DataDog (NYSE: DDOG): Barking Up the Right Tree (2024)

Summary: A Keeper

DataDog (NYSE: DDOG) offers an observability solution, a real-time dashboard that shows the health and performance of customers' technology stack. The magical dashboard diagnoses all developer nightmares (deteriorating user experience, breaches, and all that jazz). Technology leaders can also use the platform to analyze key performance indicators to ensure data dependent decisions (shoutout to my buddy Jpow). I scratch beneath the surface with an analysis of their product with simplified use cases and excerpts from my discussion with industry contacts. Despite enjoying a solid rally following strong Q3 results, I will continue to keep the company in my portfolio as a long-term keeper. Allow me to make the case with an in-depth analysis of the following tailwinds:

1. Aggressively growing addressable opportunity for DDOG (we estimate a TAM CAGR of 16% till 2025).

2. DataDog's broad portfolio to continue gaining market share with ongoing vendor consolidation among observability customers.

3. Cross-sell opportunity (~27,000 existing customers) to drive ARPU growth.

4. Strong product velocity (entering adjacent markets, e.g. AI observability & cloud cost monitoring) will also grow revenue.

5. Balance sheet strength and management's track record of sound execution.

These factors amalgamate into my target price of USD 140/share, representing 15% upside from current levels. Valuation methodology is explained in thorough detail at the end of the print.

Introduction: The Contexed Story

DataDog provides customers with a big picture view of everything happening with their data and the servers they own or rent, allowing teams to work more efficiently and avoid unexpected surges in usage and cost. In order to gain a deeper understanding of the business, we need a brief history lesson to understand the context.

The 2010s was a decade of disruptionwhich came with an exponential rise in the diversity of computer engineering techniques. Combined with the virality of mobile applications, the intricacies of developing & deploying software evolved. The need to comprehend, troubleshoot, and optimize these technology systems prompted the creation of observability solutions like DataDog.

This type of software enabled decision makers to gain oversight of the technology being used, to identify areas of underperformance. There are three prongs of an observability solution: infrastructure monitoring, log management and application performance monitoring. Think of observability like a doctor's checkup: Metrics are your vital signs (your pulse rate, blood pressure etcetera); Logs are your patient history, detailing symptoms and events; Traces are the doctor's examination, tracking what's causing you the discomfort. Just as a doctor uses these tools to diagnose and treat, observability solutions help diagnose and fix issues in digital systems (minus the long queues).

DataDog was launched as one of the first cloud-native infrastructure monitoring solution in 2010. To simplify, this meant that DataDog allowed you to monitor performance of infrastructure (servers, networking bandwidth and more) you were renting from cloud providers like AWS. This was timed perfectly at the dawn of the cloud revolution because monitoring solutions of the time only exited for on-premises (servers you owned) infrastructure.

After raising USD 94.5 million in January 2016, the company extended into application performance monitoring in late 2016 to upgrade themselves from a mere stethoscope to a full-fledge physician (to use the previous analogy of observability being a doctor’s appointment). With theiracquisition of Logmatic.io in 2017,the company was one of the earliest players to offer a complete suite of observability. Today the company is at an annual revenue run rate of over USD 2 billion dollars, with the majority of sales coming from core observability products. The management provided a revenue breakdown for the first time in their 2023Q3 earnings call:

• Infrastructure monitoring crossed USD 1 billion in annual run rate, ~46% of the total.

• Application Performance Monitoring and Logs are ~23% each, just over USD 500 million each.

• The remaining 9% stems from adjacent markets including Developer Experience and Security.

Executing well on their first mover advantage in observability software, DataDog dominates the market today as illustrated in YoY topline growth chart below:

The bolded white line for DataDog exhibits a revenue CAGR of 60% since 2018, expected to reach USD 2.1 billion for 2023. Datadog stands out from its competitors due to its user-friendly approach to cloud monitoring and observability.The moat for DataDog, in my opinion, is the high switching cost for customers as it costs more to shift platforms rather than continuing operations on DataDog. These costs are both the direct costs associated with egressing data away from DataDog as well as the indirect expenses related to additional technical expertise required to adopt open-source alternatives. Additionally, the company also distinguishes its products with over 650 integrations, one of the highest among peers.

