Datadog's third quarter results surpassed Wall Street’s expectations for both revenue and non-GAAP profitability, but the market responded negatively as investors focused on the implications of early large-customer renewals and shifting growth dynamics. CEO Olivier Pomel noted that, while Datadog saw “continued acceleration of the non-AI customer base” and robust product adoption, some major AI-native customers renewed contracts earlier than anticipated, leading to short-term revenue headwinds due to better pricing. Management also highlighted strong adoption of the Bits AI product and ongoing momentum in multi-product usage across both large enterprises and emerging startups.
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Datadog (DDOG) Q3 2026 highlights:
- Revenue $1.20 billion vs S&P analysts’ estimates of $1.14 billion (35.2% year-on-year growth, 4.6% beat)
- Adjusted EPS $0.81 vs S&P analysts’ estimates of $0.64 (26.4% beat)
- Adjusted operating income $334.3 million vs analyst estimates of $268.6 million (27.9% margin, 24.4% beat)
- Revenue guidance $1.20 billion at the midpoint for Q4 2026, roughly in line with what analysts were expecting
- Adjusted EPS guidance Management raised its full-year adjusted EPS guidance to $2.74 at the midpoint, a 8.7% increase
- Operating margin 6.2%, up from -0.7% in the same quarter last year
- Customers 4,860 customers paying more than $100,000 annually
- Annual recurring revenue $5.03 billion (35.2% year-on-year growth, beat)
- Billings $1.16 billion at quarter end, up 29.9% year on year
- Market capitalization $63.04 billion
While we enjoy listening to the management’s commentary, our favorite part of earnings calls is the analyst questions. Those are unscripted and can often highlight topics that management teams would rather avoid or topics where the answer is complicated. Here is what has caught our attention.
Our top 5 analyst questions from Datadog’s Q3 earnings call
- Sanjit Singh (Morgan Stanley) asked about changes to guidance methodology for large customers; CFO David Obstler explained the focus on minimum commitments and acknowledged early renewals can create short-term headwinds.
- Gabriela Borges (Goldman Sachs) pressed for clarity on sequential revenue trends in the AI cohort; Obstler and CEO Olivier Pomel highlighted the unpredictability caused by early renewals and rapid scaling, but expressed confidence in long-term growth as the cohort diversifies.
- Samik Chatterjee (JPMorgan) questioned the ramping contribution from new customers; Pomel noted larger initial deals, especially in government and international markets, and emphasized that many such wins have yet to fully ramp into revenue.
- Matt Hedberg (RBC) requested insights on Datadog’s opportunity in AI training workloads; Pomel described it as an emerging market segment with significant potential, but emphasized it remains early-stage and not yet a mass-market driver.
- Peter Weed (Bernstein Research) inquired about Bits AI monetization and the new credits-based pricing; Pomel explained the updated pricing model aligns with rapid improvements in model efficiency and supports broader platform usage.
Catalysts in upcoming quarters
In future quarters, our team will be watching (1) the pace at which early-renewed large customers ramp usage above their minimum commitments, (2) continued adoption of Bits AI and other AI-driven automation features across the customer base, and (3) the traction of Datadog’s platform in new verticals such as government and regulated industries. Execution on AI cost management and observability tools will also be a key marker of success.
Datadog currently trades at $176, down from $220.52 just before the earnings. Is the company at an inflection point that warrants a buy or sell? Find out in our full research report (it’s free).
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