Summary of Datadog Conference Call Company Overview - **Company**: Datadog (NasdaqGS: DDOG) - **Date**: November 18, 2025 - **Context**: Discussion of recent performance, product developments, and market trends Key Points Industry and Market Dynamics - **AI and Non-AI Workloads**: Datadog is observing a shift where 70%-75% of workloads remain legacy and on-premise, prompting a focus on modernization and the adoption of AI tools to enhance application utility [7][12][10] - **Customer Adoption**: The company is seeing increased adoption of its platform, particularly in Digital Experience Monitoring, which surpassed $300 million in revenue [4][15] - **Security Business Growth**: There has been a notable acceleration in the security segment, attributed to improved enterprise selling capabilities and competitive advantages over traditional players like Splunk [26][27] Financial Performance - **New Customer Acquisition**: Datadog reported a significant increase in new logos, driven by expanded quota capacity and a strong pipeline for Q4 and early next year [33][14] - **Revenue Growth**: The company is experiencing growth across various customer segments, including AI natives, with significant contributions from six-figure and seven-figure customers [15][17] Product Development and Innovation - **BitsAI Launch**: The introduction of BitsAI is generating excitement, with potential for increased customer value through enhanced problem diagnosis and resolution capabilities [31][32] - **Service Management Expansion**: Datadog aims to integrate service management into its platform, enhancing functionality and user engagement [56] Strategic Outlook - **M&A Strategy**: Datadog is open to larger acquisitions but maintains a high bar for integration, focusing on product management and technological alignment [36][38] - **Government Opportunities**: The company is pursuing FedRAMP certification to tap into government contracts, particularly in defense, although current contributions are minimal [42][45] Customer Insights - **Customer Preferences**: Customers prefer integrated solutions over open-source alternatives, valuing the efficiency and cost-effectiveness of Datadog's platform [23][24] - **AI Budgeting**: There is a growing comfort among customers regarding AI spending, which is expected to open up more opportunities for Datadog [47] Future Growth Drivers - **Long-term Vision**: Datadog's vision includes expanding its platform to address a broader user base and increasing functionality, particularly in security and AI workloads [56] Conclusion - Datadog is positioned for continued growth through strategic product enhancements, a strong customer acquisition strategy, and a focus on modernization in the tech stack. The company is optimistic about its future prospects, particularly in the AI and security domains.

Core Viewpoint - It is advisable to remain heavily invested in major technology companies that are significantly represented in leading indices like the Nasdaq 100 and S&P 500 [1] Group 1 - Major technology companies are currently well-represented at the top of popular indices [1]

Venture Capital Evolution - The venture capital playbook is considered broken, with significant changes needed in response to the evolving landscape, particularly due to AI [1][2] - Sequoia's leadership transition reflects a broader industry truth that many VCs and executives from the last decade are not suited for the next decade [7][28] - The pace of AI evolution is rapid, making knowledge from even six months ago potentially obsolete [5][28] AI Investment Strategy - Successful AI investments require attaching to compute budgets, replacing human headcount, or massively displacing incumbents [29] - Companies that merely use AI to enhance their products are not gaining competitive advantages; this is now seen as a baseline expectation [21][29] - The transition from AI as a tool to AI as a team member is anticipated to drive significant revenue growth [11][30] Deal Dynamics - The quality and speed of competitive clones in the AI space have increased, compressing the time available to build defensible market positions [7][12] - Traditional seed defensibility is considered dead; founders must focus on scaling quickly rather than relying on early product advantages [7][12] Portfolio Construction - Diversification is becoming increasingly critical due to the heightened variance in AI deal outcomes [7][28] - Small fund sizes ($40-100 million) that accept dilution can yield superior returns compared to larger funds maintaining ownership [7][25][30] - The best fundraising processes are characterized by cultivating relationships over time, rather than following a traditional process [31][37] Market Dynamics - The current fundraising environment is described as binary, where companies either secure funding or struggle significantly [27][38] - Companies like DataDog that are closely tied to AI compute infrastructure are performing well, while those like Duolingo that do not replace human roles are facing declines [21][14] Future Outlook - The panel anticipates that 2026 will see AI integrated as a core team member, leading to a revenue explosion [11][30] - The ongoing evolution in venture capital necessitates a reevaluation of strategies and approaches to remain competitive in the changing landscape [33][36]

