10 Quick Takeaways from CES 2014

1.  Big brand curved TVs and mega booths are cool, but to me this year’s show was all about the rise of the crowdfunded hardware startup.

 

 2.  It’s official, there are now more wearable wristband vendors than there are human wrists on the planet.

 

3.  The wearables category is still waiting for its disruptive “iPhone moment”.  New releases show nice progress, but mostly incremental.  Smart watches have a long way to go.

 

4.  Accelerating trends on display, still early: family tech and senior tech.

 

5.  The lines between the tech and non-tech worlds keep blurring.  Pizza Hut and Ford both had a very noticeable presence and were pitching their tech innovation.

 

6.  Hardware innovation is truly global.  Some of the most interesting startups I met were from Manchester (UK), Ukraine and Lebanon.  France continues to be very active in the space (Parrot, Withings, Netatmo, Sen.se, etc.). [UPDATE: See below some great 3D visualizations of the latest Withings and Sen.se products, produced by SketchFab]

 

7.  China was left, front and center.  Not just as the “workshop of the world” but, more strikingly, as as a producer/innovator in their own right. The rise of the juggernaut only seems to be accelerating.

 

8.  In home automation, entrepreneurs were talking a lot about AllJoyn, Qualcomm’s open source platform and language, and the AllSeen alliance that is going to promote an open standard for the Internet of Things.

 

9.  In 3D printing, Makerbot is killing it, with its three gorgeous new printers.  Toys still seem to be the killer app for consumer 3D printing, although the new Chefjet chocolate 3D printer by 3D systems was pretty awesome. Consolidation in the consumer 3D printer space seems likely, in the not-too-distant future.

 

10.  Yves Behar and Bre Pettis are incredible creative and entrepreneurial minds, who deserve all the hype they get.  I got to witness this firsthand as a judge on the finals of the first TechCrunch Hardware Battlefield (with Jen McCabe, also very sharp), as they turned the judging into a real time mentoring session, providing  insights that were worth way more than the top $50,000 prize.  Exciting and inspiring.

Mother (click to view in 3D)

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Mother

Withings Aura (click to view in 3D)

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Withings Aura

The Rise of the Female Hardware Entrepreneur

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.

*****

UPDATE:

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
Kati Bicknell Kindara Boulder, CO
Mary Turner AlertMe Cambridge, UK
Liz Salcedo Everpurse Chicago, IL
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
Alice Taylor MakieLab London, UK
Natasha Carolan MakieLab London, UK
Becky Pilditch Bare Conductive London, UK
Becky Stewart Codasign London, UK
Bethany Koby TechnologyWillSaveUs London, UK
Emily Brooke Blaze London, UK
Jane ni Dhulchaoinfi Sugru London, UK
Jessi Baker Provenance London, UK
Ana Burica Teddy The Guardian Zagreb, Croatia
Mila Burger Loccie Zagreb, Croatia
Alicia Asin Libelium Zaragoza, Spain

A Guide to the Berlin Tech Ecosystem

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.

Key characteristics

Unique

  • 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).

Immigrant-friendly

  • 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.

Still early:

  • 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)

Notable Startups

  • 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

VCs

  • 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).

Recorded Future, Lex Machina, DataMarket and numberFire

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).

The slides are here: Recorded FutureLex MachinaDataMarket and numberFire.

Here are the videos:

Christopher Ahlberg, CEO, Recorded Future:

 

Josh Becker, CEO, Lex Machina:

 

Hjálmar Gíslason, CEO, DataMarket:

 

Nik Bonaddio, CEO, numberFire:

 

Panel discussion:

 

Some pics:

Facebook’s troubles are everyone’s problem

Like many people in our industry, I have been watching with growing discomfort Facebook getting beaten up on the public markets, including yesterday’s new $17.729 low. Regardless of the reason (the company remained private during its phase of hypergrowth, nobody reading the S-1, etc.) and leaving aside the borderline silly hunt for a culprit (Zuck is immature, the CFO badly overestimated demand, NASDAQ botched the IPO, etc.), the point is that the darling of an entire industry, the most prominent of all emerging internet franchises, the one that epitomized social media at its most powerful, ended up colliding with, and so far losing to, the cold cynicism of public markets.

The ripple effects are starting to be felt throughout the industry, as they trickle down the ecosystem. Evernote for example announced last week that it was going to delay its IPO until at least 2015. Further down the chain, anecdotal evidence around me seems to indicate that VCs are being increasingly cautious and picky when evaluating consumer internet plays (broadly defined: social, local, mobile, etc.), particularly when there is not a very apparent business model in place or in the works. I’m not sure if it’s the end of an era just yet, but the Facebook IPO that was supposed to create a brand new virtuous circle (Facebook buying a bunch of startups, and Facebook millionaires angel investing in hundreds of others) is so far proving to have the exact opposite effect on the industry.

