You don't have to look far to find someone singing the praises of big data -- and I'm one of them. In today's connected world, we have more of it than at any point in human history. Imagine the possibilities!
But there's a dark downside to this bounty of information. It's increasingly easy to be fooled by, led astray by, and act with false confidence because of ... data. Trader and author Nassim Taleb put it best when he said:
More data means more information, but it also means more false information.
Let's say there's a 1-in-100 chance of getting a false positive when analyzing a set of data -- having the appearance of a pattern emerge that's really a random artifact or no pattern at all. If you have a limited quantity of data to work with, you might get one "false positive" per year. But once your data set becomes exponentially larger -- as it has for many businesses -- then you will find yourself awash in such false positives.
A software-as-a-service (SaaS) company that I recently invested in -- Datadog (DDOG 0.34%) -- is helping people make sense of all this data.
Image source: Getty Images
The company, in one short story
Olivier Pomel and Alexis Le-Quoc worked at Wireless Generation, which aimed to help K-12 teachers make better decisions with the help of data. Olivier worked on the development side (building things), while Alexis was head of operations (making sure they worked).
In their time there, they realized something: It was almost impossible to communicate with different departments without a shared set of data and a common vocabulary. That motivated them to found Datadog with a simple but profound mission: "to bring sanity to IT management."
The company does this by offering four broad subscriptions, each of which shares a common goal: to provide a single, real-time, unified data platform everyone can see.
- Infrastructure: Monitors how your cloud operations are performing.
- Application performance management (APM): Monitors how the individual apps running on your infrastructure are doing.
- Log management: Keeps track of all the information being collected.
- User experience (UX): Measures what is the experience like for customers navigating your websites.
Those are oversimplifications of what those tools do, but they're a sufficient foundation to give you an understanding of what the company does.
Pomel and Le-Quoc are still at the helm as CEO and CTO, respectively -- nine years after founding Datadog. Though they took it public in September, they still have significant skin in the game, owning a combined 22% of shares outstanding.
Providing the data guidance customers want
There are lots of ways to measure how successfully a company is accomplishing its mission. When it comes to Datadog, beyond the obvious metric of revenue levels, I like to monitor these four statistics:
- Total customers: I want to know if new companies are finding Datadog and using it.
- Customers with annual recurring revenue (ARR) over $100,000: This lets me know if users really like Datadog. If they didn't, they wouldn't fork over so much for its services.
- Customers with ARR over $1 million: Same as above, with higher threshold.
- Dollar-based net retention (DBNR): This monitors how much a specific cohort of customers spends from one year to the next. If it's well above 100%, that's a strong sign that the company has a competitive moat, possibly due to high switching costs.
Here's what the numbers look like for Datadog:
| Metric | 2017 | 2018 | Trailing 12 Months | Growth Rate |
|---|---|---|---|---|
| Revenue | $101 million | $198 million | $311 million | 90% |
| Customers | 5,400 | 7,700 | 8,800* | 38%** |
| Customers with $100,000-plus ARR | 240 | 450 | 727 | 88% |
| Customers with $1 million-plus ARR | 12 | 29 | 42* | 131%** |
| DBNR | 141% | 151% | 146%* | N/A |
Data source: SEC filings. *These figures are accurate as of July 31, 2019, and were not updated at the end of the third quarter. **These growth rates calculated over 18 months instead of 21 months. Growth rate = compounded annual growth rate, or CAGR
My thinking here is pretty straightforward: Datadog couldn't achieve these kinds of results unless its technology was providing value to its customers. As companies start using more and more of Datadog's technology, they come to rely on it more, creating the aforementioned moat due to high switching costs.
Given the ever-growing quantities of data being collected by businesses, I have little doubt that Datadog will continue to come out with new tools. In their IPO prospectus, they mentioned a plan for a fifth broad subscription: network performance monitoring. Such an option provides additional opportunities for Datadog to fulfill its mission of providing sanity in IT management.
The takeaway for investors
Of course, investing in newly public companies like Datadog isn't for the faint of heart. Such stocks can often rise or fall by double-digit percentages on the slightest hint of news. That's why -- when I bought shares -- I managed my allocation appropriately: it currently accounts for just 2.5% of my holdings.
If you're interested in owning a piece of a fast-growing SaaS company that's helping make sense of the world's data -- and have the stomach to cope with volatility -- I'd suggest you consider doing the same.
