By any measure, Datadog is an incredible entrepreneurial success story. The company went from a tiny startup in 2010 that had trouble raising money, to a public company that, at the time of writing, has a market capitalization of $12.5B. It was a pioneer in the category of DevOps and observability, and it’s now a clear leader. With revenues hovering around $350M, it has 1,300 employees across 31 locations around the world.
Perhaps improbably, the founders built the company out of New York, which many people over the years have thought of as a hub for adtech, media and commerce startups only. Along the way, they faced a lot of skepticism: “Whenever we pitched West Coast investors it was sort of seen as a form of mental deficiency to be based in New York and doing infrastructure“, says Olivier. I wrote a few months ago about the significance of the Datadog IPO for the ecosystem and beyond. Ironically, out of the three top public tech companies in New York today, two are infrastructure software companies (Datadog and MongoDB).
Not one for gratuitous self-aggrandizing, Olivier has given surprisingly few interviews over the years, and it was a real treat to sit down with him for a fireside chat in front of a packed house of 350 attendees at our most recent Data Driven NYC.
We had an in-depth conversations and covered a lot of topics.
The first half of our conversation was focused on Datadog itself, starting with a high level overview of the observability and DevOps space to make the discussion approachable by people who don’t know the space.
The second half of the conversation was focused on all sorts of lessons learned along the way of building a major company- sales, marketing, fundraising, etc.
Below is the video. We have also provided a full written transcript to make the content easy to scan through (many thanks to Karissa Domondon for her help with this).
No longer. But, also, kinda, yes… It’s complicated.
When people talk about “fundraising seasons”, they mean that there are certain times of the calendar year when you should be running your fundraising process. And conversely, there are times of the year when you shouldn’t, because venture capitalists won’t be paying attention.
Fundraising can feel like an awful lot of pushing. You push to get an introduction to investors, you push to get them to commit to a meeting, you push to convince them, you push to get them to issue a term sheet. Push, push, push. Historically, and for most people still, “push” has been the default mode.
But as an industry, we live in interesting times, and there’s more of an opportunity for founders to be in “pull” mode, a situation where investors come to you and do the courting and convincing – obviously, a much better position to be in for founders, especially when the investor is senior enough to write the check.
(This is the fourth post in this fundraising mini-series: quick, simple ideas that I’ve used in various fundraising conversations over the years, that I’m sharing here, one by one)
If there’s one tactical topic everyone seems to have a strong opinion on when it comes to fundraising, it’s whether entrepreneurs should be actively talking to new VCs *in between* rounds of financing, for relationship building purposes.
Many founders have had the same experience: something public or semi-public comes out about your company (a funding announcement, a press article, a blog post, a tweet, even a LinkedIn update of some sort…) and, voila, your inbox starts filling up with emails, typically from VC firm associates saying that they “heard good things” about your company and would “love to catch up”. At first, it may be vaguely flattering, but as more emails pile up, it gets tedious, sometimes overwhelming. And perhaps slightly annoying: everyone says you’re supposed to get a warm intro to a VC, but then VCs can just email you cold, and somehow they expect you to drop everything you’re doing to talk to them? Sheesh, the nerve.
Our most recent VC guest at Data Driven NYC, Mike Volpi of Index, has had a pretty amazing last couple of years, with three of his venture investments going public: Zuora, Sonos and Elastic.
Before becoming a VC, Mike ran Cisco’s routing business where he managed a P&L in excess of $10 billion in revenues, and acquired over 70 companies (note: probably a pretty good way to make a lot of friends in Silicon Valley).
A partner at Index Ventures in San Francisco, Mike invests primarily in infrastructure, open-source and artificial intelligence companies, so he was a perfect guest to have at the event. In particular, he invested in two prior presenting companies: Confluent and Cockroach Labs (in which FirstMark is also an investor).
We had a really interesting conversation about open source, AI and venture capital. Here’s the video below, and l have jotted down a few notes as well, below the fold.
(This is the third post in this fundraising mini-series: quick, simple ideas that I’ve used in various fundraising conversations over the years, that I’m sharing here, one by one)
You’ll often hear VCs recall how they knew they wanted to invest in a startup within the first 10 minutes of a one-hour pitch meeting with the entrepreneur.
For this to happen, a lot needs to align, both in terms of fit (right company for the right investor at the right time) and intrinsic merits of the opportunity (quality of the founding team, metrics, etc). But ultimately investors describe the experience less as checking a lot of boxes, and more as something akin to a state of flow: seeing, through the eyes of a founder, a future that is both exciting and inevitable.
Best-selling author, Professor of Computer Science at the University of Washington, recent recipient of the prestigious IJCAI John McCarthy Award for excellence in artificial intelligence research (among other awards) and Head of the Machine Learning Research group at D.E. Shaw: Pedro Domingos has one of the most incredible resumes in the world of AI, and we were thrilled to host him for a fireside chat at our most recent Data Driven NYC.
We covered a bunch of things, including why finance is a killer app for machine learning, his much-lauded book, ‘The Master Algorithm’ and what’s truly scary about AI (hint: not the Terminator).
Last year, Sarah Guo made news by becoming the youngest General Partner at Menlo Park firm Greylock Partners, and we were delighted to host her at our most recent Data Driven NYC.
Greylock is one of the oldest firms in venture capital, notable in particular for its investments in Facebook, LinkedIn and AirBnB. Greylock has also actively invested in the data ecosystem, including in a number of companies that presented at Data Driven NYC over the years: Cloudera, Sumo Logic, Trifacta, Instabase, etc.