While nobody is thrilled about what is happening, I hear two types of “rationalizations” around me:
  • 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.
The first point is complex and would deserve its own post (hopefully sometime soon). As to the second point, as much I’m a big fan of enterprise tech and agree that it’s probably where the action is going to be in the next few years, the above fails to reassure me, as I just don’t see an enterprise tech boom developing independently from a strong consumer internet sector, long term:
  • 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?
The stabilization of the Facebook stock price is hugely important for our entire industry. Tech blogs, true to form, are overall wildly optimistic and blame it on Wall Street “not getting it” (Techcrunch covered yesterday’s new low as a buying opportunity), but smart entrepreneurs, VCs and involved parties seem to be doing everything they can to stop the blood bath (see Fab’s Jason Goldberg post here, for example), as they fully measure the severity of the issue.

Data-driven venture capital

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.

Some thoughts on Brewster

Three days in, Brewster, the new personalized address book, has become an instant classic for me.  Perhaps I lucked out, but I didn’t experience much of the delay in processing my contacts that many others reported – I had to wait about 90 minutes which, while not ideal, was fine.  Everything since then seems to have been working like a charm  – the de-duplication and reconciliation of contacts across social networks, in particular, was beautifully done, and that’s not a trivial data problem.

I have always liked the concept of a personalized, always current address book.  In a way, it is sort of like the old Plaxo idea, which was probably before its time.  There were various startups that tried to fix the address book, including Sensobi (that eventually was acquired by GroupMe).  The next iteration of the social concept that I’m aware of is Everyme – at least in the initial vision the founders had for it when they were at Y Combinator in the Summer of 2011.  I was a bit bummed when it pivoted (or evolved) to become a private social network.

I really like that Brewster came out of the gate very “feature-rich”.  While I’m all for MVPs and generally agree that “if you are not embarrassed by the first version of your product, you’ve launched too late”, for something like this, I think the founder(s) made the right call to wait until the product was ready before launching.  At this stage of the game, anything that sounds like yet another hyped up app, and asks me to connect all my social networks when I first log in, etc. had better deliver some real value quickly for me to give it a real chance, and that was the case here.  As the founder Steve Greenwood  has apparently been mulling over this concept for many years, the temptation to release early must have been strong, particularly as it sounds like several startups are working on related concepts, including for example FullContact, but from my user’s standpoint, it was well worth it.

A few other aspects of the product (and its launch) that I like:

– I like that Brewster was clearly thought through as a data product – while the “Favorites” tab has an emotional and aesthetically pleasing aspect to it (depending on how attractive one’s friends are, at least…), the rest of the app is very data-centric: the “Lists” tabs has some interesting automatic categorization (I have 171 friends who are ‘Managing Director”, apparently, does that mean I’m old?), while the “Search” tab is awesome, with good suggested searches and the ability to uncover all sorts of interesting common interests across my contact list.

– While everything is automated, I like the fact that the product made me work manually to create my list of “favorites”.  That actually increased my personal investment into the product, and makes me less likely to discard it.

–  I really like that Brewster did not use any of the tired “virality” tricks that have become so common place.  No automatic posting on my Facebook newsfeed; no “Sent using my Brewster address book” tag line in emails, etc.

– I was impressed with the email I got to announce that my account was ready, personalized with pictures of some of my key contacts – great way of delivering a unique experience before I even started using the product in earnest.

The data privacy issue (and the fairly dramatic reactions to it) are of course a concern. I’m actually surprised that I don’t care more about it, personally — I guess I have gone pretty far down the path of accepting some privacy risk (as long as it’s not banking information), in return for getting a lot of value from the product, which I feel is the case here.  But obviously many people will feel differently, and this could sink the company entirely, if not properly addressed.

One functionality that I don’t find as impressive, at least as of now, is the “Updates” section — what it has surfaced so far (birthdays essentially) is not particularly interesting.  What would be really cool, eventually, would be an integration with Newsle, to get news about your friends.  Oh wait, add to this an integration with Cue, as well.  All built in natively into my iPhone address book and calendar.  Ok, so, maybe that’s a bit much to ask.  In the meantime, Brewster is already one of the most interesting apps I have seen in a long time.

