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 x.ai. Many thanks to my colleague Jim Hao, who worked with me on this presentation.
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:
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.
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.
The field of bioinformatics is having its “big bang” moment. Of course, bioinformatics is not a new discipline and it has seen various waves of innovations since the 1970s and 1980s, with its fair share of both exciting moments and disappointments (particularly in terms of linking DNA analysis to clinical outcomes). But there is something special happening to the industry right now, accelerated by several factors:
I’m doing a talk on the Internet of Things tomorrow at the SIIA’s “IIS: Breakthrough” conference tomorrow, and here are the slides I’ll use. It’s meant to be a high level introduction to the topic, for a broad audience of “information industry” professionals. Also used an earlier version of those slides at the WIN Global Innovator last week, which was fun. Feedback welcome.
As the fundamentally important debate over women in technology and entrepreneurship rages on (most recently sparked by what Paul Graham said, or perhaps didn’t say), I’ve been intrigued by the comparatively higher proportion of women who seem to be starting companies in one of my areas of predilection: hardware (broadly defined: open hardware, Internet of Things, wearable computing, 3D printing, etc.).
I don’t have much data here, other than my anecdotal personal experience, both as a VC and as the organizer of Hardwired NYC. But, without having to rack my brain for more than a minute or two, a bunch of names of great female founders and/or CEOs in the general hardware space comes up, including, in no particular order:
- Limor Fried, founder, Adafruit
- Ayah Bdeir, founder and CEO, littlebits (who spoke at Hardwired NYC last November)
- Amanda Peyton, co-founder and CEO, Grand St (see her talk at Hardwired NYC here)
- Jenny Lawton, President, Makerbot (see her talk at Hardwired NYC here)
- Kegan Schowenburg, co-founder and CEO, Sols (speaking at Hardwired NYC next week)
- Helen Zelman, co-founder, Lemnos Labs
- Cheryl Kellond, co-founder and CEO, Bia
- Monisha Perkash, co-founder and CEO, Lumo BodyTech
- Daniela Perdomo, co-founder and CEO, GoTenna
- Mary Huang, co-founder, Continuum Fashion
- Meredith Perry, founder and CEO, uBeam
- Julia Hu, founder and CEO, Lark
- Debra Sterling, founder and CEO, GoldieBlox
And there are many more (both in the U.S and globally), which is exciting.
The question, of course, is why hardware would be an area of particular focus for female entrepreneurs. As a category, hardware is broad, lends itself to all sorts of products, and as a result feels pretty gender-neutral.
Could it be that there are more female role models in hardware, since it is often said that role models are particularly important to female entrepreneurs ? It doesn’t appear that way. Sure, women have run some of the biggest hardware companies in the world (Carly Fiorina and Meg Whitman at HP; Ursual Burns at Xerox) but it’s unclear how much of an inspiration they would be to early stage tech entrepreneurs, and more importantly, a number of software or internet companies have been run by women as well. Perhaps more relevant are female entrepreneurs like Limor Fried, who under her “Lady Ada” moniker has become the closest equivalent to a celebrity in the hardware alpha geek world (and beyond, through her appearance on the cover of Wired in 2011).
What’s interesting is that hardware lends itself particularly well to new entrants – there’s been a big gap in innovation in hardware in the last 10 or 15 years (with some notable exceptions like Apple), and as a result there’s a “missing generation”, and plenty of opportunities for new entrepreneurs to become leaders in what, in some ways, feels like a brand new field.
Curious if anyone can think of an explanation?
Regardless, and to the extent this is indeed a trend, it is particularly exciting and promising, and we should collectively think about how to accelerate it and extend it to other areas of tech entrepreneurship.
