Startup Feeders

Which companies have the generated the greatest number of Founders as of today? 

If you want the tldr, scroll to the bottom, but would advise you read the post as it explains how the data was gathered and methodology around that.

The above question came to mind during the current debate as to why Amazon left NYC for their HQ2 and what the impact will be (that topic requires a whole separate blog post).  Many folks in the NYC tech community wanted Amazon to open an office here, partially as there would be a side benefit in that startups could be created by ex-Amazon employees (Amazon planned to hire 25K+ people in NYC, they have 8K+ currently based in NYC).   This perspective led to me to dig into some data to see if Amazon does generate startup Founders and if so, how many and what scale?

All the data came via Linkedin, through their advanced query.  In the query, I created a few filers:

Title: Co-Founder or Founder.  I wanted to know which individuals indicate that they are CURRENTLY Founders.  This doesn’t include people who were Founders at some point and are now doing something different.  It also doesn’t specifically filter for if they are a Founder of a tech startup or not.  While most of the people who are captured are likely tech Founders, some might be Founders of VC firms, consulting firms, non tech companies, etc.  I specifically didn’t want to search for the title “CEO”, as some CEOs are not the Founders of the companies they are currently leading.

Relationship: 1st Degree Connections and 2nd Degree Connections. Majority of my LinkedIn connections are VCs, Founders and tech operators.  I only captured people in my more immediate network.  If you are a startup Founder, the odds that my 1st and 2nd Degree connections having not connected with a tech Founder via LinkedIn is pretty low.

Geography:  San Francisco Bay Area, Greater Seattle Area and Greater New York City Area.  I only wanted to look at three geographies.  The only reason I included Seattle, is that I wanted to understand what impact Amazon has had in terms of generating Founders in Seattle, as a way to benchmark Amazon vs other large tech companies that are HQ’d in SF Area and NYC Area.

Company:  I only looked at PAST companies.  Obviously, it is hard to be a Founder of startup and work at another company.  I looked mainly at some of the large tech companies out there, I feel like it is pretty inclusive of most of the companies that have generated startup Founders.  I didn’t query the most recent past company (not sure if that is possible), meaning this data captured people who most recently worked at Facebook or worked at Facebook several jobs ago.

A few disclaimers:

  1.  I realize that the data doesn’t look at “successful” startups.  I understand why that is interesting but it is less relevant for what I wanted to accomplish.  I would add the word successful can be interpreted in various ways.  In addition, if you did look at successful Founders, it is a lagging indicator of which companies used to generate successful Founders and doesn’t necessarily mean they will create successful Founders going forward.  That being said, if you decide to pull this data, it would be an interesting blog post, so encourage you to do so.
  2. These large companies didn’t necessarily “generate” these Founders.  “Generate” was a word that best fit what I’m trying to accomplish, but please don’t get hung up on it.  These individuals simply worked for these companies in the past.  That being said, there could be some credit given to these companies for helping create Founders.
  3. To reiterate, some of these Founders are not necessarily working on tech related startups.

A few key observations (I have a bunch but wanted to limit it for the sake of brevity):

  1. regarding Amazon.  If you look at the Seattle column data, they grossly underperform Microsoft in terms of startups Founders, 812 vs 223.  I assumed the two would be pretty close.  On a more positive note, Amazon faired decently in NYC, which was surprising.  Between Seattle, SF and NYC, they only had 475 Founders in total, that seems really low relative to how large that company is and how long they have been around.
  2. Goldman Sachs!!!  Wow, I didn’t expect them to have that many Founders.  There were #1 in NYC and did well in SF too.
  3. IBM did surprisingly well in SF , NYC and Seattle.  Didn’t see that coming but they do have over 500K employees, so the odds they generate startup Founders is high.
  4. Seattle is really a two company town when it comes to Founder creation.  Microsoft and Amazon.  I didn’t expect anything different.  Over time there will likely be more balance as there are some interesting late stage startups that will generate Founders in the next decade.
  5.  SF has a strong concentration with 10 companies that really outperform in terms of startup generation.  In comparison, NYC seems to have a longer tail of companies that generate Founders, I think that is more healthy for a tech ecosystem.  This partially supports my argument that Amazon leaving NYC isn’t going to make a big impact in terms of future startup formation.
  6. Facebook??  I really expected a much higher number from them, that was quite the shock.  I can foresee people making the argument that Facebook Founders are better than other tech company Founders, maybe, don’t have that data but from an absolute number, that is really low.

 

2019 – a ton of $ floating round

2018 has been an ugly year for many public companies.

2018 has been a great year for many private companies and expect 2019 to be as good.

