Mike, on your comment on these large customers in Q4 exhausting their commitments but not necessarily renewing going on demand, how usual or unusual is that? And do you expect these customers just to sign a commitment contract in due course?

Yeah, I fully expect they're going to sign a new commitment. We typically sign a three-year contract with our customers once they're up and running. Many new customers start at one year the first year, then go to three years. If they burn through that commitment before the end of the contract term, the customer has two options. They can either do an early renewal or continue to purchase under the same terms until the end of their contract period, at which time they must make a new capacity purchase. This has always happened, and I expect them to sign new contracts within the next month to six months.

Sridhar, can you give us some color on the adoption trends within the data engineering portfolio, ensuring one bucket? And then looking at the AI ML application platform side with some of the announcements supporting both open AI models and anthropic models, when do you think that starts to unlock more workloads, more customer adoption, and ultimately a greater revenue as we look to the balance of this year?

In areas like data engineering, we've been working on technologies like Snowpark, which has already driven robust adoption. We’re also expanding by making investments in companies like DataVolo, bringing in more data through large-scale connectors. We are seeing brisk adoption, especially in building complicated pipelines. AI, however, is a newer set of products. We are seeing broad adoption and expect it to turn into real revenue over the coming quarters. Our ability to handle larger datasets and integrate them smoothly with AI models is key to driving customer adoption and increasing workloads.

Mike, can you talk more about the trends you're seeing with your largest customers, maybe the momentum and expansion rates, and the services that they're embracing and plan to consume this year?

Large customers continue to grow and consume. While some overachieve and others underperform our forecast, there is no unusual pattern. The momentum is strong, especially among the million-dollar-plus customers. We are also identifying new workload opportunities and improving our sales organization’s ability to migrate customers and handle their needs. I’m very pleased with our professional services team and our partners as they help drive new workloads.

Sridhar, as you think about growth levers to the business, one area you flagged was this idea of Snowflake's role in AI-powered advertising. Can you just double-click into when you think about the AI-powered ad market, is there an unlock that you see there for Snowflake in that kind of new workload scenario?

We have been in the marketing and advertising area for a long time, especially with CDPs built on Snowflake. With advancements like AI SQL, we can now do things like image analysis and video analysis through simple SQL queries. This is a critical area for Snowflake, and with the introduction of multimodal capabilities in Cortex, we expect to see more generative applications that can power more automated testing and creative generation, especially in the ad space.

Sridhar, can you talk a little bit more about what differentiates your Cortex Agents offering versus many other agent offerings out there and maybe where the product vision came from? Was this something customers were asking for? And are there any early adopters you’re working with?

What differentiates Cortex Agents is the centrality of data. We are a horizontal platform, and customers can store various kinds of data with us, making it possible to create interesting new applications. We are leveraging structured and unstructured data, combining them in a way that others cannot. It’s too early for me to share specifics about customers, but even internally at Snowflake, we’ve seen how this can be applied to different use cases, like updating meeting data or enhancing product management. It’s about bringing data together seamlessly and scaling effectively.

Mike, how conservative are the assumptions this year in the guidance versus what you did last year when you had the CEO change? How did the economy also play into the guidance for this year?

The guidance we’ve set is appropriate. We’ve always tried to give meaningful guidance, and given the scale we’re at, we think a 3% beat should be considered a big beat. The guidance takes into account the current economic environment and customer trends, including migrations that are looking very good for the second half of the year. Although Q1 may seem low due to the leap year, we’re confident in the revenue forecast for the year.

Sridhar, how do you think about adjacencies for your offering that you might want to consider, like streaming? Can you talk about how you see the product evolving?

We are focusing on ensuring we have a strong offering in both streaming and data ingestion. Streaming, in particular, comes in many different shapes and sizes, both on-prem and cloud-native solutions. We see streaming as a critical area for Snowflake, as well as Snowflake Intelligence, which blends BI and new applications. These are all areas where we think it’s important to have a presence, and we continue to partner with other technologies to fill in the gaps where necessary.