Got some great feedback on Twitter, and while my initial goal was not to be comprehensive here, thought it could actually be helpful to start a running list of female hardware founders – perhaps it can become a good resource. Here are the people that were recommended to me, who else should I add? (please add in comments)
|First Name||Last Name||Company||Location|
|Jeri||Ellsworth||Technical Illusions||Bellevue, WA|
|Anastasia||Leng||Hatch||New York, NY|
|Christina||Mercando||Ringly||New York, NY|
|Ezster||Ozsvald||Notch||New York, NY|
|Gauri||Nanda||Toymail||New York, NY|
|Lisa||Fetterman||Nomiku||San Francisco, CA|
|Laura||Berman||Melon||Santa Monica, CA|
|Amanda||Williams||Fabule Fabrications||Montreal, Canada|
|Alexandra||Deschamps-Sonsino||Good Night Lamp||London, UK|
|Becky||Pilditch||Bare Conductive||London, UK|
|Jane||ni Dhulchaoinfi||Sugru||London, UK|
|Ana||Burica||Teddy The Guardian||Zagreb, Croatia|
I recently got a chance to participate in a panel focused on opportunities in hyperlocal at the 2013 StreetFight Summit, along with Ben Siscovick. Since they recorded it, here it is, along with a couple of pics.
The rise of Berlin as an entrepreneurial center is not exactly news, and a number of U.S. VC funds or angel investors have been active there for a while. My overall impression, however, is that many U.S.-based entrepreneurs and investors have only a fuzzy idea about what is going on over there, and arguably in Europe in general – a missed opportunity in my opinion, and perhaps one of the several reasons why Europe is still a largely underserved opportunity in terms of venture capital investment. The globalization of entrepreneurship has been one of the key trends in our industry. At this stage, there’s enough evidence of global success stories coming out of Europe that smart U.S. investors should be routinely investing in the area, despite the traditional issues associated with early stage investing in Europe (multiple markets, multiple languages, tax and regulatory issues, different attitudes towards risk/failure, etc.).
From that perspective, I thought it might make sense to share notes (very much in note format) from recent travel to Berlin (among other reasons to speak at Data Days, a fun event) and a number of conversations with Berlin-based entrepreneurs and investors in other contexts. This is meant to be a “beginner’s guide” for outsiders like me, not the ultimate reference on the topic.
Overall, there’s plenty of reasons to be excited about Berlin. While some claim that the real action has already moved on to other locations (like Istanbul), the Berlin tech ecosystem is still early, and in many ways trailing other emerging global tech centers like London and NYC, probably by a few years. The fundamentals, however, are encouraging, particularly considering that the government (very active both in London and NYC) has been largely absent from the development of the Berlin ecosystem, so pretty much everything that has been happening there so far has been driven by raw, grassroots entrepreneurial energy.
Many thanks to Christophe Maire (currently CEO of Txtr), Jess Erickson (General Assembly Berlin), Koen Lenssen (Tengelmann Ventures) and Saskia Ketz (SumAll) for reviewing this post.
- Just like New York or San Francisco are not like the rest of the U.S., Berlin is not like the rest of Germany
- Artistic (buoyant contemporary art scene), rebellious culture (or “counterculture”), which seems to translate well into design talent
- Innovative and fun (renowned nightlife)
- Cheap, large apartments – particularly compared to tech centers like London, NYC or SF where finding affordable housing is an extraordinary challenge. Some say that this won’t last long if Berlin continues on its current trajectory; at the same time, the city is very large and housing supply may exceed demand for a while.
- Socially open, no class system, left leaning with an openly gay mayor (Klaus Wowereit) from the SPD (social democratic party), in power since 2001.
- Capital of one of the world’s largest economy, yet due to history, no local industry – local talent does not have many other options
- Traditional economic centers in Germany such as Munich, Frankfurt and Hamburg lag behind in terms of tech startup activity – which doesn’t mean that those cities do not have interesting companies: for example, Hamburg seems to have a gaming cluster (Bigpoint, Innogames, GoodGames, etc.), and both Facebook and Google have offices there; Munich has West Wing (online shopping club for Home & Living, received $50M of investment in June 2012), Frankfurt/Wiesdaben is active in social entrepreneurship (Hans Reitz/Grameen). But Berlin seems to have strong gravitational pull; for example, when airbnb arrived in Europe, it set up shop in Hamburg after acquiring German clone Accoleo , but subsequently moved moved all operations to Berlin. Twitter also chose Berlin over other German cities to base its operations. MTV has been there since 2004 (after moving from Munich).
