Snowflake Inc. (SNOW) Earnings

Management highlights

### AI-Driven Strategic Positioning & Product Momentum - Sridhar Ramaswamy frames Snowflake as the foundational platform for the agentic enterprise, combining a unified governed data foundation, access to leading AI models, cross-workflow connectivity, and a unifying agentic control plane. The two primary customer-facing products for this control plane are Snowflake Intelligence (natural language interface for business users) and Cortex Code (COCO, natural language development interface for builders). - AI adoption has created a powerful flywheel: AI accelerates core platform consumption as customers migrate legacy workloads to Snowflake to power secure, scalable AI; new AI products are seeing the fastest adoption in company history, opening new revenue streams; and AI product adoption in turn drives additional core platform consumption. - As of Q1, accounts using Snowflake Intelligence more than doubled quarter-over-quarter, and COCO is already used by over 7,100 accounts. COCO drives faster project delivery, including migrations, application development, and agent creation, and has already meaningfully contributed to AI revenue. - Snowflake announced the intended acquisition of Natoma to extend the agentic control plane into everyday enterprise applications, allowing users to complete actions like sending emails, summarizing conversations, and updating work tickets without leaving Snowflake, while maintaining enterprise governance and security. ### Operational & Internal Efficiency Improvements - Internal use of Snowflake's AI products has driven significant productivity gains: support team case resolution is 25% faster with 25% higher throughput per engineer; cloud deployment engineering reduced complex case resolution time by nearly 30% and cut engineering time per ticket by ~40%; COCO doubled developer productivity across the data organization and automated over 100 cross-functional workflows in weeks. In Q1, Snowflake delivered 20% more product capabilities to market than a year prior. - New Chief Revenue Officer Jonathan Boullier (JB) has seamlessly transitioned into role and positioned the go-to-market organization for AI-era scale. In Q1, the number of new use cases deployed increased 114% YoY, and use cases won per account executive increased 86% YoY, reflecting stronger demand and improved execution. ### Customer & Ecosystem Expansion - Snowflake added 13 new Global 2000 customers in Q1, up from 4 in the year-ago quarter, and saw expansion from major existing customers including a large U.S. bank that completed a multi-year Teradata migration, Nestle expanding enterprise-wide digital transformation workloads, and a large wealth management firm deploying a Cortex-powered agent that answers over 60% of executive data inquiries instantly. - Snowflake announced a new expanded $6 billion multi-year collaboration agreement with AWS to accelerate global enterprise AI adoption, and surpassed $7 billion in lifetime AWS Marketplace sales. The company also announced a $200 million expanded partnership with OpenAI and brought joint SAP partnership capabilities to general availability. ### Leadership Update - Co-founder and Chief Architect Benoit Dageville will step down from day-to-day operations in mid-June 2024, and will remain a member of the Board of Directors. Product leadership will continue to be led by EVP Christian Kleinerman.

Guidance

- Product revenue guidance for full-year FY27 was raised from 27% YoY growth to 31% YoY growth, representing a new full-year product revenue target of $5.84 billion. The upward revision primarily reflects stronger-than-expected early adoption of COCO and accelerating growth in the core data platform business. - Q2 FY27 product revenue is guided to between $1.415 billion and $1.42 billion, representing 30% YoY growth. - Full-year FY27 non-GAAP product gross margin guidance is maintained at 75%; the lower gross margin of AI products is offset by lower bandwidth costs from the new AWS agreement. - Full-year FY27 non-GAAP operating margin guidance was raised from 12.5% to 13.5%. Q2 non-GAAP operating margin is guided at 12.5%. - Full-year FY27 non-GAAP adjusted free cash flow margin guidance remains unchanged at 23%. - The full-year guidance still includes a 150 basis point headwind from the Observe acquisition, unchanged from prior guidance, and Observe is expected to add approximately 1 percentage point to full-year product revenue growth. - There has been no change to Snowflake's guidance philosophy; guidance is based on observed consumption behavior, and the upward revision reflects new observed traction from the recently launched COCO product.

