Playing “fake VC” (or the portfolio approach to getting a job in venture capital)

How does one get a VC job?

Method 1:  Start a tech company, drive it a multi-billion dollar success. Drop a few bon mots on Twitter to your robust group of followers, make visionary statements during your TechCrunch Disrupt fireside chat, and build a reputation as a helpful mentor to entrepreneurs.  Then wait by your phone as major firms call you with General Partner offers.  Or start your own firm.

Method 2: Welcome to the long hard slog.  And read on.

The good news is that it’s a great time to get into venture capital.  While venture capital remains a small industry with comparatively few openings, many VC firms have raised a lot of money lately, so they need more people to help them deploy it.  A number of investment analyst/associate positions are advertised (or were recently) – for example, we just posted a new opening at FirstMark, see here.  I’m also aware of several General Partner-level searches being conducted right now.

Ok, but how do you get those jobs?  Ask any VC, and they will tell you that they get that question all the time, and I’m no exception — in fact, I’m not-so-secretly hoping that this (long) blog post will help cover 80% or so of the content discussed in the frequent conversations I have on the topic, so I can focus on the 20% that’s specific to each person’s circumstances.

It’s not just the odds that make the topic complicated – it’s also that that there’s no single or sure-fire path to the job. Continue reading “Playing “fake VC” (or the portfolio approach to getting a job in venture capital)”

Sketchfab and the democratization of 3D content

We’re about to see a lot more 3D content in our digital lives.  Various trends, some years in the making, are now intersecting to make this a near-term reality.

On the production side, 3D has of course existed for many years – this has been, in particular, the world of Computer Aided Design (CAD), which originated in part from MIT’s Sketchpad project in the early sixties.  In one form or another, 3D has been used as a professional format across many industries, such as architecture, engineering, construction, and entertainment. Creation of 3D content (even for consumer-facing products like gaming) has remained largely the province of a comparatively small group of specialized professionals. Continue reading “Sketchfab and the democratization of 3D content”

Hardware Startups: The VC Perspective

Among all the excitement for the Internet of Things and the resurgence of hardware as an investable category, venture capitalists, many of whom new to the space, have been re-discovering the opportunities and challenges of working alongside entrepreneurs to build hardware companies.  Below are the slides that David Rogg and I prepared for the recent Connected Conference, a great global event held in Paris.  They’re a good snapshot of how someone like me thinks about the hardware space, mid-2015.



The “Straight to A” Round

The venture financing path has evolved incredibly fast over the last 18 months. In this very busy financing market, what used to be a reasonably well understood progression from a seed round to a Series A to a Series B, etc. has now morphed into a more complex nomenclature of pre-seeds ($500k or less), crowdfunding rounds (especially for hardware), seeds ($1M-$2M, 6-9 months after the pre-seed), seed primes (an extra $1M or so, 12-18 months after the seed), Series A (now routinely $10-$12M in size, occasionally up to $15M), Series A-1, Series B, C, D, E, F etc. (as companies remain private longer).

The latest entrant in this rapidly evolving nomenclature seems to be what I’d call the “Straight to A” round, where the founders skip the seed stage altogether and raise directly a $5M-$10M Series A, often before building anything, sometimes even before incorporating a company. I had seen it here and there in the past, but it now seems to have become an accelerating trend. Continue reading “The “Straight to A” Round”

The Astounding Resurrection of AI [Slides]

A few days ago, I was invited to speak at a Yale Entrepreneurship Breakfast about about one of my favorite areas of interest, Artificial Intelligence.  Here are the slides from the talk — a primer on how AI rose from of the ashes to become a fascinating category for startup founders and venture capitalists.  Very much a companion to my earliest post about our investment in   Many thanks to my colleague Jim Hao, who worked with me on this presentation. and the emergence of the AI-powered application