If you are a Founder/CEO of a VC backed startup, you shouldn’t feel down about access to capital, there is a ton of cash floating around.

In 2018, $75 BILLION has been raised by US based VC firms.  The $75B is an aggregate of 286 new VC funds raised in 2018.  The $75B doesn’t include non-US based firms who are actively investing here or corporate investors or family offices or Softbank.  Point being is there a lot of capital available if you are staying private and need more money.

The put the $75B into context, if you look at the VC fundraising data during the top of the last market in 2007, the total was almost exactly half, with $37B in capital raised.  So assuming we are going into a downturn, there 2x more capital this time vs 2008.

Here is a list of the 50 largest VC funds that were raised in 2018 , go get that money!

Fund Size ($M) Fund Name
8,000.00 Sequoia Capital Global Growth Fund III
6,300.00 Insight Venture Partners X
3,750.00 Tiger Global Private Investment Partners XI
2,500.00 Petershill Private Equity
1,913.31 Lime Rock Partners IV AF
1,850.00 Bessemer Venture Partners X
1,800.00 Sequoia Capital China Growth Fund V
1,500.00 Norwest Venture Partners XIV
1,375.00 General Catalyst Group IX
1,360.00 GGV Capital VII
1,350.00 NewView Capital Fund I
1,300.00 Providence Strategic Growth III
1,200.00 JMI Equity Fund IX
1,050.00 Lightspeed Venture Partners Select III
1,000.00 Thrive Capital Partners VI
1,000.00 Index Ventures Growth V
800.00 Battery Ventures XII
750.00 Lightspeed Venture Partners XII
700.00 Main Post Growth Capital II
670.00 Silversmith Capital Partners II
650.00 Index Ventures IX
650.00 Accel-KKR Growth Capital Partners III
650.00 Bain Capital Venture Fund 2019
640.00 8VC Fund II
638.54 Meritech Capital Partners VI
600.00 Lime Rock Partners VIII
600.00 Charles River Partnership XVII
550.00 Sequoia Capital China Venture Fund VII
535.00 Level Equity Growth Partners IV
520.00 Lead Edge Capital IV
500.00 Bertram Growth Capital III
460.00 GGV Discovery Fund II
450.00 Battery Ventures XII Side Fund
450.00 Ampersand 2018
450.00 Matrix Partners XI
435.00 Emergence Capital Partners V
420.00 Ribbit Capital V
400.00 Investcorp Technology Partners IV
400.00 Venrock Healthcare Capital Partners III
400.00 Redpoint Ventures VII
400.00 Scale Venture Partners VI
392.00 Sprout Endurance Partners
362.24 Cordillera Investment Fund II
360.00 B Capital Fund
360.00 Forerunner Partners IV
350.00 Capricorn Healthcare & Special Opportunities II
350.00 G2VP I
350.00 Trinity Hunt Partners V
350.00 True Ventures VI
350.00 Alliance Consumer Growth Fund IV

 

$50M+ deals in NYC

There has been a flurry of $50M+ rounds announced for NYC HQ’d startups, so was interested in taking a look at data and comparing 2018 vs prior years.  see below.

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As you can see, 2018 has been an incredible year in terms of # of deals and dollars.  In 2012 there were zero deals that were $50M+ in size, which is eye opening when you look at the 2018 data.

It is really amazing to see the growth of the startup community in NYC, so many investors are excited about what is happening.  On the investor front, I was wondering which firms have been the most active in these $50M+ round sizes.  see below.

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The middle column is the most relevant as it captures which firms have been the most active in the past two years.  Over half of these investors have offices in NYC, so the days of having to fly to Sand Hill to raise large rounds could be coming to end potentially.

Does being Founder lead to being the best VC?

I don’t believe that being a Founder of tech startup gives you a better chance of being the best VC.  I have never seen any data that confirms this, if you have it, please share that in the comments section.  On the contrary, if you look at some of the best VCs of all time, they were NOT Founders of tech startups.  The great thing about this industry is that regardless of your background, you can be a great VC Identifying who is going to be the best VC, when a VC is just starting, is extremely difficult, which is why the job of being a LP is so challenging.

Here is the tweet thread that got me thinking about this topic:

 

 

 

 

 

 

 

 

 

 

I do recognize that specific words are critically important for this debate.  Entrepreneur vs Founder is a material difference.  The original premise and original tweet was about “Founder” not Entrepreneur .  That being said, most of folks on the list provided below were neither an entrepreneur or founder, a few did work for tech startups though but that is different debate.