Segment performance

Snowflake reports a single product segment for its AI Data Cloud platform. In Q1 FY27, product revenue totaled $1.334 billion, representing 34% year-over-year growth, accelerating from 30% in the prior quarter and 26% in the year-ago quarter. This marked the strongest sequential dollar product revenue growth in Snowflake's history. Key segment metrics include: 13,912 total customers, 616 net new customers (up 38% YoY), 64 customers with over $10 million in trailing 12-month (TTM) revenue, and 779 customers with over $1 million in TTM revenue. 46 customers crossed the $1 million TTM revenue threshold in Q1, up from 26 in the year-ago quarter. Net revenue retention was 126%, and remaining performance obligations grew 38% YoY. Non-GAAP operating margin reached 12%, expanding over 300 basis points YoY. Non-GAAP product gross margin for the quarter was in line with the full-year target of 75%.

Risks & headwinds

Management did not discuss new material operational failures or unanticipated risks during this call. Management noted that forward-looking statements are subject to inherent risks and uncertainties that could cause actual results to differ materially from projections, and directed investors to review risk disclosures in Snowflake's recent SEC filings (10-K, 10-Q) and earnings press release. Management acknowledged the need to build cost governance controls for AI product usage to prevent unexpected customer spend, and is already building account-level and agent-level cost limits into the platform, but does not expect unregulated spend to become a material headwind to adoption.

Analyst Q&A

• Q: What drove the inflection in growth and the large upward guidance revision this quarter, split between market demand, core platform growth, and AI product traction? /

  A: The inflection comes from a three-part effect: AI is creating a strong secular tailwind for the core data platform as customers accelerate migrations to Snowflake to power AI workloads; agentic products Snowflake Intelligence and COCO (which launched the week before Q1 began) saw much stronger early adoption than expected; and COCO creates a second-order effect by driving additional core platform consumption, because it makes projects, migrations, and new workload deployment much faster. COCO was the single largest driver of the guidance increase, as management had no observed adoption behavior to include in prior guidance, allowing the team to layer in the new traction for the full-year outlook, alongside the observed acceleration in the core business.

• Q: Will customers begin throttling COCO spend to control costs, and what is the impact of lower-margin AI products on overall gross margin? /

  A: While cost management is a valid consideration, COCO delivers enormous productivity value that far outweighs incremental spend for most customers: for large enterprises, labor costs for data teams are 3-4x the cost of data infrastructure, so 10x productivity improvements from AI are very well received. Management is proactively building cost governance tools (account-level, agent-level spend limits) to help customers manage usage. While AI products do have a lower gross margin than the core platform, lower bandwidth costs from the new expanded AWS agreement offset this drag, allowing Snowflake to maintain its 75% full-year product gross margin target.

• Q: What moat does Snowflake have against pure-play AI labs and new entrants in autonomous agent development, given the importance of context for agent performance? /

  A: Snowflake sits at the center of enterprises' most valuable governed data, which gives it an unmatched ability to provide the context AI agents need to deliver useful results. Snowflake already leverages metadata and activity data inside the platform to improve query performance, and now uses that same data to improve AI context for COCO and Snowflake Intelligence, leading to better out-of-the-box results than generic agents. Widespread customer use of COCO within Snowflake also creates a flywheel: Snowflake can learn across usage patterns to improve the product over time, which deepens its competitive advantage.

• Q: Why isn't Snowflake leaning into more go-to-market hiring given the strong demand, especially with the new CRO transition? /

  A: AI has already driven large productivity improvements across the entire organization, allowing Snowflake to win far more use cases per account executive than a year ago. Solution engineers can now build relevant prototypes and demos much faster, and internal functions like support, documentation, and SRE have become much more efficient via AI automation, freeing up resources to invest in high-leverage growth areas. Management will continue to invest in key growth functions, but is benefiting from widespread efficiency gains from AI that reduce the need for large-scale incremental hiring.