Sarah is mostly focused on enterprise, SaaS and security investments, and we got into a bunch of interesting topics during this conversation.
(This is the second post in this fundraising mini-series: quick, simple ideas that I’ve used in various fundraising conversations over the years, that I’m sharing here, one by one)
Much of the frustration that startup founders experience about fundraising is due to the lack of clarity around two simple questions: “What do investors want?” and “How do they make investment decisions?”
Part of what makes the exercise such a “black box” is that the answer is often “it depends”. Investment decisions are made by humans, based on imperfect information, in an environment that constantly changes.
In addition, parameters evolve with each round: different expectations, criteria, and processes, and often different venture firms. You may feel you’re building the same company all along, but investors at different stages will be looking at it in very different ways.
As a starting point to understand how investors (angels and VCs) make decisions, one simple framework that I find myself using in conversations about fundraising is “art vs science”.
Should we be worried about the prospect of AI superintelligence taking over the world?
“In the real world, current-day robots struggle to turn doorknobs, and Teslas driven in ‘Autopilot’ mode keep rear-ending parked emergency vehicles […]. It’s as if people in the fourteenth century were worrying about traffic accidents, where good hygiene might have been a whole lot more helpful”.
This is one of my favorite quotes from “Rebooting AI: Building Artificial Intelligence We Can Trust,” a new book by Gary Marcus – scientist, NYU professor, New York Times bestselling author, entrepreneur – and his co-author Ernest Davis, Professor of Computer Science at the Courant Institute, NYU.
Gary did us a big honor recently: he chose to speak at Data Driven NYC on the evening of the publication of the book. He also signed a few copies. Our first book launch party!
Particularly if you’re trying to make sense of the still-ongoing hype around AI, including predictions of global gloom, Gary’s book is a fantastic read: a lucid, no-nonsense and occasionally provocative take on the current state of AI, that distills complex concepts into simple ideas, and includes plenty of interesting and often funny anecdotes.
For founders thinking through fundraising, here’s a simple mental model I like:
“If this was a product launch, instead of a fundraising process, what would you do?”
Almost by definition, founders are very passionate about launching new products, and a lot of it comes instinctively. That’s often less the case for fundraising, sometimes considered as a counter-intuitive chore.
I haven’t written much on this blog about fundraising over the years, in part because there’s already so much good content on the topic out there.
But each time I get a chance to participate in tech community events, which I have done a fair bit in the last 9-12 months, I’m reminded that, for many founders, fundraising is as opaque and ambiguous a process as ever.
The venture financing landscape keeps shifting: dislocation of the traditional seed/A/B/C path, lots of new funds, older funds that evolve their strategies, long bull market (for now), increasing bifurcation between the “haves” (startups that can literally raise billions of dollars of venture money) and “have nots” (the many others that can’t get a simple financing done), etc.. New generations of entrepreneurs arrive on the scene all the time, and have to make sense of a complex process in this shifting environment.
As a result, for all press about quick oversubscribed rounds and mega-financings, most founders experience a good amount of head scratching and frustration.
So I’m going to do my bit to help clarify, and share a few models and ideas I have learned along the way, in the hope that some entrepreneurs may find it helpful.
In its largest acquisition since Oculus in 2014, Facebook just announced last night it acquired CTRL-labs, a 4 year old startup based in New York, for a reported $500M-$1B.
Coincidentally, CTRL-labs CEO, Thomas Reardon (who goes by Reardon) was our guest at Data Driven NYC just a couple of weeks ago. Reardon is a particularly compelling entrepreneur, and this was a fascinating fireside chat, where we dove into machine learning, neuroscience, VR and all sorts of cool topics.
CTRL-labs builds what it calls “neural interface technology”: algorithms that decode the activity of individual motor neurons and turns that into control over machines, thereby completely redefining the interaction between humans and machines. Because the technology captures your intentions without requiring any physical movement, you can do things that you could never do by moving, and you can start “imaging experiences where you would have 20 fingers… or 8 arms or legs”.
The video (below) is well worth a watch in its entirety, including the audience Q&A at the end, and I’ve jotted down a few notes as well, for a quick review.
The Datadog IPO just happened, and it’s proven to be a resounding success, not surprisingly given the company’s superb metrics – big revenues ($333M ARR), happy customers that keep buying more (146% net revenue retention) and, unlike many others, a history of profitability. To make the story even more epic, it transpired that the company had turned down a last minute big acquisition offer from Cisco shortly before the IPO, which valued the company higher than its proposed IPO range.
While I’m a small personal shareholder in the company and friendly with its founders, this is not going to be a VC victory lap kind of a post, for the simple reason that I did not invest in the company as a VC (as the early rounds of financing took place before my current tenure, in my defense!).
Regardless, I wanted to write a few quick thoughts, as I believe this particular IPO should be loudly celebrated.
I’m excited to announce that FirstMark has led a $12.5M Series A investment in Crossbeam, alongside Salesforce Ventures and Hubspot Ventures, with existing investors Uncork, First Round and Slack Fund participating.
At its core Crossbeam is a data escrow service. It allows companies that are partnered with each other (or looking to be) to combine their data sets (mostly customers and prospects) in a secure, trusted, compliant way, into a third party data warehouse (Crossbeam). They can then run analytics, without exposing the raw data behind the scenes, to identify opportunities to partner together.