There are many roads to success: The Buddy Media example

It’s been a few days now since their acquisition was formally announced, and I continue to be fascinated by the Buddy Media story.  But what fascinates me is less the company itself and all the things that make it great –  and instead the fact that its success tests the conventional wisdom of what makes a venture successful.  Rightly or wrongly, investors, prospective employees, the press, and anyone who tries to predict the highly unpredictable fate of startups, tend to default to some common assumptions about what’s going to work and what isn’t.  The Buddy Media story challenges that conventional wisdom in some interesting ways:

1.  NYC is not a good place to start an enterprise software company

It’s a bit ironic that, for all the talk about NYC being a media and eCommerce hub, the largest acquisition in five years would be an enterprise software company.

2.  It takes forever to build a successful enterprise software company.

It took Buddy Media less than 5 years from start to success, including an initial pivot.  

3.  To build a successful enterprise software company, you need technical co-founders, or at least a technical CEO

Buddy Media’s CEO is a serial entrepreneur with two degrees in journalism.  Buddy Media’s COO is a serial entrepreneur with a background in business development and marketing and a degree in economics.  The other co-founder and Chief Strategy Officer is a digital branding and marketing expert with a degree in Broadcasting and Mass Media.  

4.  Selling to marketers and advertisers is a really tough business.

Fortune 500 marketers and advertising agencies are indeed a tough audience – long sales cycles, often low budgets, a preference for homegrown solutions, a reluctance to buy what others in the industry purchase: not easy.   But the Buddy Media success shows that it can be done, with the right execution: build the best product in your category, focus on sales, make friends in the right places, hire some key people from agencies, and work really hard.

5.  Be really careful with strategic money

Buddy Media took a strategic investment from advertising leader WPP, which ended up substantially accelerating their business.

6. Service companies can’t become product companies

After an initial pivot, Buddy Media had to turn themselves into a service company to survive the 2008 economic recession.  James Altucher has a really interesting post on Techcrunch that describes this phase.  Somehow, they were able to gradually build a product offering.  

7.  The best founders are young and single

Two of the co-founders of Buddy Media are married.  On top of that, they have three children.  While there are famous examples of homeruns started by married founders (Cisco, VMware, etc.), in my experience, behind closed doors most investors think it’s a terribly risky idea.   The Buddy Media story shows that where there is will there is a way: founders with family obligations can still endure the rollercoaster lifestyle of the startup world.

 

Working with big companies: 10 practical tips for startup founders

If you’re a startup founder, a day will come, generally sooner rather than later, when you have to deal with a big company – whether that’s a Fortune 1000 company you’re trying to sell something to, a large advertising agency you hope will drive some advertising dollars your way, or a media company you want to strike a partnership with.   You may have been successful “selling” your vision to a group of angels or VCs and raise some money, but selling to a large company (and in “selling”, I include all forms of partnerships and other business development efforts) is a different animal altogether. For the last three years or so, I’ve been on the big company side and have heard many startups pitch a business relationship.  The following tips – some trivial and slightly tongue in cheek, others more substantial – are based on patterns and issues I’ve seen over and over (presented in no particular order of priority).

1.  Read a few sales books.   Our startup culture very much celebrates product people (those who, like Steve Jobs, are able to create “stuff that people want”), and tech talent (the people who actually build the product).  Some iconic founders of the previous decades may have been sales people (Larry Ellison being one example), but sales seems to have fallen out of favor as a key part of any founder’s skillset – you’ll hardly ever hear any VC express a strong preference for CEOs who have a strong sales background, the way they rave about technical CEOs.  One consequence of this is that many startup founders (especially the younger ones, but not only) come equipped with incredible product savvy, but seem to have spent very little time learning how to sell.  Selling to a large company is not just a question of presentation, it’s also about navigating a complex organization and being able to qualify an opportunity –I find that startup founders often fail to ask some basic questions about budgeting cycles, decision process, etc., and end up not being able to truly appreciate whether they have a real opportunity or not.  The good news is, there’s tons of literature out there.  Sure, many sales books have cringe worthy titles, and none of them are perfect, but after reading a few of those, a number of important principles emerge.  Worth investing some time reading a few.

2.  Hire a sales person.  This flows from the previous point.  No question, founders should be the initial sales people at their startups: there’s no better way to get market feedback and fine tune your value proposition.  But I’m often surprised by how long startups wait before bringing in their first sales (or “biz dev”) person on board.  I’m all in favor of building viral buzz about your product through blogs and social media, and using other innovative techniques to increase your inbound leads. But in many cases, all those techniques only take you so far, and at some point, particularly if you sell to large companies, you’re going to have to go through a series of in-person sales meetings.  Like for most things in life, experience helps, and in my opinion, a combination of an experienced sales (or biz dev) person and a product/tech founder proves very effective in a meeting with a big company.