Core Insights - Datadog's stock has reached an all-time high, driven by the increasing demand for AI tools and services, which aligns with Ark Investment Management's forecast of a $13 trillion opportunity in the software industry by 2030 [1][3][18] Company Overview - Datadog offers a comprehensive portfolio of software and AI development tools, which are essential for developers, particularly in the context of AI software development [3][4] - The company's cloud observability platform is utilized across various industries, providing real-time monitoring of digital infrastructure to prevent customer experience disruptions [4][5] AI Product Demand - Datadog has introduced AI-specific products such as LLM Observability and OpenAI Monitoring, which help developers manage costs and technical issues when building large language models [6][7] - The number of customers using Datadog's AI products has surged by 67% year-over-year, indicating strong demand and growth potential in this segment [8][9] Financial Performance - In Q3 2025, Datadog reported total revenue of $886 million, a 28% increase from the previous year, with AI products contributing significantly to this growth [10][11] - AI-native customers accounted for 12% of total revenue, doubling from 6% a year ago, showcasing the accelerating revenue growth in this area [11] Future Projections - Following strong financial results, Datadog has raised its revenue forecast for 2025 to $3.39 billion, nearly $200 million higher than initial estimates [12] - Analysts are generally bullish on Datadog's stock, with a consensus price target suggesting an 8% potential increase over the next 12 to 18 months, although the stock is currently trading at a premium [13][15] Market Position - Datadog's price-to-sales ratio is currently at 22.4, which is 33% higher than its three-year average, indicating potential limitations for further upside in the near term [15][17] - The demand for cloud observability tools and AI monitoring is expected to grow significantly, positioning Datadog favorably in a market projected to expand dramatically by 2030 [18]

Core Viewpoint - The article discusses the reliability of Wall Street analysts' recommendations, particularly focusing on Datadog (DDOG), and emphasizes the importance of using these recommendations in conjunction with other analytical tools like Zacks Rank to make informed investment decisions [1][5][10]. Summary by Sections Brokerage Recommendations - Datadog has an average brokerage recommendation (ABR) of 1.36, indicating a consensus between Strong Buy and Buy, based on 42 brokerage firms' recommendations [2]. - Out of the 42 recommendations, 33 are Strong Buy and 3 are Buy, which represent 78.6% and 7.1% of the total recommendations, respectively [2]. Limitations of Brokerage Recommendations - Solely relying on the ABR for investment decisions may not be wise, as studies indicate limited success of brokerage recommendations in predicting stock price increases [5]. - Brokerage analysts often exhibit a positive bias due to their firms' vested interests, leading to a disproportionate number of favorable ratings compared to negative ones [6][10]. Zacks Rank as an Alternative - Zacks Rank is presented as a more reliable tool, categorizing stocks from Strong Buy to Strong Sell based on earnings estimate revisions, which have shown a strong correlation with near-term stock price movements [8][11]. - The Zacks Rank is updated more frequently than the ABR, making it a timely indicator for predicting future stock prices [12]. Current Outlook for Datadog - The Zacks Consensus Estimate for Datadog's earnings has declined by 2.1% over the past month to $1.85, reflecting analysts' growing pessimism about the company's earnings prospects [13]. - This decline in consensus estimates has resulted in a Zacks Rank of 4 (Sell) for Datadog, suggesting caution despite the favorable ABR [14].