- Part of the European Union (doesn’t solve all labor laws issues, but helps tremendously in terms of recruiting talent from other EU countries)
- Just about everybody seems to speak English
- International founders: perhaps ironically, a number of Berlin startups, including some of the most prominent ones, were founded or co-founded by non German nationals, including Souncloud (Swedish founders), Gidsy (Dutch founders), Amen (one American co-founder), Incrediblue (Greek founders), Readmill (Swedish founder), GoEuro (American), rules.io (American), GetYourGuide (Swiss), etc.
Solid supply of technical talent
- For now at least, there’s much less of a talent war than in other tech hubs, particularly SF and NYC, but some say it is changing fast.
- Strong German work ethic (one of the reasons for an overall low employee turnover, together with restrictive laws around employment termination and the German social structure in general).
- Solid universities, although fairly theoretical: Humboldt, Technical University, Freie Universiat. Berlin also has two of Germany’s top art and design universities: UdK and Weißensee
- Geographically close to cheap talent: Leipzig, Warsaw, etc.
- There’s some history of large tech companies like Siemens having a strong presence in Berlin, but by the sound of it, at this stage startups are the only game it town in terms of recruiting top technical talent
Increasingly solid community infrastructure
- Lots of co-working spaces: Agora Collective, Ahoy, Betahaus, ClubOffice, Co.Up, LaunchCo, Mobilesuite, Raumstation, St Oberholz, Tante Renate, etc – some spaces are essentially cafes, others are actual office spaces with scheduled activities.
- More on the way: The Factory
- Several accelerator programs: StartupBootcamp Berlin, Mcube, Hubraum, Project A, YouIsNow, Berlin Startup Academy
- Education: General Assembly now offers enterpreneurship courses in collaboration with BetaHaus
- Press: Berlin has its own industry blogs, including Venture Village and Silicon Allee. Techcrunch (largely Mike Butcher) covers extensively Berlin startups.
- While it’s been growing for a few years now, the tech ecosystem still generally feels early, compared to London or NYC
- Berlin was always known for hacker culture (chaos computer club) leading to cutting edge outfits in 90’s (art+com, convergence, gate5).
- Started with the Samwer brothers – was a mixed blessing for Berlin. While starting successful businesses, they perfected the art of the startup copycat (with the resulting bad reputation). Examples: StudiVZ (Facebook clone), Citydeal (Groupon clone, assets acquired by Groupon), Zalando (originally a Zappos clone, has expanded beyond shoes since), Wimdu (airbnb clone)
- Now produces original startups (readmill, researchgate, goEuro, etc.), with an increasing number with global relevance and aspirations (SoundCloud)
- Berlin seems still mostly focused on consumer internet companies (with a good amount of mobile plays), with comparatively fewer B2B or enterprise startups; it is not a full ecosystem yet from that perspective, with some exceptions like cloudControl (European PaaS provider)
- While there is a fair distribution of startups across the stages (from seed to late stage), overall the ecosystem is too recent to have a very solid track record of exits. Some examples: ImmoScout (sold to DT for €450m), Idealo (a comparison shopping site, acquired by Axel Springer in 2006), gate5 (today “nokia Maps” employing 800 people in Berlin), StudiVZ (sold to one of its investors, Georg von Holtzbrinck Publishing Group, for €85 million in 2007), MyphotoBook (sold to Holtzbrink), Nugg.ad (provider of predictive behavioral targeting solutions for digital advertising, acquired by Deutsche Post in 2010 for €50M), KaufDa (local search and local promotion search, acquired by Axel Springer), Zanox (acquired by Springer for €250m), Casacanda (online shopping club for daily design inspirations, acquired by Fab.com in February 2012 in an all-stock deal valuing the company at around $10M), Brands4Friends (sold to eBay for €150m, etc.)
- Sounds like the government hasn’t quite caught on – in starck contrast to London or NYC. The success of the Berlin ecosystem seems to have been entirely driven by a grassroot, community effort.
- There’s less VC money available than in other places like NYC (or to some extent London); companies tend to be very capital efficient and tend to monetize early .