Software is Eating the World: The Opportunity Expands

"Software is eating the world," as put by the venture capitalist Marc Andreessen, this statement is as true as it was 12 years ago. From disrupting legacy businesses to enhancing human productivity, software continues to increasingly become an integral component of producing goods and services across all global economies. In today’s digital age, SaaS companies sell their services over the internet (think Uber, Netflix, Spotify) to millions, if not billions, of users around the world. All the companies of today (and of the future) need various software to seamlessly deploy their respective services.

Monitoring solutions areintegral for any software stack, allowing heightened insights to conveniently resolve underperformance issues. Philosophically, this is an expanding market as businesses rely more on digital systems, the demand for observability solutions is set to rise. These tools help companies understand and optimize their digital operations, making them essential for ensuring reliable and high-performing systems. I use the following forecasts from IDC's Black Book to pencil out the total addressable market for DataDog products: Cybersecurity Analytics, Intelligence, and Orchestration, IT Service Management (ITSM) Software and IT Operations Management (ITOM) Software.

Their opportunity is expected to grow at a CAGR of 16% from USD 36 billion to approximately USD 47 billion by 2025, representing ample opportunity for DataDog to grow.

Market Share gains: Platform Play & Vendor Consolidation

Datadog's management has been able to execute well on their platform play, which revolves around providing a complete and unified observability platform.Unlike traditional monitoring tools that focus on specific aspects of infrastructure, Datadog provides a single platform that collects and analyzes data from various sources, including servers, cloud containers, networks, and serverless functions. This unified view enables DevOps teams to identify and resolve issues more quickly and efficiently, leading to improved performance and reduced downtime. This one-stop solution has fared well with customers across verticals, including France's state-owned railway operator SNCF,real estate brokerage Compass, and food delivery champion Delivery Hero.

Their platform centric approach has been a success with customers, as illustrated in the market share diagram below. DataDog sat at 21% market share among public peers in 2021, which has accelerated to 25% for 2023.

According to the 2023 Gartner Magic Quadrant for Observability, DataDog has "a broad portfolio of solutions for monitoring, with an integrated look and feel and common UI across components. This common user experience increases operator efficiency, reducing the need to context switch between different products." That’s nerdspeak for DataDog’s platform being the absolute killer both in terms of completeness of vision and ability to execute.

This reigned true in my own due diligence as well, as I conversated with industry professionals in my circle.One of my great friends, employed at a GCC-based technology company, shifted away from the open-source software Promethus and adopted DataDog. Alternatives assessed were Dynatrace (NYSE: DT), New Relic, Honeycomb and Lightstep. My connection revealed that their decision was based on the added functionality and an intuitively easy UI offered by DataDog.

Another tailwind for DataDog to gain market share is the vendor consolidation phenomenon.In today's economic climate, where technology companies are facing increasing pressures to reduce costs and improve efficiency, vendor consolidation is becoming increasingly attractive. By consolidating their software vendors, businesses can simplify their IT environments, reduce licensing and support costs, and gain better visibility into their IT operations. DataDog's complete suite of products, coupled with the ease of use, makes it an ideal candidate for customers to consolidate their spend on.

Success of Land in Land-and-Expand

Anet dollar-based net retention rateconsistently exceeding 120% is the symbolism of DataDog’s monstrous go-to-market strategy. Despite a bleak outlook for software spend in the last couple of years, DataDog has consistently been able to keep their net retention rates close to 120%, which essentially means that their customers are spending 20% more today than they were a year ago. I believe that this number will stay above 120% in the near term and may go above 130% as the global macroeconomic outlook improves in 2024.

Additionally, their bottom-up approach of marketing to developers, system administrators and engineers and let their platform sell its way to the top has grown the customer base at a CAGR of 24% for the last five years to 26,800.Large customers, as categorized by customers with over $100,000 in annual spend, grew at a CAGR of 38% to 3,130for the same period. With such a large base of customers and a wide breadth of products offered by DataDog, the company is now in the “expand” phase of their land-and-expand strategy. In my opinion, the next stint of growth will be derived from cross-selling products to their existing customer base.I expect average revenue per user (ARPU) growth in large customers to be an important revenue driver in the coming years.

Product Velocity: Entering Adjacent Markets

DataDog has a phenomenal product velocity, which is especially important in today's dynamic technology landscape. As illustrated in the graph below, DataDog spends more on GAAP R&D than GAAP S&M (~47% vs 38%, as illustrated above), which appears out of sync with the rest of my infrastructure software universe. This relatively lower S&M expense reflects well on the management's cost control mechanisms. However, the more important consideration is their product velocity. I am confident in DataDog’s ability to release complementary products in adjacent markets to diversify their revenue base in the medium to longer term.

