion. Frank, when you talk to CIOs at some of your larger customers, I'm curious if you pick up any concern about the pace at which their Snowflake spend is growing? Or is it still that there's such price disparity versus the incumbents that it's not an issue? I'm curious kind of how you think about balancing that in a consumption-based model.

我想問一下強勁的淨收入擴張的後續情況。弗蘭克，當你與一些大客戶的首席信息官交談時，我很好奇你是否對他們的 Snowflake 支出增長速度感到擔憂？還是與現有企業相比仍然存在價格差異，這不是問題？我很好奇您如何考慮在基於消費的模型中平衡它。

So here's the important thing, I already mentioned it a little bit earlier. So Snowflake is a variable paradigm, right? In other words, this is not fixed. People can consume as much and as little as they have appetite and budget for, which is why you have this buoyancy in net revenue retention rate because people -- because they now can. They start doing things that they could not do before.

所以這是重要的事情，我之前已經提到過。所以 Snowflake 是一個可變範式，對吧？換句話說，這不是固定的。人們可以根據他們的胃口和預算消費多少，這就是為什麼你的淨收入保留率有這種浮力，因為人們 - 因為他們現在可以。他們開始做以前做不到的事情。

The big thing -- and by the way, it's not CIOs that are upset. It's usually CFOs that are -- they can't understand how you go from one period to the next and all of a sudden the number has doubled. But the business is telling them, no, we need to do this. So people are getting used to spending way more money on this class of service than they ever imagined. And the reason is they now can and they now need to, right?

重要的是——順便說一下，感到沮喪的不是 CIO。通常是首席財務官——他們無法理解你是如何從一個時期過渡到下一個時期的，突然間這個數字翻了一番。但企業告訴他們，不，我們需要這樣做。因此，人們習慣於在此類服務上花費比他們想像的更多的錢。原因是他們現在可以而且現在需要，對吧？

Now does that take time? Yes, it takes time for people to get used to that. I mean I've talked to CTOs. They said, we spent $50,000 last year. We're spending $1 million this year. How the hell do I explain that? Well, that is -- those are the types of transitions that we're going through. We have customers where we are the second largest line item behind Amazon, AWS, right? Well, that's what we're getting used to for a customer that you're spending on a service like this at this rate.

現在這需要時間嗎？是的，人們需要時間來適應這一點。我的意思是我已經和 CTO 談過了。他們說，我們去年花了 50,000 美元。今年我們要花費 100 萬美元。我他媽的怎麼解釋呢？嗯，那就是——這些是我們正在經歷的過渡類型。我們有客戶，我們是僅次於亞馬遜、AWS 的第二大訂單，對吧？好吧，這就是我們習慣於以這種速度在這樣的服務上花費的客戶。

But when data becomes the beating heart of your enterprise, that -- it makes total sense. It's just that it doesn't make sense in a historical context. And it takes time for us to transition to this realization, like this is pretty damn important. And that's sort of -- sometimes it goes a little bit too quick. And people are like, holy moly, this thing is a little bit too slick and too fast, and it's just too easy to fire up a cluster or a warehouse. And instead of running this process once a week, we're now running it every night because they see advantage in doing it, right?

但是，當數據成為您企業的心臟時，那-它就完全有意義了。只是在歷史背景下它沒有意義。我們需要時間才能過渡到這種認識，因為這非常重要。這有點 - 有時它有點太快了。人們就像，天哪，這東西有點太圓滑太快了，而且很容易啟動一個集群或一個倉庫。而不是每週運行一次這個過程，我們現在每晚都運行它，因為他們看到這樣做的好處，對吧？

But we're seeing people getting used to large numbers. I mean I'm -- quite honestly, in my own history in software, I'm just stunned by the size of the relationships that we're seeing in this business, and it's an amazing thing. But it does take time for people to really transition to the realization that this is going to have a big economic footprint.

但我們看到人們已經習慣了大數字。我的意思是，老實說，在我自己的軟件歷史中，我對我們在這個行業中看到的關係的規模感到震驚，這是一件了不起的事情。但人們確實需要時間才能真正過渡到意識到這將產生巨大的經濟影響。

Yes, yes, makes sense. Obviously, good problems to have. Maybe one quick follow-up, if I could. We've talked about the network effects that come from the data exchange. In the near term, what's more important on that front in your view? Is it getting more customers to participate? Or is it getting more data providers on the network?

是的，是的，有道理。顯然，有好的問題。如果可以的話，也許可以進行一次快速跟進。我們已經討論了來自數據交換的網絡效應。在您看來，近期在這方面什麼更重要？是否有更多的客戶參與？還是網絡上有更多的數據提供者？

Yes. I don't know that we need to trade those off, quite honestly. We can walk and chew gum, if you will. So we're operating on both those vectors at the same time. In terms of data providers, it -- sometimes it's more of a qualitative than a quantitative thing because they're not all created equal. So some of those -- and by the way, it's very vertically oriented in the types of data that we're dealing with. So it's a fairly nuanced thing. It's very important for us that we enrich the data cloud with new data all the time because there's going to be more and more customers who -- the reason to be on Snowflake is not just the world-class execution capabilities that we have, but they need to be there because their partners are there, their data providers are there. That, after a while, starts to break the bow because it becomes a no-brainer. But we have to have both. If you don't have the workload execution capabilities, the data richness will not save you. You need to have both.

