Datadog (DDOG) shares in early May fell 11.5% in one session even though the company delivered strong Q1 results and raised its 2024 revenue outlook. The stock has now rebounded 10.6% from the May 7 low of $110.34, although it’s still 3.8% below where it was trading just ahead of the earnings report.
Datadog, a provider of a cloud-based observability and security platform, reported that Q1 total revenue of $611.2 million advanced 27%, accelerating from growth of 25.6% in the previous quarter. Total revenue beat the consensus estimate by 3.4%. Operating margin of 27% was nicely above the outlook of 22%. Per-share earnings of 44 cents came in nine cents above the consensus. Free cash flow totaled $187 million (30.6% margin).
Total RPO of $1.73 billion rose 52%, while current RPO grew in the low-40% range. The total customer base gained 10% to 28,000. Datadog added about 700 customers sequentially, up from 500 in the previous quarter. There are now 3,340 customers with annual recurring revenue (ARR) of $100k+, up 15% year over year. Dollar-based net retention held steady sequentially in the mid-110% range.
For Q2, Datadog sees total revenue of $620 million to $624 million (growth of 22% at the midpoint) versus the consensus at the time of $620.6 million. The EPS outlook of 34 cents to 36 cents was in line with the consensus of 35 cents.
For 2024, the company’s updated total revenue outlook of $2.59 billion to $2.61 billion was above the consensus of $2.58 billion. The latest forecast represents growth of 22% to 23%, above the previous guide calling for 20% to 21% growth. The updated 2024 EPS outlook of $1.51 to $1.57 topped the previous forecast of $1.38 to $1.44.
Given Datadog’s pricey valuation, expectations were high heading into the Q1 report. With the stock recently trading around $122, the enterprise value/forward revenue multiple is still elevated at 14.8 (based on the 2024 consensus revenue estimate of $2.61 billion).
Datadog bulls point to several positives that could drive upward revenue revisions throughout the year. The company continues to see robust RPO growth (powered by longer-term commitments from large customers), product platform acceptance is healthy (47% of customers have four or more products versus 43% a year ago), cloud cost optimization activity has eased and usage trends are improving at existing customers (usage growth in Q1 was higher than in Q4).
At last week’s JP Morgan tech conference, Datadog CEO Olivier Pomel offered some upbeat commentary, saying the company is seeing “stabilization or growth again from most of the customer base.” AI-native customers are “growing gangbusters,” while large enterprises are “accelerating growth.” Older organizations (mainly web and mobile natives) are “growing, but more cautiously,” according to Pomel.
He argued that the observability business alone can enable Datadog to scale 5x or 10x from here based on the fact that the company is a constant share gainer in the IT operations management (ITOM) market, which is growing 10% to 11% annually. Datadog also operates in the cloud services market, which is growing about 20% annually. Datadog is the #1 provider of observability solutions in the cloud, but only has a 9% to 10% share, leaving plenty of growth runway.
Pomel said Datadog is largely under-penetrated across its current customer base with existing products, while continuing to expand its overall product footprint. He noted that the company’s new products shipped between 2020 and 2023 have already contributed more than $200 million in ARR.
Datadog is benefiting from vendor consolidation in observability (especially after the acquisitions of Splunk and New Relic), according to Pomel. Organizations are increasingly realizing that it’s more efficient to use Datadog instead of a number of point solutions because the company can provide a unified view of operations across teams and datasets.
Datadog’s growth will continue to be driven by cloud migrations, digital transformation and AI adoption. When it comes to AI, the vast majority of the tech industry right now is still training or prototyping AI models versus actually running them in inference, said Pomel. On the Q1 earnings call, he talked about how Datadog usage tends to be more correlated with live applications and inference workloads that follow AI training.
Following the Q1 report, Baird upgraded Datadog to ‘Outperform’ with a price target of $140. The firm thinks the pullback in the stock provides a buying opportunity, calling out dissipating cloud cost optimization headwinds and improving cloud consumption trends.
Datadog possesses the industry-leading, cloud-native observability platform that should continue to benefit from the accelerating shift to the cloud, according to Baird. Also, the firm sees Datadog benefiting from industry share gains against Cisco/Splunk.
Baird points out that AI is already contributing to Datadog’s growth and will provide more tailwinds as inference work picks up and AI applications move into production and start to scale with users.
Barclays trimmed its Datadog price target to $145 from $152, but kept its ‘Overweight’ rating because it continues to believe the company is well-positioned to reaccelerate growth on the back of ramping new workloads. Guggenheim agrees, saying it’s just a matter of when, not if, Datadog’s business momentum begins to reaccelerate.