Mike, can you give some more insight on how you think the partnership with Microsoft and OpenAI will impact Snowflake and potentially what it could mean from a revenue standpoint in the future?

The partnership with Microsoft and OpenAI is a big deal for us. It makes OpenAI’s models accessible within Snowflake’s security perimeter, providing customers with greater flexibility. While it's too early to quantify the revenue impact, we believe it will bring significant upside once we see traction with customers. It opens up new possibilities for us and our customers in building world-class applications without requiring data to go anywhere else.

Snowflake 雪花 SNOW 2024年第4季度電話會議記錄問 Ai

會議亮點

- ? Q4產品收入達943億港元，按年增長28%
- ? **未來業績承諾總額達6,900億港元**，按年增長33%
- ? 淨收入保留率達126%，顯示客戶穩定增長與持續消費
- ? 非GAAP營運利潤率達9%，自由現金流利潤率為43%
### 業務動態與市場發展
- ? 產品創新加速，年度推出超過400項新功能，涵蓋AI、數據共享及雲端計算
- ? 與Microsoft擴大合作，將OpenAI模型整合至Cortex AI，提升AI應用能力
- ? 金融與科技客戶表現強勁，ExxonMobil、Honeywell、倫敦證交所等知名企業持續採用
- ? 資料工程與AI應用增長，Snowpark佔FY25產品收入3%，動態表導入企業級應用
### 企業策略與運營效率
- ? 積極拓展多產品採用，Snowflake持續獲取新客戶，並推動現有客戶的產品覆蓋率
- ? FY25非GAAP調整後自由現金流利潤率達26%，顯示業務穩健增長
- ? 精簡組織結構與提高營運效率，包括優化管理層級及提高新進人員質量
- ? 未來增聘工程及銷售團隊，確保新產品市場滲透度
### FY26前瞻與財務展望
- ? Q1產品收入預計介乎955至960億港元，按年增長21-22%
- ? **FY26產品收入預期達4,280億港元**，按年增長24%
- ? 預期非GAAP營運利潤率將提升至8%，自由現金流利潤率為25%
- ? **股權補償費用（SBC）將下降**，由FY25的41%降至FY26的37%
### 未來增長機遇與風險管理
- ? Iceberg數據格式推動更廣泛數據覆蓋，開放式數據管理進一步提升Snowflake競爭力
- ? AI與機器學習技術應用擴大，客戶使用Snowflake AI功能的每週活躍數超過4,000
- ? 全球市場擴張，Snowflake計劃於主要市場加強推廣與合作
- ? 專注於提升產品價值與客戶體驗，透過數據工程與AI解決方案增強業務吸引力

分析員問題與解答FAQs

會議內容

SELECT * FROM `tblmarketprice` WHERE (`code`, `date`) IN (('^HSI', '2025-03-03 00:00:00'), ('^HSI', '2025-02-28 00:00:00'), ('^HSI', '2025-02-27 00:00:00'), ('^HSI', '2025-02-26 00:00:00'), ('^HSI', '2025-02-25 00:00:00'), ('^HSI', '2025-02-24 00:00:00'), ('^HSI', '2025-02-21 00:00:00'), ('^HSI', '2025-02-20 00:00:00'), ('^HSI', '2025-02-19 00:00:00'), ('^HSI', '2025-02-18 00:00:00'), ('^HSI', '2025-02-17 00:00:00'), ('^HSI', '2025-02-14 00:00:00'), ('^HSI', '2025-02-13 00:00:00'), ('^HSI', '2025-02-12 00:00:00'), ('^HSI', '2025-02-11 00:00:00'), ('^HSI', '2025-02-10 00:00:00'), ('^HSI', '2025-02-07 00:00:00'), ('^HSI', '2025-02-06 00:00:00'), ('^HSI', '2025-02-05 00:00:00'), ('^HSI', '2025-02-04 00:00:00'))

過往會議記錄

Snowflake 雪花 SNOW 2024年第4季度電話會議記錄 問 Ai

Snowflake 雪花 SNOW 2024年第4季度電話會議記錄問 Ai