3.  Play down the startup vibe.  Sure, Zuckerberg wears sandals in business meetings (at least in the movie), but for almost everyone else, there’s very little upside to showing up in a hoodie and sneakers at a meeting where most people are going to wear ties and business suits.  The startup tech world may have its own, idiosyncratic rules and codes, but when it comes to selling to a large company, it’s back to reality.  Those people don’t read TechCrunch every day (if ever), and they will have most likely no idea who your hotshot investors are.  Do yourself a favor and don’t show up looking like a college kid, because in large companies, recent college graduates are the people at the very bottom of the totem pole, not the people you invest a significant amount of time and resources doing business with.

4.  Do not play with your phone during the meeting.  Ever.  Can’t tell you how often this happens. It typically goes down something like this.  Three founders or team members of the startup show up at the meeting.  One ends up being the lead presenter and fielding most of the questions.  Another one says something every 10 minutes or so, and looks bored and disengaged the rest of the time.  The third one spends the entire meeting playing with their iPhone (and I’m not talking about taking meeting notes).  Guys, seriously? Remember, people will rarely call you on it, but that doesn’t mean you got away with it.

5.  Come prepared.  This should be obvious, but it’s not, and if you are truly well prepared for a meeting, it can be a major differentiator playing in your favor. Unlike an investor pitch, a pitch to a big company is not about you and how awesome your product is.  It’s about how you can help the big company solve a specific problem. You should come in knowing everything you can read about the big company, and have ideas about where and how you could help.  If you show slides, insert screenshots of the big company’s products in your deck. Your demo should be using examples relevant to the big company, or at a minimum, to whatever industry the big company operates in.  If you truly want to make an impression, build a simple demo just for the meeting.  Regardless, your demo should work – send the link to your host in advance to make sure the demo is going to work from within the firewall.  If this is a key meeting for you, you should spend days, not hours, prepping for it.

6.  A sales meeting is not a mentoring session.  Again, something I’ve seen a few times – your big company hosts may be really friendly, they may show genuine interest in hearing your story, and they may have experience that is very relevant to your needs and challenges.  Listen to their feedback and ideas if they offer them, but remember that you’re in a sales meeting.  Resist the temptation to ask questions about how they were able to solve specific problems, or what they’d do if they were you, etc.  Overall, one of the things they’re trying to establish on their end is that, while you’re a startup, you’re already pretty solid and it’s generally safe for them to work with you.  Asking this type of questions is not going to help.

7. Be patient.  Getting stuff done with a big company takes time.  Most people understand that, but they often attribute it to the fact that large companies have more processes, approval layers, lawyers involved, etc.  That is certainly true.  But the more fundamental (and scarier) reason for it is that large companies typically care about whatever business deal you’re discussing a lot less than you do.  Entering into a business relationship with a startup rarely moves the needle for them, at least not in a substantial and immediate way.  They can have a genuine interest in working with you, but they rarely feel true urgency.  Of course, from the startup’s perspective, it is frustrating because that deal can be a make or break moment.  Most techniques you may use to create a sense of urgency are likely to come across as a gimmick, and should be used with caution. Recognize that reality and plan accordingly.

8. Don’t beat a dead horse.  Being patient doesn’t mean that you should wait around forever.  For some reason, large companies, just like some VCs, rarely actually say “no”.  If there’s a fit, it should be fairly obvious after a couple of meetings.  If you’re going from meeting to meeting with different people each time, if getting people to return your calls feels like pulling teeth, or if they mention how working with you may make sense for a big project that they’re going to start next year, it’s unlikely anything substantial is going to happen for you anytime soon.  Learn to recognize when the opportunity is not going anywhere, and move on.

9.  Don’t forget the biz dev guy (or gal). You’ve probably heard (or experienced) how things work before:  your first point of contact at a large company will typically be their business development people; while it’s perfectly fine to start with them, you’ll want to quickly find an internal champion, preferably someone who has P&L responsibility and real decision power.  The twist I would add is this: don’t drop the biz dev person once you’ve found your champion. The person you thought was going to be your champion may not turn out to the right person, they may get too busy, change jobs or lose interest.  The biz dev person is your long-term ally within the large company, because their performance is often measured internally based on the number of opportunities they bring in that end up with an actual deal – so their interests are aligned with yours and they’ll want to make you successful.

10.  Be careful with big company politics.  Like any human organization, large companies are fraught with politics and as an outsider, it’s unlikely you’re going to be able to play them right.  So stay away as much as you can. Be transparent, keep everyone in the loop, don’t make comments about people, don’t take sides.  Don’t shop around from department to department in the hope you’ll find someone who’ll bite, unbeknownst to all the other people you’ve met with previously.  Don’t suggest strange things like making intros between employees of the same company (in most companies, they can pick up their phone).   Invest time in getting to know your contacts at the big company, and make them look good in front of their bosses.