Datadog Stock: Growth Triad Holds Strong, AI Expansion, TAM, Profitability (NASDAQ:DDOG)

Monty Rakusen Investment Thesis AI has been the coolest thing to talk about during conference calls through last year as companies vie for investor attention and capital in one of the hottest phases of technology in the longest time. According to FactSet, AI was discussed at least 177 times across earnings calls, reaching its peak in 2023 during Q2 last year. This year created a new record as companies discussed AI almost 200 times across conference calls, according to FactSet. That does not necessarily translate to results, as can be observed by the recent earnings performances put up by Salesforce (CRM), MongoDB (MDB), and UiPath (PATH), who have all been touting similar AI tailwinds through last year. As we enter the second year of GenAI, companies will be strongly judged on not just the amount of capex dollars being deployed towards AI but also on the volume of revenue that can be directly traced back to AI, giving investors a measurable way to track the company’s performance directly through AI. Fortunately, Datadog (NASDAQ:DDOG) is one of those companies that has started to break out their earnings performances and attribute portions of their ARR to AI. While still at nominal levels, I believe AI is one of the pillars leading Datadog into a continued phase of TAM expansion/penetration backed by strong profitability. However, with most of the gains still priced in, I am still holding out for Datadog to drop lower and, for now, will attach a Hold rating. Recap of Datadog’s business from the AI lens In my first coverage of Datadog, earlier this year, I detailed how the company’s telemetrics and observability cloud software makes it “easier for backend technology teams such as DevOps and SecOps teams to gain more visibility into the inner workings of their organization’s technology tools, systems, and applications.” The company is still going strong with their cloud-based offerings focused on managing & monitoring application performance, logs, etc. Over the past year the company’s cloud products have evolved at all the three subsets of their cloud platform to harness and integrate AI and continue towards their vision of creating a “unified” platform for one source of comprehensive truth about the enterprise’s cloud. Here’s a slide from the company’s Investor Day presentation that diagrammatically explains how Datadog has integrated AI across their platform. Exhibit A: How Datadog embeds AI into its platform of cloud observability offerings (2024 Investor Day, Datadog) Datadog’s products made it very convenient for developers to understand various aspects of their cloud from a performance and maintenance standpoint. Datadog’s AI products such as WatchdogAI and BitsAI appear to make it even easier since these products act as copilots for the enterprise while also increasing productivity, per my observation. These products and integrations specific to AI were already launched last year and appear to have provided some boost to Datadog’s ARR. AI’s nominal contribution to Datadog has significant room to grow Over the past five years, Datadog’s revenue has grown at an astonishing pace of ~48% CAGR since 2019, per its investor presentation. In that phase of growth, Datadog’s cloud observability products found robust appeal with customers as the pace of digital transformation and cloud adoption quickened. Exhibit B: Datadog’s revenue grows at an astonishing 48% CAGR rate since 2019 (Q1 FY24 Investor Presentation, Datadog) The 49% CAGR also includes management’s revenue guidance for FY24. In FY24, the company sees revenue growth slow down to ~23% this year. There are two reasons I believe investors would be wrong to assume that growth would terminally slowdown from here. First, the slowdowns demonstrated by Salesforce and others indicate that general deployment of AI and subsequent products will not be accretive for technology companies in the long term. In Salesforce’s example, the company said they saw “customers delaying or slowing projects,” while seeing “strong demand for Data Cloud and multi-cloud adoption.” To me, this indicates there were sudden IT spending adjustments in Salesforce’s legacy products, such as customer CRM and customer support projects, that caused the slowdown. In Datadog’s case, the DevOps and DevSecOps target markets remain strong, with no sign of disruption from AI and IT spending remaining healthy. According to Gartner, the TAM is expected to grow at 11% CAGR for ITOM and 16% CAGR for cloud security, both larger markets within which Datadog operates. Second, Datadog has been rapidly deploying products in the still-nascent AIOps market. Until May of this year, Datadog had launched its Bits AI and other AI tools in beta state, available only to select customers, as revealed on the earnings call. On the same earnings call and at recent conferences like the BofA GTC conference, management revealed that