AI is experiencing an astounding resurrection.  After so many broken promises, the term “artificial intelligence” had become almost a dirty word in technology circles.  The field is now rising from the ashes.  Researchers who had been toiling away in semi-obscurity over the last few decades have suddenly become superstars and have been aggressively recruited by the largest Internet companies:  Yann LeCun (see his recent talk at our Data Driven NYC event here) by Facebook; Geoff Hinton by Google; Andrew Ng by Baidu.  Google spent over $400 million to acquire DeepMind, a 2 year old secretive UK AI startup. The press and social media are awash with thoughts on AI.  Elon Musk cautions us against its perils.
What’s different this time? As Irving Wladawsky-Berger pointed out in a Wall Street Journal article, “a different AI paradigm emerged. Instead of trying to program computers to act intelligently–an approach that hadn’t worked because we don’t really know what intelligence is– AI now embraced a statistical, brute force approach based on analyzing vast amounts of information with powerful computers and sophisticated algorithms.”  In other words, the resurgence of AI is partly a child of Big Data, as better algorithms (in particular, what’s known as “deep learning”, pioneered by LeCun and others) have been enabled by larger than ever datasets and the ability to process those datasets at scale at reasonable cost.

Continue reading “ and the emergence of the AI-powered application”

Lending Club IPO: Nice Guys Don’t Finish Last, and Other Lessons

The superb Lending Club success story is what the startup world is all about: a software-based reinvention of massive and inefficient industry; a product that puts consumers first and delivers undeniable benefits ; and an entrepreneurial mega-hit that brings incredible riches and returns to its founder and investors.

In some ways, Lending Club is a classic Silicon Valley story; in some other ways, it is pretty atypical. As a friend of Renaud Laplanche’s for over 20 years, I have had a chance to witness from up close some parts of his journey with Lending Club. It is full of interesting lessons for entrepreneurs and the tech industry in general.:

1.  Nice guys don’t finish last. According to some, the tech ecosystem has been grappling with a proliferation of jerks with oversized egos at the helm of very successful startups (see Pando’s “asshole rollcall” here). Whether one shares that point of view or not, Renaud is exactly the opposite of that. Kind, loyal, generous and understated, he’s the living proof that world-class entrepreneurial talent, drive and persistence don’t necessarily come associated with arrogance and low EQ.

2.  CEO focus does matter. Renaud has been focusing maniacally on his venture for the last eight years. Up until recently, he had spoken at comparatively few conferences. He doesn’t have a portfolio of cool angel investments on the side. Heck, he doesn’t even have a Twitter account.

3. Great founders can come from all sorts of backgrounds. Renaud defies a lot of current startup CEO stereotypes. He is not a technical founder. He started his career as a (gasp) corporate lawyer.   He’s a sole founder. He is French, with an unmistakable accent. Continue reading “Lending Club IPO: Nice Guys Don’t Finish Last, and Other Lessons”

The Internet of Things: Reaching Escape Velocity

An edited version of this post appeared on TechCrunch here.  A downloadable version of the chart is available on SlideShare here.

It’s been about 18 months since my original attempt at charting the Internet of Things (IoT) space. To say the least, it’s been a period of extraordinary activity in the ecosystem.

While the Internet of Things will inevitably ride the ups and downs of inflated hype and unmet expectations, at this stage there’s no putting the genie back in the bottle. The Internet of Things is propelled by an exceptional convergence of trends (mobile phone ubiquity, open hardware, Big Data, the resurrection of AI, cloud computing, 3D printing, crowdfunding). In addition, there’s an element of self-fulfilling prophecy at play with enterprises, consumers, retailers and the press all equally excited about the possibilities. As a result, the IoT space is now reaching escape velocity. Whether we’re ready for it or not, we’re rapidly evolving towards a world where just about everything will be connected. This has profound implications for society and how we collectively interact with the world around us. Key concerns around privacy and security will need to be addressed.

For entrepreneurs, the opportunity is massive. Where Web 1.0 connected computers to the Internet and Web 2.0 connected people, Web 3.0 is shaping up to be connecting just about everything else – things, plants, livestock, babies… Each new wave has spun out giant companies (Google and Amazon for Web 1.0, Facebook and Twitter for Web 2.0). Will Web 3.0 create a comparable group of behemoths?

The space has been evolving so rapidly over the last year and a half that our IoT landscape became quickly outdated. Here is a revised and updated version. A few notes: as always, and despite our best efforts, a number of great companies will be missing; omissions are completely unintentional. Also, as much as possible, we have tried to put one brand per category, although many companies probably belong to several categories. Finally, categorization of a rapidly evolving space is an imperfect exercise – we have done our best to be directionally correct, but we’re certainly open to feedback on how to make this chart better and more accurate.


