Datadog's 2026 Q2 Call: Guidance Conservatism, Growth Driver Claims Clash

Date of Call: Aug 6, 2026

Financials Results

• Revenue: $1.12B, up 36% YOY
• EPS: $0.63 to $0.65 per share (Q3 guidance); $2.50 to $2.54 per share (full-year 2026 guidance)
• Gross Margin: 79.62%, compared to 80.5% last quarter and 80.5% prior year
• Operating Margin: 23% to 24% (Q3 guidance); 23% (full-year 2026 guidance)

Guidance:

• Q3 revenue expected in the range of $1.13B, representing 28% to 29% YOY growth.
• Q3 non-GAAP operating income expected in the range of $260 to $270M, implying an operating margin of 23% to 24%.
• Q3 non-GAAP net income per share expected in the range of $0.63 to $0.65.
• Full-year 2026 revenue expected in the range of $4.4B, representing 30% YOY growth.
• Full-year 2026 non-GAAP operating income expected in the range of $1.01B to $1.03B, implying an operating margin of 23%.
• Full-year 2026 non-GAAP net income per share expected in the range of $2.50 to $2.54.

Business Commentary:

Revenue Growth and AI Customer Expansion:

• Datadog reported revenue of $1.12 billion for Q2 2026, representing an increase of 36% year-over-year.
• The growth was driven by accelerated revenue across the customer base, with significant contributions from AI-native customers and a notable increase in non-AI customer growth to the high 20% year-over-year.

Product Adoption and Platform Strategy:

• The company observed that 58% of customers now use four or more products, up from 52% a year ago, and 13% use 10 or more products, up from 7% a year ago.
• This trend is attributed to Datadog's platform strategy, which has resonated well in the market, with customers adopting more products to optimize business outcomes.

Geographic and Segment Performance:

• Datadog's performance was strong across all regions, with particular strength in the Americas due to significant AI activity in the U.S., and robust execution in LATAM.
• Growth was broad-based across customer segments and industries, indicating a strong adoption trend of AI and cloud technologies.

Innovation and New Product Launches:

• At the Dash user conference, Datadog announced over 100 new products and features, including enhancements to Bits.ai and expansions in AI and security offerings.
• These innovations are aimed at addressing the growing complexity in customer workflows and the increasing demand for AI and security solutions.

Customer Retention and Financial Metrics:

• The trailing 12-month net revenue retention percentage was in the low 120s, indicating strong customer retention and loyalty.
• The company's free cash flow was $279 million with a free cash flow margin of 25%, reflecting efficient operations and strong financial health.

Sentiment Analysis:

Overall Tone: Positive

• "We are over here and above the high end of our guidance range." "Our business is booming." "We feel very good about what we see in the market." "We feel ideally positioned to have customers of every size and every industry... so they can transform, innovate, and drive value through AI."

Q&A:

• Question from Sanjit Singh (Morgan Stanley): Could you share any additional details on the new contract with the largest customer and the Lower usage, including if it's due to lower unit price, churn, or downsell?
  Response: Management declined to comment on specific customer details, stating the business is booming and the customer's reduced usage does not overshadow the acceleration seen elsewhere, with the business growing at the same rate excluding this customer.

• Question from Raimo Lenschau (Barclays): What observability opportunities exist for inference, and how much more observability is needed?
  Response: Management sees opportunity at every layer of the AI stack, from infrastructure (GPUs) to agent monitoring and application-level observability, with customer concerns shifting towards cost optimization as AI adoption scales.

• Question from Gabriela Borges (GS): How are CFO-level conversations evolving, especially regarding new features like infinite cardinality and budget sourcing?
  Response: The core value proposition remains helping customers make or save money. New features like infinite cardinality address cost and complexity concerns, helping customers control AI costs and get more value from their data.

• Question from Mike Sikos (Needham): Are the AI labs you landed this quarter the same as the in-house AI labs with hyperscalers, and what's driving the strong ramp of new logos?
  Response: They are different customer sets: new AI-native labs and established hyperscaler labs. The strong ramp of new logos (30% of growth) is a compounding trend, driven by both new logos added over the last year and their subsequent growth.

• Question from Alex Zuckin (Wolf Research, LLC): How is AI security, like AI breaking containment, presenting an opportunity for Datadog's observability and security crossover?
  Response: AI requires a complete rebuild of security approaches, integrating observability and security at speed. Datadog's integrated platform and new AI Guard products are well-positioned to address this emerging complexity.

• Question from Eric Heath (KeyBank Capital): Can you provide more color on the Q3 revenue guidance and the impact of AI model diversification?
  Response: Guidance methodology is unchanged, incorporating conservatism. Model diversification is positive, opening opportunities but also creating complexity, which Datadog is positioned to help manage, similar to its rich AI ecosystem strategy.

