Snowflake(US:SNOW)2024-05-23 00:32Financial Data and Key Metrics - Q1 product revenue grew 34% YoY to $790 million [11][19] - Remaining performance obligations (RPO) totaled $5 billion, with YoY growth accelerating to 46% [11] - Non-GAAP adjusted free cash flow margin was 44% [11][20] - Non-GAAP product gross margin was 76.9%, slightly down YoY due to GPU-related costs for AI initiatives [20] - Non-GAAP operating margin was 4%, benefiting from revenue outperformance [20] - Cash, cash equivalents, and investments totaled $4.5 billion at the end of Q1 [20] - Q2 product revenue guidance is between $805 million and $810 million, with full-year product revenue expected to reach $3.3 billion, representing 24% YoY growth [22] Business Line Data and Key Metrics - AI-related products, including Cortex and Arctic, are gaining traction with over 750 customers using Cortex AI capabilities [13] - Snowpark adoption is strong, with more than 50% of customers using it in Q1, driven by Spark migrations [14] - Collaboration capabilities are a key competitive advantage, with nearly a third of customers sharing data products, up from 24% a year ago [15] - Unstructured data processing is growing, with 40% of customers now processing unstructured data on Snowflake, adding over 1,000 customers in the last six months [16] - Iceberg is in public preview with over 300 customers, expected to drive future revenue opportunities [17][21] Market Data and Key Metrics - Strong growth in February and March, with moderation in April due to seasonal factors like Easter holidays in Europe [19][37] - Smaller accounts outside the Global 2000 contributed significantly to growth, alongside large customers like a median entertainment Global 2000 company and a large retail and consumer goods company [19] - Financial services remain the largest vertical, with notable growth in technology and healthcare sectors [80] Company Strategy and Industry Competition - The company is focused on AI innovation, with Cortex AI and Arctic LLM driving differentiation in the market [9][13] - Snowflake is investing in AI and machine learning, with Cortex AI, Iceberg, Snowpark Container Services, and Hybrid Tables expected to be generally available later this year [13][14] - The company is leveraging its partner ecosystem, including collaborations with Fiserv, EY, Deloitte, and others, to amplify its platform's power and unlock new use cases [17] - Snowflake is positioning itself as the world's best enterprise AI data platform, combining collaboration capabilities and a thriving application platform to drive network effects [18] Management Commentary on Operating Environment and Future Outlook - The CEO emphasized the importance of AI in democratizing access to enterprise data and driving growth across all layers of the platform [9][10] - The company is optimistic about its ability to help customers run their businesses more efficiently, with examples including a large US telco and a global financial services customer [11] - Management highlighted the stable optimization environment, with seven of the top 10 customers growing quarter-over-quarter [20] - The company is investing in AI-related initiatives, including the acquisition of TruEra, to unlock additional revenue opportunities in the future [22][30] Other Important Information - The company repurchased 3 million shares at an average price of $173.14, using $516 million in Q1, with $892 million remaining under the $2 billion authorization [20] - Snowflake will host its Investor Day on June 4 in San Francisco, coinciding with the Snowflake Data Cloud Summit [23] Q&A Session Summary Question: Drivers of query volume acceleration and price per query pressure [24] - Growth is driven by new customers, expansion from existing customers, and increased workloads like AI and data engineering [25] Question: Efficiency of Arctic LLM and GPU spend [27] - Arctic LLM was trained efficiently due to a unique mixture of experts architecture and pre-experimentation [28] - GPU spend may increase slightly, with investments focused on AI initiatives and hiring [30] Question: Time to value for Cortex and deferred revenue trends [32] - Cortex AI allows customers to quickly adopt AI without upfront GPU commitments, enabling rapid value creation [33] - Deferred revenue trends are influenced by seasonal billing patterns, with RPO growth reflecting strong customer commitments [34][35] Question: April usage moderation and storage revenue impact [36][38] - April usage was muted due to seasonal factors like Easter holidays, but Q2 guidance reflects current consumption trends [37] - Tiered storage pricing impacted margins by $6 million to $8 million in Q1, with storage revenue remaining consistent at 11% of total revenue [39] Question: Vision for AI and demarcation lines [41] - AI will impact multiple levels of the data stack, with Snowflake focusing on enterprise-grade AI applications and collaborating with partners for broader AI capabilities [43] Question: RPO acceleration and notable trends [45] - RPO growth was driven by large deals, including a $100 million deal in Q1, reflecting strong customer commitments [46] Question: CEO priorities for 2024 [47] - Priorities include driving product innovation, improving go-to-market efficiency, and engaging with customers and partners [48] Question: Sales and marketing forecast and evolution [50] - The sales motion is evolving to address different customer needs, including data scientists and business leaders, with specialized partner organizations supporting new product offerings [51] Question: Iceberg's potential to accelerate growth [56] - Iceberg enables Snowflake to address a larger data footprint, unlocking new use cases and revenue opportunities by integrating with existing customer data [57][58] Question: Strength in smaller customers and sales/marketing investments [70][73] - Growth from smaller customers was broad-based across industries, with investments in sales and marketing focused on quota-carrying hires and business development [72][74] Question: Cortex and Arctic use cases [76] - Cortex AI is being used for applications like sentiment analysis, summarization, and data extraction, with Arctic LLM enhancing enterprise AI capabilities [77][78] Question: Consumption trends and vertical performance [79] - Consumption growth was broad-based, with strong performance in financial services, technology, and healthcare sectors [80]