Some comments on the chart:

Explosion of startup activity: With hardware incubators graduating legions of new entrepreneurs, crowdfunding in full swing and an increasing number of VCs excited about the space, new companies and products are popping up left and right. The previous version of this chart featured 199 companies – it now has 612 logos!

Big companies are very active: I’ve written this before about the connected home segment, but this is a distinctive characteristic across the board: large companies have been active in this space or closely related spaces for a long time and are showing no interest in letting themselves get disrupted by small startups. This is true for industrial companies (GE, Siemens, Bosch, Philips, etc.) as well as big tech (Cisco, Intel, Apple, Samsung, etc.). The increasing impact on the space by Google, a fairly recent entrant in the hardware category, will be a development to keep an eye on in the coming months.

M&A activity is accelerating. Since the first version of the chart 18 months ago, a number of promising startups have been acquired: Nest and Oculus, of course, but also others such as Basis, Dropcam, SmartThings, Revolv, etc. Partly as a result of this, it’s pretty striking that there are comparatively few mid- to late-stage startups in the IoT space.

A global phenomenon: Innovation in the IoT space has been happening all around the world. Europe has been very active (Withings, Sigfox, Netatmo, Berg, and many others), as have other parts of the world (Australia with LIFX, etc.).

Some areas are getting overheated: The wearables market is probably getting close to its saturation point, at least for casual/consumer products (trackers, watches, etc.). The connected home segment has seen large companies make aggressive moves through acquisitions, investments or product launches (Google with Nest, Dropcam and Revolv, Apple with Homekit, Samsung with SmartThings, GE with Quirky/Wink), and the opportunity to become the home’s central “hub” is quickly becoming a deep-pocketed player’s game.

Plenty of other areas are just getting started: Innovation is accelerating at an incredible pace in a variety of segments such as digital health (patient monitoring), “invisibles” (connected pills, connected contact lenses), augmented reality, enterprise and industrial internet (asset tracking, energy management, machinery monitoring), smart cities, robotics, connected cars, aerials (drones, nanosatellites), user interfaces, software platforms and analytics, developer tools and ecosystems, security applications, and connectivity infrastructure. Just as certain verticals have neared critical mass, new and innovative applications have been spun up and built out.

In many ways, this is just the beginning. A lot can go wrong, but we are all in for an exciting ride.

This updated chart has been a team effort at FirstMark. Many thanks to David Rogg who handled the research and heavy lifting on the chart, as well as Caitlin Graham (logos), Dan Kozikowski (interactive version) and Sutian Dong (original version).

A Few Non-Obvious Things I Learned as a New VC

I joined FirstMark as a partner a little over 18 months ago now, and it’s been a thrilling ride.  It’s also felt like a steep learning curve: lots of nuances, and lots of institutional memory to absorb.  Below is a glimpse into what I’ve seen happening “behind the scenes” on the VC’s side to the table – stuff that was not obvious to me in my former roles as entrepreneur, angel investor or corporate incubator/strategic.

1.  A real commitment.  Like for many new VCs operating at the Series A level,  the biggest shock to the system was the realization that one gets to make very, very few investments – basically two or three a year.  You quickly find yourself having to choose between a number of opportunities you really like. Making a new investment is a big deal, and a decision that one has to live with for years to come. You also get to work with an entrepreneur very closely, and live up to their level of trust and expectations.  In a way, it feels like a marriage, except one where divorce is not really an option.  There’s an occasionally brutal asymmetry between the fundraising process (which can be quick and intense, especially if it is competitive) and what happens afterwards, which is a lot of hard work over a long period of time.  Both the entrepreneur and the VC would be well advised to get to know who they’re about to work with for the next few years of their lives.  You don’t need to be friends with your VC (although friendships develop over years of working together), but you do need a core of mutual respect and commitment to hard work and excellence, as well as a shared vision of the future.