DataDog's focus on product velocity is well-aligned with the future of the infrastructure software market, which is expected to continue evolving in the coming years. My conviction lies in the belief that DataDog has positioned itself to thrive in this dynamic future. The past year has seen a notable acceleration in their product velocity, notably with the introduction of AI Observability and Security products. I believe that these strategic moves exemplify DataDog's commitment to innovation, with the following as pivotal in expanding their competitive edge:

Example 1:AI Observability

As AI -leads the wave of innovation (especially with productivity software), DataDog announced products geared towards next generation AI customers earlier this year. These products include Large Language Model monitoring to identify performance issues in these models (prompt lengths, API latencies etcetera) and model catalog which gives customers a centralized view of all generative AI models, along with their usage and costs. In their earnings call for the third quarter of 2023, the management reported that their products generated 2.5% annual recurring revenue (ARR) from next-gen AI customers. This is just the beginning, as the adoption of AI continues to accelerate, I believe that DataDog is a key beneficiary of the dollars flowing into the AI ecosystem.

Example 2: Monitoring as a form of cloud cost control

With cloud computing costs running away from CIOs, vendor lock-ins with hyperscale cloud providers have been a point of contention for some time now. Gartner estimates that 60% of infrastructure and operations leaders will encounter public cloud cost overruns due to lack of comprehensive view into cloud environments. Cloud cost controls have been thoroughly discussed and encouraged by investors as technology companies shift their focus on profitability. In today’s world of cloud cost optimizations, a mistake as meagre as storing some extra data in the cloud can be billed by tens of thousands of dollars. To this end, DataDog’s observability tools come with cloud cost management which provides insights for the decisionmakers to optimize costs without diminishing productivity. I believe that this embrace of FinOps shows very clearly the philosophical direction that the company has taken to become an auditor for cloud costs. In my opinion, there is no better tool than the monitoring service which already scrutinizes the functionality of the system.

Another positive for the company is the strong balance sheet, as the company has a net cash position of USD 1,445 million. Having little leverage gives DataDog more financial flexibility and autonomy to invest in growth and innovation. An additional benefit is, cetris peribus, the company will continue to benefit from interest income from their marketable securities of USD 1,894 million. Interest income for their latest quarter was USD 30 million, approximately 5.4% of their total revenue at an annualized interest rate of 6.3%. The company's deferred revenue (services that the company is contractually obligated to fulfil) has also trended upward historically, currently close to USD 600 million dollars.

We expect DataDog to have Average Revenue per User (ARPU) of $74,300 for this year, which has grown at a CAGR of 21% since 2019. The company has also exhibited excellent operating leverage as their Operating Margin (non-GAAP) increased from 0% in 2019 to 19% in 2023. As the company continues to scale, I believe this number will stabilize around 30% at terminal levels. As previously mentioned, the company has a restricted SG&A expenditure which makes the 30% operating margin seem easily attainable. All of this should flow down to their earnings translating into shareholder value for the coming years.

Downside Risks

• Monitoring tools from hyperscale cloud providers may become more attractive with price reductions and bundling.

• New entrants and private equity-backed companies may pose a competitive threat to DataDog’s leadership position.

• Deteriorating macroeconomic condition may adversely impact overall cloud spending and valuations.

My Target Price of USD 140/share is based on the simple average of two valuation methodologies:

• Intrinsic value of USD 145/share is based on a 10-year DCF model with a 10% weighted average cost of capital and 4% perpetual growth beyond my investment horizon. My analysis assumes a revenue CAGR of 18.7% and Adjusted EBITDA to stabilize around ~40% of revenue as the company continues to scale.

• We use enterprise value to revenue (EV/R) to factor in the comparable equities' revenue growth potential in my analysis. For my high-growth software universe (SNOW, CRWD, DDOG, NET, TEAM, NOW, MDB), the median EV/Rev multiple is around 18x. With no premium or discount over these companies, I assign the same revenue multiple (despite having above average margins) for DDOG. With my 2024 revenue expectations, the target price from relative valuation is USD 136/share.

Conclusion

I believe the company is strategically positioned to benefit from several tailwinds in the medium to long-run, including increasing cloud spending and AI adoption. I expect the company to retain its lead as a DevOps favorite and continue to gain ground in an already expanding market. I also believe that a greater focus on FinOps (cloud cost management) can also offer some upside to earnings. I remain bullish on the stock and will continue to add to my position at every given opportunity.