- One point people disagreed about: some say the ecosystem is still a bit “clique-ish”, the community hasn’t yet completely geled as a full integrated, selflessly supportive environment (at least compared to SF or NYC) –others disagreed, citing Berlin’s community as one of its key assets.
- Successful entrepreneurs are starting to give back to the ecosystem in the form of active angel investments. Some notable examples: Dario Suter, Fabian Heilemann, Christophe Gras, Christophe Maire, Christian Vollman, Marco Börries, Martin Sinner, Lukasz Gadowski, Michael Brehm, etc.
- Rocket Internet (Samwer brothers) plays have alone raised close to 1bn in 2012 alone and breeds large number of 2nd generation entrepreneurs with international experience. Employs overall 10,000 people in Berlin alone.
- Team Europe, project-A and other Incubators breed ambitious international companies (Madvertise, Delivery hero, Sponsor pay)
- Soundcloud: world’s leading social sound platform
- Amen: the place for creating and sharing opinions about the extra ordinary things in life.
- Gidsy: community marketplace for authentic experiences
- 6wunderkinder: multi-platform productivity solutions for individuals, groups and businesses
- Wooga: third largest social games developer in the world
- Delivery Hero: global network of online food ordering marketplaces
- Zalando: largest European eCommerce group (including shoes)
- 9flats (peer to peer apartment rentals)
- Lieferheld: platform for ordering and paying food online
- EyeEm: smart photo-sharing application for smartphones
- Txtr: distributed eBooks platform
- Readmill: social and shareable reading platform
- Researchgate: community for researcher and scientists
- MoviePilot: promotion platform for movies (DFJ esprit)
- Monoqi.com: highly curated commerce
- Other companies/products that came back in conversations: HelloFresh, Trademob, Travis-Cl, Fort Rabbit, Cobot.
Angels, seed investors, founder collectives or micro VCs
- Rocket Internet (Dealstreet, Wimdu, GlossyBox, Westwing, 21Diamonds, payleven)
- Team Europe (Delivery Hero, Lieferheld, Madvertise)
- Christophe Maire: Swiss serial entrepreneur, currently CEO of Txtr, investor in soundcloud, Amen, EyeEm, LoopCam, Appaware, PhoneDeck
- Klaus Hommels: Swiss leading European angel investor
- Ashton Kutcher: investor in Amen, Gidsy, Soundcloud
- Martin Sinner: MD at Idealo and active angel
- US funds: Highland (Wooga, getyourguide), Union Square Ventures (Soundcloud), Kleiner Perkins (Soundcloud), GGV (Soundcloud), RedPoint Ventures (9flats), JP Morgan (Zalando), kinnevik (RocketInternet), Benchmark, FounderFund (Researchgate), Spark Capital (getyourguide)
- International funds: Index Ventures (Soundcloud, Gidsy), Atomico (6Wunderkinder), Balderton (Wooga), DST Global (Zalando), Kite Ventures (Delivery Hero, Lieferheld), ru-Net (Lieferheld), Sunstone Capital (Amen, Gidsy), Wellington Partners (EyeEm, Readmill), e.Ventures (9flats, kaufDa, Dealstreet), Passion Capital (EyeEm), Mangrove Capital Partners, Partech, b-to-v Partners, etc.
- German funds: Earlybird, HV Holtzbrinck, IBB (ClipKit, cloudControl), Earlybird Ventures, BMP Media Investors, Tengelmann Ventures, Dumont Venture, High Tech Gründerfonds (a public private partnership with 10+ corporate investors, currently investing out of a €293.5 million fund), GMPVC (German Media Pool, invested in 9flats).
- Corporates: BDMI, T-Venture (ClipKit, 9flats, 6Wunderkinder).
The November NYC Data Business Meetup was focused on “vertical-specific” applications of big data – startups leveraging the big data stack to offer new solutions to specific industries, such as finance and government (Recorded Future), the legal industry (Lex Machina), energy (DataMarket, although it offers data sets for other industries as well) and sports (numberFire).