2.  Conviction, not data. Early stage VCs (seed and Series A) operate in a daunting scarcity of data points. You get a few numbers, a few meetings with the founders, and also you see a bunch of companies, so you get a sense of how an opportunity compares to others. Other than that, and for all the thinking about data driven VC investing, the reality is that investment decisions are mostly about storytelling and forming personal conviction – painting a vision of the world where a company becomes hugely important. One consequence for entrepreneurs to bear in mind: VCs are really hungry for any data point that can help them.  It’s certainly true about the “big things” (revenue, traction, etc., especially as they compare to other opportunities the VC is seeing), but it’s also true for the “small things”, which can become become disproportionately important  (particularly if they add up), as the VC is trying to piece together a story: whether that’s signs of possible greatness (e.g., your former boss really insisted on putting $50k in your new venture) or trouble (being rude to the receptionist, consistently taking forever to reply to emails, etc).


3.  Not a single way to reach conviction:  VCs come in all sorts of flavors – some successful investors are deeply analytical (build roadmaps and investment thesis, get into details) while others are more “social” (relying on networks of trusted experts they’ve built over years to help them identify signal from noise).  What’s been interesting to me is that you find very successful investors on both sides of the spectrum, and also find those different types happily co-existing within the same firm.   Naturally, everyone is also heavily influenced by their professional history (what worked for them in the past as an operator or investor), as well as all sorts of personal criteria that often have nothing to do with the intrinsic merits of an opportunity – for example, the bar for a new investment will be naturally higher if an investor is already on 12 boards and always on the brink of being overwhelmed by the amount of work they face.   For the entrepreneur, it’s always a good idea to understand who they’re pitching to, as in any sales process, as an investor’s personal circumstances and background matter immensely.


4. VC firms are not a monolith. Once an individual investor has reached personal conviction, they need to sell it internally to get the deal done.  Because of the scarcity of data points and the range of personal styles, most investment decisions can be argued either way, and they often are. VCs are opinionated people, and there’s a fair amount of disagreement behind the scenes happening at firms during the discussions leading to an investment decision, which is a healthy thing, as you need checks and balances.  Many firms have reported that the most successful investments in the long run are the ones that were initially the most polarizing internally.  Depending on the firm, internal politics may come into play as well (glad to report that FirstMark is remarkably immune to this).  But, bottom line, decisions can come out either way quite easily, so for entrepreneurs, there’s certainly a numbers game involved.  Unless no one wants to take a first or second meeting (in which case there’s probably a deeper problem), it’s quite possible to get turned down by many firms before finding the one that will say yes (which can absolutely be a bigger name firm that the ones that said no).


5.  “Deal dynamics” matter a lot.  One really interesting aspect of seeing “how the sausage is made” on the VC side is to realize that the intrinsic merits of the opportunity is only a part of the equation. There’s also this thing called “deal dynamics” that VCs talk about all the time —  basically a catch all for all sorts of criteria related to timing, valuation, competition and to some extent, stage, geography and seasonality as well.  Because they see so many opportunities, VCs need to have strong filters in place about what makes sense for them – how they think about portfolio construction, ownership percentages, etc., matters a lot.  Here as well, this means that there is a number of reasons why an opportunity may not be a fit for a specific firm which have little to do with the fundamental merits of that opportunity.  Sounds like horrible VC bullshit, but it’s very true: a VC’s decision to “pass” is quite often not personal.


6. The VC world is really small.  While there are thousands of startups around at any point in time, there are only a few hundred active VC firms, which typically only have a handful of General Partners.  People come in and out of the industry all the time, VC firms rise and fall, but for the most part, the core remains the same and many people are around for years (or decades).   And it’s a pretty tight knit world:   there’s all sort of ways for VCs to meet (panels, industry conferences), socialize (informal small group dinners) and work together (sitting on boards together, switching firms, occasionally personally investing in each other’s funds, etc.). As a result, the industry is characterized by a deep connective tissue, full of history, institutional memory, cliques and alliances.   There’s this interesting “coopetition” dynamic where people sometimes compete, sometimes collaborate, but overall everyone tends to know each other well.  As a result, information often travels easily and quickly, although not necessarily reliably.  Facts can be checked, and reputations matter immensely.  For entrepreneurs and VCs alike, there are some real  benefits in handling difficult situations elegantly, fairly and transparently, as it’s all a long term game in a small echo chamber.