Core Insights - Datadog has launched a new product, Storage Management, aimed at helping teams optimize cloud object storage costs and eliminate unnecessary spending [1][4] - The product is designed to provide granular visibility, proactive anomaly detection, and targeted recommendations for cloud storage management [1][4] Group 1: Product Features - Storage Management offers detailed insights into cloud object storage at the bucket and prefix levels, enabling teams to identify anomalies in storage growth and access patterns [4] - The product provides unified context by correlating cost, usage, and metadata across different buckets and prefixes, facilitating the enforcement of lifecycle and retention policies [7] - It includes proactive anomaly detection and alerts to quickly identify and respond to unexpected storage growth and cost spikes [7] Group 2: Market Context - The increasing usage of cloud object storage driven by data-intensive and AI workloads has led to rising cloud storage costs, making cost management a significant challenge for operations teams [2] - Companies developing AI products find that data storage and processing costs are often the third-highest expense, surpassing costs associated with AI model training and inference [5] Group 3: Optimization Opportunities - Datadog Storage Management helps organizations uncover specific savings opportunities, such as transitioning cold data to less expensive storage classes and deleting duplicate objects [3][5] - The product aims to accelerate savings by providing actionable recommendations on data re-tiering, archiving, or deletion [7]

Industry Overview - The Internet Software and Services sector is experiencing growth due to increased IT spending on hybrid operating environments and mobile device penetration, prompting businesses to invest in web-based infrastructure and security software [1] - The Internet Software industry is ranked in the top 28% of Zacks Industry Rank, indicating expected outperformance in the market over the next three to six months [2] Company Highlights Palantir Technologies Inc. (PLTR) - Palantir's AI strategy integrates its Foundry and Gotham platforms, focusing on AI adoption in government and commercial sectors, with an expected revenue growth rate of 41.1% and earnings growth rate of 43% for next year [6][10] - The company is involved in significant government projects, such as the Department of Defense's Open DAGIR initiative, enhancing military operations through AI [7] - Palantir's AIP boot camps have attracted over 1,000 companies, showcasing its platform's capabilities across various industries [8] Snowflake Inc. (SNOW) - Snowflake is set to benefit from rising demand for cloud-based data platforms, with an expected revenue growth rate of 22.3% and earnings growth rate of 33.9% for next year [11][15] - The cloud analytics market is projected to grow from $35.39 billion in 2024 to $130.63 billion by 2030, with a CAGR of 25.5%, supporting Snowflake's growth trajectory [12] - Snowflake's AI Data Cloud is gaining traction across multiple industries, enhancing enterprise capabilities in data management and analytics [14] Datadog Inc. (DDOG) - Datadog is experiencing growth from new customer acquisitions and increased adoption of its cloud-based monitoring platform, with an expected revenue growth rate of 19% and earnings growth rate of 15.4% for next year [16][20] - The company unveiled over 125 new products at DASH 2025, including AI observability tools, enhancing its competitive position [17][18] - Datadog's solutions are increasingly used to monitor AI-powered applications, driving broader product usage [19] Atlassian Corp. (TEAM) - Atlassian is benefiting from the demand for remote working tools, with a 25X year-over-year increase in AI interactions among over 1 million monthly active users [22] - The company's AI-powered Rovo platform and automation tools are driving growth in premium and enterprise editions [23] - Atlassian's collaboration with OpenAI to enhance its software with generative AI features is expected to boost revenue [24] Zoom Communications Inc. (ZM) - Zoom is capitalizing on the hybrid work trend, with its AI Companion achieving a fourfold increase in monthly active users year-over-year [26][27] - The platform's integration with third-party applications and custom AI functionalities is enhancing operational efficiencies for customers [28] - Zoom has an expected revenue growth rate of 3% and earnings growth rate of 0.1% for next year [29]