AI now accounts for 3.5% of the company’s ARR, growing 50 b.p. since the previous sequential quarter. While the company was also quick to taper down excitement, management did provide some more guidance on what investors can expect from the company: We said 3.5% of the ARR. So there’s evidence that there’s activity but not mass adoption yet that has manifested itself into a change of the workloads. We actually don’t care. We sell based on sort of capacity you use. And so any way the client wants to use that, whether it be to monitor LLMs or do logging or look at network or databases would be part of our contract with the client. So I think we’re early days, and we don’t know how it’s going to go, but there’s good evidence of activity in these different directions. I would also like to point out that the 3.5% of the ARR number that Datadog announced was before May of this year. In May, Datadog announced the general availability of its Bits AI copilot product, and I expect an increase in revenue growth based on the progress the company has already demonstrated while Bits AI and other AI products were in beta. Upgrading my outlook on Datadog operating leverage Another takeaway from my observation based on management’s commentary from the BofA GTC conference that I attached earlier is their perspective on how higher usage of AIOps tools by Datadog can boost capacity and consumption. Datadog is a subscription-based business, but their pricing menus and strong product platform incentivize customers to spend an additional delta by buying incremental products such as “additional containers to monitor, custom metrics packages, anomaly detection, and app analytics,” that are all based on usage (taken from their 10-k). In the latest earnings report, Datadog now sees operating margin remaining on an adjusted basis for the year, as shown in the table below. Operating Leverage FY19 FY20 FY21 FY22 FY23 FY24E Adj. Operating Income -$5 $64 $165 $326 $490 $595 Adj .Operating Margin -1.5 11% 16% 19% 23% 22.90% Click to enlarge Their FY24 outlook already reflects a raised outlook as compared to their previous guidance of 21.2% adj. operating margin. I believe that as products such as Bits AI move out of the gate and get widely adopted, the consumption of Datadog’s platform will increase, leading to higher revenue and operating margins. Plus, Datadog continues to demonstrate increased usage in terms of products across its platform as users buy into the company’s multi-product approach, keeping users on the platform. I had mentioned this earlier in a coverage where customers are “expanding their adoption of Datadog’s products from 2+ and 4+ products to 6+ and 8+ products.” Unfortunately, Datadog looks fully priced at the moment My model suggests that Datadog is astonishingly fully priced for future growth at the moment. The company presented their long-term plans at Investor Day, which aim to track +25% operating margins over the long-term. I have already explained in previous sections why I am raising my revenue outlook for Datadog based on the performance of Bits AI and other AI products in beta. As Bits AI becomes generally available, I expect this to also push their operating margins higher. Therefore, I now see adj. operating income growing at a CAGR of 29% CAGR faster than the ~25% CAGR revenue growth. In terms of shares, I will assume the ~2.5% share dilution rate set by management, while the 9% WACC calculation can be found here. Exhibit C: Datadog’s valuation shows the stock is priced in (Author) If I compare Datadog’s growth rates to the S&P 500, I believe a forward PE of ~55 is warranted, ~60 if investors are even more optimistic. At these valuation levels, I still do not see enough upside for me to recommend buying the stock here. Risks & Other factors For now, the software spending slump appears to be contained in a certain segment of the cloud software market, mainly among companies such as Salesforce, UiPath, and others such as MongoDB. I had mentioned my reasoning earlier for the slowdown that Salesforce had referred to. However, if the spending slowdown broadens across all cloud software, Datadog would see headwinds as well. I don’t believe that is the case yet, as can be seen in the performance strength demonstrated by Adobe, another legacy cloud software company operating in a different cloud software market than Datadog. Cloud spend appetite will be crucial to the positive outlook I have for Datadog. Takeaway The company is fundamentally in a strong position to expand quickly into AIOps, which is a relatively new market, thus expanding the company’s TAM. But despite the stellar performances and strong outlook that I have for Datadog, I believe the company’s investors are quite optimistic about the stock already, based on pricing and anticipated growth. For now, I will rate Datadog as a Hold and watch for potential catalysts in management’s commentary or product usage patterns before I turn optimistic on the stock.