7.  VCs do things I hadn’t realized they did.   It’s perhaps obvious in retrospect, but one surprise to me was that VCs spend an awful lot of time raising money – you’d figure that as an early stage VC, you’d be the one investing the money but the reality is that, once you’ve made the initial investment, you find yourself involved in all sorts of fundraising processes for follow on rounds for your companies, so you end up hat in hand alongside your entrepreneur.   Another unanticipated aspect of the job is that VCs can really help with exits – particularly not-so-great ones.  It’s something that doesn’t make great press stories and that people don’t like to brag about, but behind the scenes, I have seen good VCs spend a lot of time engineering exits for companies that need to “find a home”.  That often makes the whole difference between a complete disaster and a “soft landing” or an acqui-hire that occasionally nets the founders some real money.   Of course, the VC is self-interested (optimizing for results and reputation) but in my opinion, just that is a real reason to take VC money.

NYC: A Natural Home for European Entrepreneurs

Last night I was invited to speak at the inaugural NYC European Tech Meetup.  There are tons of obvious reasons why the NYC and European tech ecosystems should work closely with one another, so a meetup on the topic was long overdue.  Congrats to Alban Denoyel and Anthony Marnell for starting it, and thanks for inviting me to speak, was a lot of fun.  Below are the slides I used – the presentation was meant to be a “State of the Union” of European tech in NYC, a high level overview fit for an inaugural meetup and get the conversation started.


Many thanks to David Rogg, our newest associate at FirstMark, for helping me with this.  I’m sure we missed some companies and people – if so, let us know in the comments, and we’ll update the presentation.

The French Startup Ecosystem: At a Tipping Point

I know, when thinking about hotbeds of startup innovation, France doesn’t exactly jump to mind. Sure, there are interesting things happening in European tech – in London, or Berlin (which I covered here). Or Finland. But France? Ask U.S investors and entrepreneurs, and you’ll hear more or less the same thing: high taxes. Impossible to fire people. Government intervention. Language barrier. Fear of failure. Strikes. The country of the the 35 hour law, where people are prohibited by law to answer email past 6pm.

Yet things have started to accelerate meaningfully in French early stage tech, particularly in the last two or three years. I was fortunate to be recently invited as part of a delegation of US VCs and media guests to spend a few days in Paris to meet with local entrepreneurs and VCs, as well as President Hollande and other senior members of the French government. As a Frenchman who has spent his entire professional career in the US, I’m perhaps more cynical than most about those matters, but I came back from my trip genuinely intrigued by the potential of the French tech scene.

For anyone who cares to look, the fairly obvious conclusion is that there’s a huge gap between perception and reality, when it comes to the French startup ecosystem. Very significant progress has been made on all fronts – more interesting startups, more funding, lots more talent rushing into the sector, improved legistation, etc. – yet the word has not caught on.

It is going to take a while to close that perception gap – if nothing else, because it takes a long time to overcome a negative reputation. But you can’t blame people outside France for being confused – France has been showing traits of schizophrenia in its approach to innovation and business success. For all its emerging crop of talented young tech entrepreneurs, most of France is still deeply ambivalent about business and individual wealth creation. French entrepreneurs are building great businesses, but often show a tendency for self-bashing and country-bashing. The current French government has been sending mixed signals (or has done a dramatic 180 degree turn, depending on how you look at it). Elected on a left wing platform, at first it showed signs of being anti business – including an ill fated attempt at raising capital gains tax, and a badly botched meddling into Yahoo’s attempt to acquire Dailymotion, a French competitor to YouTube. It now has launched a charm offensive towards the startup world both within and outside France, labeled “La French Tech” – first started by Fleur Pellerin, then Minister for the Digital Economy and now run by Axelle Lemaire, her successor since April 2014 – both talented and in sync with a younger generation of French entrepreneurs.  All of this is certainly encouraging; time will tell whether this is a long term change of mentalities.

Here some thoughts – not meant to be a comprehensive review of everything happening in France of course or mention every single noteworthy person or company – just my notes.

Talent is French Tech’s Biggest Asset. France has had excellent engineering schools and a deep bench of technical talent for generations.   The big development of the the last few years is that many graduates of those schools are increasingly choosing to go work for startups (or start one) instead of choosing a career at Bain, Goldman Sachs or Total.  Many of those schools have launched seemingly very active incubators.  And this new generation of graduates speaks English a lot better than its elders.

