Monica Click
There are lots of concerns weighing on the minds of Datadog (NASDAQ:DDOG) investors. With the company largely clearing the hurdle in its 3Q22 results, there are still some concerns for the 4Q22 results and what might the full year 2023 guidance for the company be.
Some of the concerns include the hyperscalers slowing momentum, concerns about end demand for observability and worries about the consumption model of Datadog.
This article aims to provide investors with a preview for Datadog’s earnings that is expected to be released on 16 February. I have written a previous article on Datadog, which can be found here.
Brief company description
Datadog was founded in 2010 and was publicly listed in 2019. It is a monitoring and security platform for cloud applications, catering to users like developers, IT operations teams and business users. The company first started out in infrastructure monitoring and has expanded to observability, application performance monitoring, log management, UX and more recently into AIOps and Security.
Cloud spend optimization, slower workload migration, and decelerating hyperscaler growth
There is no doubt that Datadog could see a slowdown as what we have seen for the hyperscalers, which have thus far reported a slowdown in cloud migration and optimization of cloud spend in their recent quarter.
While I think that the businesses of Datadog and hyperscalers are not like-for-like comparison, there is good reason to look to the hyperscalers to see how Datadog might perform. This is because when there are more workloads deployed into the cloud and the greater the cloud migration activity, this implies greater opportunity for Datadog’s end-to-end observability platform.
Microsoft (MSFT) exited the recent quarter with growth of mid-30s in constant currency for Azure. Management expects Azure growth to decelerate further by four to five percentage points in constant currency terms.
CEO Satya Nadella mentioned this during the quarterly earnings call:
Just as we saw customers accelerate their digital spend during the pandemic, we are now seeing them optimize that spend. Also, organizations are exercising caution given the macroeconomic uncertainty.
This weakness in the cloud space is not just confined to Microsoft.
The leader in the industry, Amazon’s (AMZN) AWS is also feeling the pinch. In the recent quarter, we saw AWS report a modest 20% growth year on year to $21 billion, as customers continued to look to optimize their spend on the cloud with the uncertain and weakening global backdrop. Furthermore, there was evidence that the deceleration will continue in the near-term
CFO Brian Olsavsky had this to say about the headwinds AWS was facing in its recent quarterly earnings call:
As we look ahead, we expect these optimization efforts will continue to be a headwind to AWS growth in at least the next couple of quarters. So far in the first month of the year, AWS year-over-year revenue growth is in the mid-teens.
Alphabet’s (GOOG) Google Cloud also experienced the same deceleration as management cited the macro backdrop for the slower growth in Google cloud as their customers look to optimize costs as well.
What does the slowdown in growth for hyperscalers mean for Datadog?
While hyperscaler activity is correlated to Datadog, I ague that this is not entirely so as Datadog remains more protected in a downturn scenario. This is because Datadog’s broader base of products and applications focusing on mission critical workloads will help to offer better insulation and protection from the deceleration we are seeing with the hyperscalers.
I would also note that in the third quarter, Datadog did not see a change in its demand environment for the optimization activity. This is because of the alignment with new logos and new workloads. That said, management did mention that there was just very slightly more optimization they see on the infrastructure monitoring side of the business compared to Application Performance Monitoring (“APM”).
All in all, I think that in the coming fourth quarter results, if Datadog continues to show resilience even with what we are seeing with the hyperscalers, then this would imply that Datadog has sufficient levers in place with new logos and new workloads that can potentially offset this weakness in hyperscaler growth. That said, I think that I will also be watching for management’s commentary on the demand environment to see if there has been any material changes given the relatively significant deceleration in growth we see with the hyperscalers.
Positive early commentary on 4Q
Firstly, I would note that in the prior earnings call, management mentioned that their sales pipeline was looking strong heading into the fourth quarter for new logos and new products. They continue to see good opportunities across geographies, industries and customer sizes.
Given that Datadog utilizes a usage model, this implies that new logo wins today could lead to sizeable expansion in usage over the years as the macro backdrop improves. This gives customers the near-term agility to be able to do more with less as well.
Secondly, when asked about hiring activity, I think that management will be prudent in hiring activity and plan headcount according to how the macroeconomic environment pans out. The message that management was trying to send in the prior quarter was that its investment in headcount will be done so in a responsible way and management continues to be careful and disciplined in spending while looking towards its long-term opportunity.
Important trends in 3Q
In the third quarter, revenue grew 61% year on year as it beat the high-50s percentage growth expectations for the quarter while Datadog showed strong operating leverage as operating profit margin came in at 17%, four percentage points ahead of consensus and free cash flow margin came in at 15%, five percentage points above consensus.
That said, there were some negatives as there was a deceleration in net logo growth and RPO. Total customers grew 27% year on year in the third quarter, representing a five percentage points deceleration and the first time customer growth went below 30%. In addition, customers with more than $100,000 ARR grew 44% year on year to 2,600, decelerating by six percentage points and it is the fifth quarter of decelerating growth in its large customer metric. That said, I think that this cadence in the large customer metric is still impressive to me. RPO growth came in at 31% year on year, 20 percentage points lower than the second quarter as a result of some large multi-year deals in the third quarter of 2021.
I like that the multi-product adoption is rising as there are now 40% of customer using at least four products and 16% of customer using at least six products, both metrics posting gains sequentially.
Lastly, Datadog acquired Cloudcraft, which is mainly an aqua-hire for the company. Cloudcraft is a cloud design tool that has been used by hundreds of thousands of engineers and provides real-time visualizations to support cloud architecture decisions.
Valuation
To determine the valuation of Datadog’s stock, I utilize an EV/Sales method. I apply a 15x EV/Sales terminal multiple on Datadog’s FY2025 revenue and discount that back by 10% to derive the company’s target price. As the company has been seeing a strong growth rate of more than 30% and operating at a solid “rule of 80” for a software company, I think that the higher EV/Sales is justified.
My one-year target price for Datadog is $121. This implies 41% upside potential from the current stock price.
Risks
Competition
Datadog has shown the capital markets its strong ability to innovate. That said, there is a risk that other players may intensify pressure in the markets in which Datadog operates. Competitors in the observability market include companies like Splunk (SPLK) and Dynatrace (DT). As a result, Datadog needs to continually invest in the talent and continue to bring innovation through persistent research and development efforts.
Weakening cloud environment
As highlighted at great lengths in the article, the deceleration we have seen in the cloud industry has come unexpected as customers prioritize optimizing their cloud spend and are slowing down cloud migration in the near-term. There is a risk that this deceleration continues for a longer period of time or if the cloud market remains weak for longer than expected as companies continue to hold back on spending. This would bring downside revisions to Datadog’s estimates.
Macroeconomic environment
I think that while the expectation is that we might have a soft landing, there is a risk that we might see a recession in 2023. This might result in further pulling back of budgets and thus slower growth for Datadog in the near-term.
Conclusion
As we approach Datadog’s 4Q22, I think that the expectations are low given the worries about its consumption model, observability end demand and hyperscaler weakness. That said, I think that it’s important to use the fourth quarter results as a gauge for how Datadog is coping relative to the hyperscalers and whether the company’s broader base of products and applications focusing on mission critical workloads will help to offer better insulation as suggested. Management’s commentary on the next quarter sounded positive based on the last management call, while the third quarter results continued to beat expectations, demonstrating resilience in its business model.
My one-year target price for Datadog’s stock is $121. This implies 41% upside potential from the current stock price.
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