Core Insights - Rokt has appointed David Obstler, CFO of Datadog, to its board of directors and Matt Briers, former CFO of Wise, as a board advisor and observer, as the company prepares for a potential IPO [1][2][3] Group 1: Executive Appointments - David Obstler will chair the audit committee and has extensive experience in operational finance, particularly in technology companies [3][4] - Matt Briers brings experience from his tenure at Wise, where he oversaw significant global expansion and a successful direct listing [4] Group 2: Company Growth and Financial Performance - Rokt's revenue grew by over 40% year-over-year in 2024, reaching $600 million [5] - The company is projected to power more than 7.5 billion transactions in 2025 across various leading ecommerce businesses [5] Group 3: Strategic Partnerships and Acquisitions - Recent partnerships include collaborations with Ulta Beauty, Albertsons, and Macy's, alongside acquisitions of Canal, mParticle, and Aftersell [6][7]

Core Insights - Datadog reported $885.65 million in revenue for Q3 2025, marking a year-over-year increase of 28.4% [1] - The EPS for the same period was $0.55, up from $0.46 a year ago, with a surprise of +22.22% compared to the consensus estimate of $0.45 [1] - The revenue exceeded the Zacks Consensus Estimate of $849.77 million by +4.22% [1] Performance Metrics - Datadog has 4,060 customers with over $100k in ARR, surpassing the four-analyst average estimate of 3,942 [4] - The total number of customers stands at 32,000, slightly below the three-analyst average estimate of 32,113 [4] - Remaining Performance Obligations are reported at $2.79 billion, exceeding the three-analyst average estimate of $2.55 billion [4] Stock Performance - Datadog shares have returned +16.3% over the past month, contrasting with the Zacks S&P 500 composite's -0.2% change [3] - The stock currently holds a Zacks Rank 2 (Buy), indicating potential for outperformance in the near term [3]

Core Insights - Datadog reported Q3 2025 non-GAAP EPS of 55 cents, a 19.6% increase year-over-year, exceeding Zacks Consensus Estimate by 22.22% [1] - The company's net revenues reached $885.7 million, reflecting a 28.4% year-over-year growth and surpassing the consensus estimate by 4.22% [1] Customer Metrics - Datadog ended Q3 with 32,000 customers, up from approximately 29,200 in the same period last year [2] - The number of customers with an annualized run rate (ARR) of $100,000 or more increased to 4,060, compared to about 3,490 in the prior year, contributing to 89% of total ARR [2] Product Usage - 84% of customers utilized two or more products, an increase from 83% year-over-year [3] - 54% of customers used four or more products, up from 49% in the previous year [3] - The trailing 12-month net revenue retention rate was approximately 120%, an increase from the mid-110% range in the prior year [3] Financial Performance - Non-GAAP gross profit for Q3 increased by 28.4% year-over-year to $718.9 million, with an adjusted gross margin of 81.2% [4] - Research & development expenses rose by 38.2% year-over-year to $269.5 million, accounting for 30.4% of revenues, an increase of 220 basis points [4] - Sales and marketing expenses increased by 25.5% year-over-year to $195.5 million, with a slight contraction in percentage of revenues to 22.1% [5] - General & administrative expenses grew by 28.7% year-over-year to $46.5 million, remaining flat as a percentage of revenues [5] - Non-GAAP operating income was reported at $207.4 million, a 19.8% increase year-over-year, although the non-GAAP operating margin declined by 170 basis points to 23.4% [6] Balance Sheet and Cash Flow - As of September 30, 2025, Datadog had cash, cash equivalents, and marketable securities totaling $4.1 billion, up from $3.9 billion as of June 30, 2025 [7] - Operating cash flow for the quarter was $251 million, an increase from $200 million in the previous quarter [7] - Free cash flow was reported at $214 million, compared to $165 million in the prior quarter [7] Guidance - For Q4 2025, Datadog anticipates revenues between $912 million and $916 million, with non-GAAP EPS expected in the range of 54-56 cents [10] - For the full year 2025, revenues are projected between $3.386 billion and $3.390 billion, with non-GAAP EPS expected to be between $2.00 and $2.02 [10]