One particularly noteworthy addition to the French educational system: Ecole 42, a new and highly innovative computer science school funded by a $100 million gift from Xavier Niel, France’s most successful tech entrepreneur. As far as I know their model is entirely unique: anyone can be admitted regardless of previous educational background (high school diploma not required). Past an initial online logic test, applicants go through a month long selection process involving a grueling 15 hours a day, 7 days a week routine. Those who are admitted to the school go through a curriculum that involves entirely team based projects, and are assessed through peer review only.  Oh, and it’s free.  The quality of the first class is said to be truly outstanding.

Big Data and Connected Devices. France tends to produce fairly original startups and comparatively few “copycats” of successful U.S. companies – for example Vente Privee pioneered the concept of online flash sales that was then imported in the U.S.. There are plenty of startups large and small in areas such as eCommerce (ShowroomPrive), video (Dailymotion) and music (Deezer, eDJing). But considering my specific areas of interest, I’m excited to see French startups excelling in Big Data and or math/data driven areas (think Criteo, Talend, Scality, Qunb, PriceMatch, etc.). France is also particularly innovative in the connected devices and hardware space (Parrot, Withings, Netatmo, Sigfox, Sense, Aldebaran, etc.).

Startups Dreaming Bigger: A common complaint against France (and indeed, most of Europe) expressed by US investors has been the relative scarcity of startups with truly global ambitions. In an environment where financing has been limited, many startups have had to focus on reaching profitability quickly, as opposed to focusing on scale. Also, French startups have historically focused on the French market, at least initially. Not that this is not a viable strategy: the market is reasonably large (65 million inhabitants), and large tech businesses have been built with a domestic focus – not least of which Illiad, Xavier Niel’s $17 billion ISP and cell network business. But it’s typically not what US investors are looking for, as their economics are driven by their ability to find hypergrowth businesses with true potential for $1BN+ exits, which are typically generated by startups conquering quickly very large markets.

This, too, seems to be changing, as the new generation of French startups seems to be thinking globally much more systematically, and much earlier in their development. Of course, French startups have had big international successes before (Business Objects, ILOG, Kelkoo, etc.). But there just seems to be a lot more French startups that are showing a strong international inclination – Criteo (which IPO’ed on the NASDAQ last year) derives at least 80% of its revenues outside France; rapidly growing ride sharing startup BlaBla Car is already present in 12 countries. Anecdotal conversations I have with French entrepreneurs indicate a clear desire to go international very early.

More VC Financing Options: While there’s still long ways to go compared to the U.S., there seems to be more VC financing options than ever before available to French startups:
• Seed financing: compared to other European countries, there seems to be more funds than individual angels at the seed fun: Elaia, Alven and Isai are names that come back frequently in conversations
• Early stage financing: Partech, Idinvest and Iris seem to be the main players.
• Growth financing: there seems to be a gap there, filled in part by London based funds (mostly Accel and Index)
• BPI France is an important (a strange, by American standards) player in the ecosystem. The result of an amalgamation of various state entities in late 2012, it is a VC fund (with 5 different funds), a venture debt provider and a fund of fund (with 56 partner funds).

Improved Regulatory Environment. This would be worth a separate  blog post, but here are some of the highlights of what was discussed during my recent trip to France:
• A startup can fire employees completely at will during their first 8 months of employment
• Past that 8 month period, French labor laws were relaxed in 2008 to allow firing in a broader range of situations, including “economic” situations where requirements or qualifications change – not quite the US situations but in practice, not a major issue apparently
• The 35 hour work week law, passed in 2000, was essentially amended in 2004 to the point of being completely voided of substance
• The 6pm email ban never existed and was the result of bad transation (see The Economist here)

Celebrating the rise of the French-American startup: Whether you call it a brain drain or a global partnership in the making, it’s hard not to notice the recent influx of French tech entrepreneurs in the U.S. Sure, a handful of French nationals have been prominent in the US startup industry for a while: Bernard Liautaud (Business Objects), Jeff Clavier (SoftTech), Loic Le Meur (Le Web), Fabrice Grinda (OLX), Tariq Krim (Netvibes now JoliCloud), Hubert Tieblot (Curse) and, increasingly, Renaud Laplanche (Lending Club) are some of the more obvious names. But the pace of arrival of French entrepreneurs has now accelerated to an entirely different dimension.