是的。老實說，我不知道我們需要權衡這些。如果你願意，我們可以邊走邊嚼口香糖。所以我們同時對這兩個向量進行操作。就數據提供者而言，它 - 有時它更多的是定性而不是定量的東西，因為它們並非都是平等的。所以其中一些 - 順便說一下，它在我們正在處理的數據類型中非常垂直。所以這是一個相當微妙的事情。對我們來說非常重要的是，我們一直用新數據豐富數據云，因為會有越來越多的客戶——使用 Snowflake 的原因不僅是我們擁有的世界級執行能力，而且他們需要在那裡，因為他們的合作夥伴在那裡，他們的數據提供者在那裡。那，過了一會兒，開始打破弓，因為它變得不費吹灰之力。但我們必須兩者兼得。如果你沒有工作負載執行能力，數據豐富也救不了你。你需要兩者兼得。

Your last question comes from the line of Brent Thill from Jefferies.

你的最後一個問題來自 Jefferies 的 Brent Thill。

Just on the go-to-market as we go into next year in terms of your quota-carrying sales capacity and your build-out. How are you thinking about what you're adding to the system? Are you accelerating the build-out here, given what you're seeing with the economy starting to stabilize a little bit? Or are you -- just maybe walk us through your thoughts on how you're thinking through the shape of that go-to-market?

就你們的配額銷售能力和擴建而言，就在我們進入明年的時候進入市場。您如何考慮要添加到系統中的內容？鑑於您看到的經濟開始穩定一點，您是否正在加速這裡的擴建？或者你是——也許只是讓我們了解你是如何思考進入市場的形式的？

Well, what I would say is we're very much focused. I'll first talk geography. EMEA is one that we're investing very heavily in and adding a fair number of people there as a percent of what they have. We're clearly focused on going after the largest enterprises in the world, and so we are continuing to add reps there.

好吧，我想說的是我們非常專注。我先說地理。 EMEA 是一個我們正在大力投資的地區，並在那裡增加了相當數量的人員，佔他們所擁有的百分比。我們顯然專注於追求世界上最大的企業，因此我們將繼續在那裡增加代表。

I would say we really never slowed down given what was happening in the economy. You can see that year-over-year and Q3 of 2020, we had 900 people in our sales organization, and we've added roughly almost 300 people into our sales organization over that period of time, of year. And we will continue to add at that similar pace going forward next year.

我想說，鑑於經濟中正在發生的事情，我們真的從未放慢腳步。您可以看到，與去年同期和 2020 年第三季度相比，我們的銷售組織中有 900 名員工，並且在這一年的這段時間裡，我們的銷售組織中增加了大約近 300 人。明年我們將繼續以類似的速度增加。

I would say the other area we're really adding as we get more into the major accounts, we're adding a lot more SEs into our organization because majors require more one-to-one relationship, where in the past, we never did. So I would say is we are really going after those larger accounts and enterprise more so than SMB.

我想說的是，隨著我們越來越多地進入主要客戶，我們真正添加的另一個領域是，我們正在向我們的組織中添加更多的 SE，因為專業需要更多的一對一關係，而在過去，我們從未這樣做過.所以我想說的是，我們真的比 SMB 更關注那些更大的客戶和企業。

Yes. The only thing I will add to that is that we're also on a massive push to drive verticalization end-to-end in our selling motions. And that means that quota is going to be overlaid and added by vertical as well. So you see our capacity to sell will grow. And it's really nice that we have it geographically, we have it by large enterprise accounts, and we're going to have it by vertical.

是的。我唯一要補充的是，我們也在大力推動銷售活動中端到端的垂直化。這意味著配額也將被垂直覆蓋和添加。所以你看到我們的銷售能力將會增長。我們在地理上擁有它真是太好了，我們通過大型企業客戶擁有它，並且我們將通過垂直方式擁有它。

So we're very excited about the company verticalizing. We're -- because we're having great business on the technology side and the media side, retail, consumer packaged goods, health care. So that's where a lot of our selling capacity is going to grow in the coming years.

所以我們對公司的垂直化感到非常興奮。我們是——因為我們在技術方面和媒體方面、零售、消費品、醫療保健方面都有很好的業務。因此，這就是未來幾年我們的許多銷售能力將增長的地方。

And I'll add, Brent, too, that we've really been focused in the last 12 months on the system integrators. The global system integrators, we're adding more people there, the likes of Deloitte and Accenture, building real practices around Snowflake. And we're going to continue to invest in those because they are starting to drive meaningful business to us.

我還要補充一點，布倫特，在過去的 12 個月裡，我們確實一直專注於系統集成商。全球系統集成商，我們正在那裡增加更多的人，比如德勤和埃森哲，圍繞 Snowflake 建立真正的實踐。我們將繼續投資於這些，因為它們開始為我們帶來有意義的業務。

And that was our last question. Ladies and gentlemen, this concludes today's conference call. Thank you for participating. You may now disconnect.

這是我們的最後一個問題。女士們，先生們，今天的電話會議到此結束。感謝您的參與。您現在可以斷開連接。