DDOG Q1 Earnings Call: Growth in Large Deals, AI Adoption, and Platform Expansion Drive Outlook
Cloud monitoring software company Datadog (NASDAQ:DDOG) reported Q1 CY2025 results topping the market's revenue expectations , with sales up 24.6% year on year to $761.6 million. The company expects next quarter's revenue to be around $789 million, close to analysts' estimates. Its non-GAAP profit of $0.46 per share was 9% above analysts' consensus estimates.
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Revenue: $761.6 million vs analyst estimates of $741 million (24.6% year-on-year growth, 2.8% beat)
Adjusted EPS: $0.46 vs analyst estimates of $0.42 (9% beat)
Adjusted Operating Income: $166.5 million vs analyst estimates of $165.1 million (21.9% margin, 0.8% beat)
The company lifted its revenue guidance for the full year to $3.23 billion at the midpoint from $3.19 billion, a 1.3% increase
Management raised its full-year Adjusted EPS guidance to $1.69 at the midpoint, a 2.4% increase
Operating Margin: -1.6%, down from 2% in the same quarter last year
Free Cash Flow Margin: 32.1%, similar to the previous quarter
Customers: 3,770 customers paying more than $100,000 annually
Net Revenue Retention Rate: 118%, in line with the previous quarter
Annual Recurring Revenue: $3.2 billion at quarter end, up 24.6% year on year
Billings: $747.7 million at quarter end, up 21% year on year
Market Capitalization: $36.61 billion
Datadog's first quarter results were shaped by robust customer adoption of new observability and security products, alongside notable expansion in enterprise and AI-native segments. CEO Olivier Pomel highlighted increased usage of products like Flex Logs and Database Monitoring, as well as strong traction with large customers, stating, 'Dollar bookings for new logos were up over 70% year-over-year and much stronger than our typical seasonal softness in Q1.'
Looking ahead, management raised full-year revenue and adjusted earnings guidance, citing continued investment in sales capacity and R&D to support product innovation and market expansion. CFO David Obstler emphasized that while 'cloud hosting costs rose more quickly than we expected in Q1,' Datadog remains focused on optimizing expenses and expects efficiency projects to yield savings throughout the year.
Datadog's leadership attributed Q1 performance to increasing product adoption, strong execution in large enterprise deals, and momentum in AI-driven workloads. The company also emphasized investments in new product areas and international expansion to sustain growth.
Platform adoption broadening: Management reported rising customer engagement across multiple products, with a growing proportion of users adopting four or more Datadog offerings. Notably, 83% of customers now use at least two products, reflecting increasing reliance on the platform.
AI cohort accelerating: The AI-native customer segment continued to grow, with these clients now representing approximately 8.5% of annual recurring revenue. Management noted that AI-related deals contributed significantly to overall revenue growth and bookings.
Large enterprise deals rising: The quarter saw a sharp increase in large transactions, with 11 deals exceeding $10 million in total contract value—up from just one in the same period last year. These wins were attributed to Datadog's ability to replace multiple existing tools and consolidate observability functions for complex organizations.
Security and data observability investment: The company highlighted expansion in its security and data observability products, supported by the recent acquisitions of Eppo and Metaplane. Over 7,500 customers now use Datadog's security offerings, and the Database Monitoring product is approaching $50 million in annual recurring revenue.
International and sales capacity growth: Datadog increased its international sales headcount by mid-30% year-over-year and continues to target new markets, including the launch of an Australian data center to address regional requirements for data residency and privacy.
Management's outlook for the coming quarters is shaped by continued investment in product innovation, expansion of sales capacity, and growing demand for observability and security solutions—especially among large enterprises and AI-focused organizations.
Continued AI adoption: Management expects further growth from AI-native customers, with increased observability needs as organizations deploy more AI-driven workloads in production environments.
Platform expansion and integration: The integration of new capabilities from recent acquisitions and the expansion of data observability solutions are positioned to drive cross-sell opportunities and deepen customer engagement.
Margin focus and efficiency projects: While gross margins faced short-term pressure from higher cloud hosting costs, Datadog is prioritizing efficiency initiatives to optimize spending and maintain margins within its historical range, even as operating investments continue.
Mark Murphy (J.P. Morgan): Asked about the opportunity in monitoring AI-generated code, to which CEO Olivier Pomel responded that the shift to AI-written software increases the need for observability, moving value from code creation to operational monitoring.
Sanjit Singh (Morgan Stanley): Inquired about the evolution of data observability as a growth area. Pomel explained that data observability is now seen as critical for building new AI workloads and emphasized the strategic importance of recent acquisitions in this space.
Raimo Lenschow (Barclays): Questioned the factors behind the raised guidance and gross margin changes. CFO David Obstler explained that guidance reflects recent trends but remains conservative, and margin pressure was due to increased cloud costs and investment in new functionality.
Jake Roberge (William Blair): Asked about the durability of AI-native cohort growth and Flex Logs adoption. Pomel noted potential volatility due to customer concentration but stated that Flex Logs is driving net new use cases and higher platform usage.
Brad Reback (Stifel): Sought clarity on Datadog's approach to on-prem and "bring your own cloud" workloads. Pomel indicated that Datadog is adapting solutions to address customer preferences and sees opportunity in supporting hybrid and on-prem environments.
Looking ahead, the StockStory team will monitor (1) ongoing adoption of AI observability and security products, (2) the impact of sales capacity expansion on large enterprise deal volume, and (3) the integration and market traction of recent acquisitions like Eppo and Metaplane. The outcome of Datadog's DASH user conference in June and progress on margin optimization initiatives will also be important signposts for tracking execution.
Datadog currently trades at a forward price-to-sales ratio of 11.5×. In the wake of earnings, is it a buy or sell? See for yourself in our free research report.
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