The French-American startup seems to come in three flavors:
• Startups founded by French nationals in the U.S.: for example Lending Club (San Francisco), (Palo Alto), Datadog (NYC), Placemeter (NYC), etc. Those companies often have no specific connection to France other the nationality of their founders.
• Startups founded in France by French nationals, that move to the U.S. very early in their development, sometimes after going through a local incubator like Le Camping (and then going through a U.S. incubator like Techstars): Sketchfab, Infinit, Doctrackr are some examples. Dashlane (in which my firm, FirstMark, has been an early investor) is another prominent example. Those companies often have their development teams in France and at least half of their management team in the U.S.
• Startups founded in France by French nationals, that reach some scale domestically first, and then move in the U.S. for growth expansion, for example: Novapost, Synthesio, Criteo
While one should be careful to not immediately assimilate this trend to “the Israeli model” (lots of nuances there), this dual structure (R&D in France and commercial operations in the U.S.) seems to work quite well.

This new generation of cross-atlantic startups should be celebrated. Seen from a purely French and short term perspective, this may not feel ideal: many of those companies will “flip” (meaning, transform from a French legal entity to a Delaware one, effectively becoming U.S. companies), and some entrepreneurs will become rich but won’t pay taxes in France. Long term, however, the benefits are immense – the vast majority of those French entrepreneurs will eventually come back to France, bringing with them deep entrepreneurial expertise, international connections and the financial means to be active seed investors in French startups, which will in turn hire people in France.

The key is here is to think of French tech as a globally distributed ecosystem, as opposed to a French one – many of French tech’s biggest successes will occur in the U.S. and, increasingly Asia.

NYC is a logical second home for French tech: while the Silicon Valley is the undisputed center of the tech world, NYC offers obvious advantages to French entrepreneurs interested in building global businesses: shorter flight, less of a time difference, arguably less of a cultural difference, and a younger, hungrier tech ecosystem where it easier to make a name for oneself. From that perspective, it was somewhat of a surprise to me when speaking to French entrepreneurs in Paris that they were most often thinking about the Valley as opposed to New York.

New York has a strong emerging French tech community: Fabrice Sergent (Cellfish), Mathieu Nouzareth (Freshplanet), Morgan Hermand-Waiche (Adore Me), Olivier Pomel and Alexis Lê-Quôc (Datadog), Alexandre Douzet (The Ladders), Gaspard de Dreuzy (Kapitall, Pager), Christophe Garnier (MommyCoach) and many others.  Some prominent figures of the NYC tech community have deep ties or strong interest in France, including Kevin Ryan (Gilt, MongoDB, Business Insider, Zola) and Ed Zimmerman (Lowenstein Sandler). This community is starting to gel quite nicely. The French consulate in New York (led by the new-ish consult Bertrand Lortholary) is starting to actively promote the French entrepreneurial community. And just this week, a new conference (La French Touch conference) is being launched and could become an important focal point.

What needs to happen next? Building a tech ecosystem takes generations (of startups). Companies need to start, receive financing, grow and exit. Founders and early employees need to contribute back their expertise and money (through angel investing) into the next generation of startups.  Large exits also embolden the next generation of entrepreneurs and VCs.  So France, like other emerging tech hubs, needs more exits.  However, it does have an incredible secret (or not so secret) weapon in the form of Xavier Niel – who invested 200 million euors to convert a former railroad depot into an incubator for 1,000 startups. This could be just the final touch that Paris (in particular) needs to get to the tipping point – this by itself should give a serious reason to US VCs to make Paris a must-stop destination on their tours of tech hubs in Europe.

Special thanks to Jerome Lecat (Scality) and Marie Ekeland (formerly of Elaia) for organizing our Paris visit, and to Philippe Collombel (Partech) for walking me through the Sentier and the Paris VC world.


The State Of Big Data in 2014: a Chart

Note: This post appeared on VentureBeat, here.