Here are the videos:
Christopher Ahlberg, CEO, Recorded Future:
Josh Becker, CEO, Lex Machina:
Hjálmar Gíslason, CEO, DataMarket:
Nik Bonaddio, CEO, numberFire:
- It’s not entirely bad that things cool off a little bit — there are just too many startups being created in those consumer areas, too much angel and VC money floating around, valuations that don’t make sense, not enough technical talent to support the whole thing, etc
- As an industry, we’ll all be fine because things have been heating up on the enterprise tech side. Public markets have been much more accepting of the enterprise tech plays (Splunk, ServiceNow, Palo Alto Networks all did very well in their IPOs). For every Instagram, there seems to be a Nicira type acquisition. Box.net and its young CEO are the object of the type of hype (and investor funding) typically reserved to successful consumer plays. The combination of the cloud and big data trends has many commentators excited. Some see the beginning of a 20 year cycle of innovation in enterprise IT.
- Enterprise tech does not have the gravitational pull of the consumer internet. Because you can touch it, feel it, experience it, everyone can relate to the consumer internet. And because it is very visible, the young entrepreneurs who succeeded at it not only made fortunes in a short amount of time, but became pop culture icons in the process (complete with movies, Gap ads, etc.). Rightly or wrongly, this has created all the excitement around tech that we now take for granted. Some of it perhaps led to unwanted attention (not sure that, as an industry, we need Justin Bieber to be angel investing, as much as I’m a fan…), but arguably this has drawn into the industry a lot of talent and money that has lifted all boats. What happens when this interest subsides? Enterprise tech sorely lacks sex appeal: it is complicated, obscure, behind the scenes. You pretty much can’t be an outsider to the tech industry and come up with a good idea. If exciting consumer tech projects stop being funded, will Wall Street techies still continue to migrate to startups? Will hundreds of thousands of people will still feel an urge to learn to code? Will the broader public still care about tech?
- Consumer internet companies have been driving, or at least influencing, innovation in enterprise IT over the last few years – whether it is actual technology (Amazon pioneering cloud computing, Google/Yahoo/Facebook/LinkedIn being driving forces in big data, etc.), the way enterprise tech is consumed by employees (social enterprise, Bring Your Own Device, etc.) or the way it has been sold to enterprises (freemium plays that bypass the CIO). What happens to this phenomenon, long term, if consumer internet is no longer driving innovation?
- Consumer internet companies have proven to be great early customers of enterprise tech startups. Of course, you could argue that this “startups selling to other startups” does not make sense because at the end of the day it’s all funded by VC money. But the reality is that every enterprise tech startup needs early customers, and many consumer internet startups have proven to be more willing to use new, bleeding edge technologies – the hope being that, once an enterprise tech startup has a few success stories with startups under its belt, it makes it easier to “graduate” to Fortune 500 companies. When the internet bubble burst in the early 2000s, consumer tech companies went down first, but enterprise tech startups soon followed, because many of them essentially lost a chunk of their customer base. Could the same phenomenon occur today?
I have been very intrigued by the recent emergence of “data driven” firms, aiming to use data to reinvent venture capital.
While they certainly review various data points and metrics before deciding to invest in a startup, as of today venture capital investors largely operate based on “pattern recognition” – the general idea being that, once you’ve heard thousands of pitches, sat on many boards and carefully studied industries for years, you become better than most at predicting who will make a strong founder/CEO, what business model will work and eventually, which startup will end up being a home run. The trouble is, the model doesn’t always work, far from it, and many VCs end up making the wrong bets, resulting in disappointing overall industry results. Could VCs be just like the baseball scouts described in Moneyball, who think they can spot future superstars because they’ve seen so many of them before, but end up being beaten by a cold, objective, statistics-based approach?
Enter several firms trying to do things differently:
- Google Ventures has created various data-driven algorithms that inform their investment decisions – see the team discussing the concept at last year’s Web 2.0 Summit here.