• Question from Koji Ikeda (Bank of America): How does Bits.ai automation impact data consumption, and could it reduce the volume of activity that drives revenue?
  Response: Automation via Bits.ai increases value by fixing issues and preventing damage, leading to more product usage (e.g., more dashboards, alerts, users), not reducing consumption—it's a win-win for customers and Datadog.

• Question from Samik Chatterjee (J.P. Morgan): Is the non-AI customer acceleration sustainable, and is it driven by new logos or increased usage?
  Response: Acceleration is broad-based and largely driven by existing customers, sustainable due to cloud migration, product adoption, and consolidation, with go-to-market investments supporting the growth.

• Question from Howard Ma (Guggenheim Security): How does Bits.ai adoption compare to past feature expansions, and what drove the $30M+ TCV deal with a large online media company?
  Response: Bits.ai adoption is broader now, with more surfaces (chat, code generation, testing). The large media deal involved consolidation, using multiple Datadog products for AI, cloud SIEM, and data observability, reflecting a win against competitors.

• Question from Brad Reback (Stiefel): Should we assume the core business growth excluding the largest customer is strong and accelerating?
  Response: Yes, the core business (excluding the largest customer) has been accelerating for five quarters, with growth rates consistent, indicating underlying strength and positive market trends.

Contradiction Point 1

Guidance Conservatism for Large Customers

Different explanations for conservative guidance on the largest customer's usage.

Sanjit Singh (Morgan Stanley) - Sanjit Singh (Morgan Stanley)

2026Q2: The guidance reflects a conservative view on this large customer's usage, which is a factor they cannot fully control. - David O'Leary(CFO)

Regarding the largest customer renewal's impact on guidance, was the new contract of similar duration, and is the lower usage due to a lower unit price or churn/downsell, and what is the overall outlook for this customer? - Raimo Lenschow (Barclays)

2026Q2: The guidance for Q3 and the full year incorporates the observed usage reduction to de-risk the outlook. - Olivier Pomel(CEO), David Obstler(CFO)

Contradiction Point 2

Drivers of Non-AI Customer Growth

Contradiction on whether growth is driven by existing customers or new logos.

Samik Chatterjee (J.P. Morgan) - Samik Chatterjee (J.P. Morgan)

2026Q2: The acceleration is largely driven by existing customers (not new logos) due to ongoing cloud adoption and consolidation. - Olivier Pomel(CEO), David O'Leary(CFO)

What is driving the acceleration in the non-AI customer base—new logos or increased usage—and is it sustainable, considering CFOs' budget caution around AI? - Mike Cikos (Needham)

2026Q2: The percentage of growth from new logos added in the past year has increased from 25% to 30%, indicating a compounding effect from both new lands and the growth of recently added customers. - David Obstler(CFO)

Contradiction Point 3

Growth Driver: New Logos vs. Existing Customers

Contradiction on whether acceleration is driven by new customer additions or existing customer growth.

Samik Chatterjee (J.P. Morgan) - Samik Chatterjee (J.P. Morgan)

2026Q2: The acceleration is largely driven by existing customers (not new logos) due to ongoing cloud adoption and consolidation... - Olivier Pomel(CEO)

What is driving the acceleration in the non-AI customer base, and is it sustainable—through new logos or increased usage? - Raimo Lenschow (Barclays)

2026Q1: The improvement is due to a combination of platform expansion, successful sales capacity ramp, and market tailwinds from AI investment. The acceleration in non-AI growth is pronounced even when excluding AI-driven trends. - David Obstler(CFO)

Contradiction Point 4

Opportunity Characterization for AI Model Usage

Contradiction in framing the opportunity from AI model diversity—opportunity vs. complexity.

Eric Heath (KeyBanc Capital) - Eric Heath (KeyBanc Capital)

2026Q2: Increased model options open doors for customers but create complexity, which is an opportunity for Datadog. - Olivier Pomel(CEO)

What is the impact of diversified AI model usage by customers on business performance? - Mark Murphy (J.P. Morgan)

2026Q1: The heterogeneity of silicon is a tailwind for Datadog as it allows the company to provide a unified view across diverse infrastructures. - Olivier Pomel(CEO)

Contradiction Point 5

Impact of AI on Infrastructure Monitoring

Contradiction on whether AI is a direct driver of infrastructure monitoring growth.

Andrew Sherman (Stifel) - Andrew Sherman (Stifel)

2026Q2: There is an acceleration in infrastructure product consumption overall. Much of this is tied to the new build-out for AI workloads... - Olivier Pomel(CEO)

Has there been any growth in AI-driven infrastructure monitoring, particularly with CPUs? - Mark Murphy (JPMorgan Chase & Co)

2025Q4: It's too reductive to map hyperscaler CapEx directly to LLM observability. The broader trend indicates increased system complexity and volume, which benefits Datadog's overall business. - Olivier Pomel(CEO)