It’s been almost two years since I took a first stab at charting the booming Big Data ecosystem, and it’s been a period of incredible activity in the space. An updated chart was long overdue, and here it is:

(click on the arrows at the bottom right of the screen to expand)

A few thoughts on this revised chart, and the Big Data market in general, largely from a VC perspective:

Getting crowded: Entrepreneurs have flocked to the space, VCs have poured money into promising startups, and as a result, the market is starting to get crowded. Certain categories like databases (whether NoSQL or NewSQL) or social media analytics feel ripe for consolidation or some sort of shakeout (which may have already started in social analytics with Twitter’s acquisitions of BlueFin and GNIP). While there will be always room for great new startups, it seems that a lot of the early bets in the broader infrastructure and analytics segments have been made at this stage, and the bar for success is getting higher – which doesn’t mean that VC money will stop pouring in. In terms of this specific industry chart, we’ve clearly reached the limit of how many companies we can fit one page. I’m sure there are a number of great companies we either missed or didn’t have enough space to include – apologies in advance to those, and I’d love to hear people’s thoughts and suggestions in the comments section about who else should be included.

Still early: Overall, we’re still in the early innings of this market. Over the last couple of years, some promising companies failed (for example: Drawn to Scale), a number saw early exits (for example: Precog, Prior Knowledge, Lucky Sort, Rapleaf, Nodeable, Karmasphere, etc.), and a handful saw more meaningful outcomes (for example: Infochimps, Causata, Streambase, ParAccel, Aspera, GNIP, BlueFin labs, BlueKai). Meanwhile, some companies seem to be reaching significant scale, and have raised spectacular amounts of money (for example, MongoDB has now raised over $230M, Palantir almost $900M and Cloudera $1B). But overall, we’re still early in the curve in terms of successful IPOs (Splunk or Tableau notwithstanding) and large exits, although the big companies are getting more acquisitive in the space (Oracle with BlueKai, IBM with Cloudant). In many segments, startups and large companies are jockeying for position and no obvious leader has emerged.

Hype, meet reality: A few years into a period of incredible hype, is Big Data still a thing? While less press worthy, the next couple of years are going to be hugely important for this market, as corporations start moving Big Data projects from experimentation to full production. While they will lead to rapidly increasing revenues for some Big Data vendors, those deployments will also test whether Big Data can truly deliver on its promise. Meanwhile, the fundamental need for Big Data technology keeps increasing, as the deluge of data keeps accelerating, powered in part by the rapidly emerging Internet of Things industry.

Infrastructure: Hadoop seems to have solidified its position as the cornerstone of the entire ecosystem, but there are still a number of competing distributions – this will probably need to evolve. Spark, another open source framework that builds on top of the Hadoop Distributed File System, is getting a lot of buzz right now because it promises to fill in the places where Hadoop has been weak, namely interactive speeds and good programming interfaces (and early signs seem to point to fulfilling that promise). Some themes (for example, in memory or real time) continue to be top of mind; others are appearing (for example, there’s a whole new generation of data transformation/munging/wrangling tools, including Trifacta, Paxata and DataTamer). Another key discussion is whether enterprise data will truly move to the cloud (public or private), and if so, how quickly. Many will argue that Fortune 500 companies will keep their data (and the software to process it) on premise for years to come; a generation of Hadoop-in-the-cloud startups (Qubole, Mortar, etc.) will argue that all data is moving to the cloud long term.

Analytics: This has been a particularly active segment of the Big Data ecosystem in terms of startup and VC activity. From spreadsheet type interfaces to timeline animations and 3D visualizations, startups offer all sorts of different analytical tools and interfaces, and the reality is that different customers will have different type of preferences, so there’s probably room for a number of vendors. Go to market strategies differ as well – some startups focus on selling tools to data scientists, a group that is still small but growing in numbers and budget. Others adopt the opposite approach and sell automated solutions targeting business users, bypassing data scientists altogether.

Applications: As predicted, the action has been slowly but surely moving to the application layer of Big Data. The chart highlights a number of exciting startups that are fundamentally powered by Big Data tools and techniques (certainly not an exhaustive list). Some offer horizontal applications – for example, Big Data powered marketing, CRM tools or fraud detection solutions. Others use Big Data in vertical specific applications. Finance and ad tech were always early leaders in adopting Big Data, years before it was even called Big Data. Gradually, the use of Big Data is spreading to more industries, such as healthcare and biotech (particularly in genomics) or education. This is only the beginning.

Many thanks for my FirstMark colleague Sutian Dong for doing a lot of the heavy lifting on this chart. My former colleague Shivon Zilis of Bloomberg Beta contributed immensely to prior versions of this chart.