- Correlation Ventures raised $165M earlier this year for its first fund, which was reportedly oversubscribed (a rarity for a new fund). Correlation says it has built the “world’s largest, most comprehensive database of U.S. venture capital financings”, which covers “the vast majority of venture financings that took place over the past two decades, tracking everything from key financing terms, investors, boards of directors, management backgrounds, industry sector dynamics and outcomes”. Based on this data, Correlation has developed predictive analytics models which it uses to guide its investment decisions – as a result, it can make decisions very quickly (less than two weeks) and doesn’t require additional due diligence.
- Just earlier this week, E.ventures (which results from the relaunch of BV Capital) also emphasized its own data-driven approach to investment decisions
Since I’m a big fan of anything data-driven (decisions, product, companies), the concept resonates strongly with me. Predictive analytics have been successfully used in various industries, from retail to insurance to consumer finance. Other asset classes are highly data driven – fundamental and technical analysis drive billions of dollars of trade; hedge fund quants spend their lives building complex models to price and trade securities; high-frequency trading bypasses human decision making altogether and invests gigantic amounts of money based solely on data. In this world where everything gets quantified, why should venture capital be an exception?
However, as much as I like the idea, I believe venture capital doesn’t lend itself very well to a model-heavy, quasi “black box” approach. The creation of a reliable, systematic predictive model is a particularly challenging task when you consider the following obstacles:
- A relatively sparse data set: while by definition there’s not much data about early stage startups, you could argue that that amount is constantly increasing, as everything is moving online, and everything online can be measured. You could also argue that, if you could have access to all historical data from all VC firms in the country, and efficiently normalize it, you would end up with a lot of data. But still that amount of data would pale in comparison to what’s available to public market investors – Bloomberg processes up to 45 billion “ticks” (change in the price of a security)… daily.
- Limited intermediary feedback points: Before getting to a final outcome (game lost or won), baseball is full of small binary outcomes (a player hits the ball or he doesn’t). Similarly, in market finance, the eventual success of strategy can typically be broken down in many different points with binary outcomes (you make money or you don’t). In venture capital, before getting to a final outcome (a startup has a liquidity event), it’s unclear how many of those intermediary, measurable points you get, that can enable you to build models – perhaps a few (the startup’s next round is an “up round” or a “down/flat round”) but certainly nothing compared to the above examples.
- Extended time horizon: in baseball, the rules of the game do not change from game to game, or season to season. In venture capital, the “game” can last for years, because investments are highly illiquid. During that time, pretty much anything can change – regulatory framework, unforeseen disruptive forces in the industry, etc.
In addition, it would be interesting to see how startups react in the long run to investors who are interested in them mostly because they scored well on a model, as opposed to spending extended time getting to know them. Unlike public stock markets, venture capital fundraising is a two-way dance, and startups often pick their investors as much as their investors pick them.
However, while I have my doubts about using data models as valid predictors of the overall success of an early stage startup, my guess is that there are still plenty of interesting insights to be gleaned from the data, and that forward-thinking VC firms could gain a competitive advantage by actively crunching it – my sense is that very few firms have done so at this stage.
Interestingly, there are some good data sources and emerging technologies out there that could be leveraged as a first step, without engaging into a massive data gathering or technology development effort:
- Public (and/or free) sources: Crunchbase is a great source of data. There are many directions you could go with mining it – as an example, see what Opani (an early stage NYC big data company) came up with here. I bumped into Semgel, a web app that has taken a stab at instantly gathering and analyzing Crunchbase data. The Crunchbase data could be augmented with data from marketplaces such as Factual. See also this intriguing article about pre-money valuations of startups (typically not information that’s disclosed) could possibly be mined from publicly available Delaware certificates of incorporation and similar documents in other states.
- Private Databases: There a few interesting databases that collect and organize more complex information flows around private companies such as CB Insights (which also offers a data-driven tracking tool called Mosaic)
- Technologies: In addition to the various open-source big data tools, there are some technologies/companies that could be leveraged to mine VC industry data, including for example Quid, co-founded by the talented Sean Gourley – “understanding co-investment relationships and deriving investment strategies” is one the challenges they address.
If anyone is aware of other efforts around crunching data relevant to VCs, or other ways VCs have been used a heavily data-driven approach, I’d love to hear about it in the comments.