Here is a list of folks who meet all of the following parameters:

  1. They were not tech Founders before they started leading venture rounds
  2. They started leading venture rounds (Seed/A/B) post 2005
  3. They have substantial realized gains (not looking at TVPI), meaning they distributed meaningful money to their LPs (DPI)

If you know VCs that meet ALL of these parameters, please let me know in the comment section and will add them.  In no particular order:

Rebecca Lynn – Canvas

http://www.canvas.vc/team-member/rebecca-lynn/

 

Ian Sigalow – Greycroft

https://www.greycroft.com/people/ian-sigalow/

 

Kirsten Green – Forerunner

https://forerunnerventures.com/team/kirsten-green/

 

Chetan Puttagunta – Benchmark

https://www.linkedin.com/in/chetanputtagunta/

 

Shana Fisher – Third Kind

https://www.crunchbase.com/person/shana-fisher#section-overview

 

Mamoon Hamid – Kleiner Perkins

https://www.kleinerperkins.com/people/mamoon-hamid

 

Tony Florence – NEA

https://www.linkedin.com/in/toflorence/

 

Mike Volpi – Index

https://www.indexventures.com/team/mike-volpi

 

Roger Ehrenberg – IA Ventures

https://www.crunchbase.com/person/roger-ehrenberg

 

Matt Cohler – Benchmark

https://www.linkedin.com/in/mattcohler/

 

Aydn Senkut – Felicis Ventures

https://www.felicis.com/team/aydin/

 

Hans Tung – GGV Capital

https://www.ggvc.com/team/hans-tung

 

Active Early Stage Investors in NY based companies (Jan ’17 to Aug ’18)

In preparation for an event that we run on a regular basis, called Fundraising Workshop, wanted to provide an update on some of the most active early stage VCs (Venture Capital) who are investing in NY based startups.

A few items before providing you the information.

  • The data was pulled via CB Insights
  • The investors do not need to be based in NY but have to be investing in NY based companies
  • The date range was Jan 1 2017 to August 13 2018
  • It only includes venture capital firms and excludes accelerators, angels, corporates, etc.
  • CB Insights doesn’t provide data on who is leading the rounds, so the assumption with these firms listed, is that they participated in the round and not necessarily lead, a critical distinction when fundraising.  If you are fundraising, you need to do more homework to figure out is actually leading rounds.

The data is below.

Most active VCs who participate in sub $2M rounds, see below.  Many of the seed and pre-seed rounds are sub $2M in size, so if you are looking for firms who are active at this size, this is a good target.  Now, the data around pre-seed and seed is challenging since many of these rounds are not announced , which makes it is difficult for CB Insights to capture.  So this list is not comprehensive but I think it provides a lot of signal on the right firms to reach out to.

sub $2M rounds

Most active Seed VCs, see below.  In this query and unlike above, I didn’t put parameters on the size of the seed round.

Seed

Most active Series A VCs, see below.  Again, no parameters on the size of the round.  As I mentioned in beginning of the post, I am unable to query who is “leading” these particular round.  So some of these firms could be leading and other could be participating in them.

Series A

Slack $7B valuation

As you may of heard, Slack is supposedly raising a $400M equity round at  a$7B valuation.

I wrote a blog post about Slack’s last announced valuation in 2016, when it was $3.8B.  The tldr was that if Slack was a public company, it would be trading a 42x revenue run rate.  In that blog post, I referenced the Bessemer Cloud Index, which provides perspective on what enterprise saas public companies are being traded at.  The median revenue rate for these companies is 8.5x, but those public companies are growing at a much slower pace, so it was expected that Slack would earn a large multiple.  That being said, I thought 42x was a bit rich.

In the article mentioned in the first sentence, the had a chart: Slack has indicated they have 3M+ paid users, see below.

slack-growth-2018-stacked (1)

Per Slack pricing page,  they charge between $6.67 and $15 per paying user per month.

So, based on 3M paying users, they are between $240M  ($6.67/user/month x 12 months x 3M paid users) in annualized revenue run rate and $540M revenue run rate.  If you split the difference, lets assume they are a $390M annualized revenue run rate.

If you take the valuation of $7B and divide it by $390M, they would be trading at 18x annualized revenue run rate.

I think 18x is a fair valuation given their grow rate, although Slack paid user growth is slowing, which is expected as the company gets larger.  The closest public saas comparison I would find is Shopify, which is trading at 17x annualized revenue run rate.

THE END.

 

Top NYC growth startups?

Are these the top growth startups in NYC?  I don’t know, but lets take a look at some PUBLICLY available data from LinkedIn, Glassdoor and CB Insights.  If you want a TLDR, scroll to the bottom.

As many of you are aware, they are so many listicles circulating online about the top companies, they are rarely data driven and read like who is the most popular, not who is best or fast growing.  They typically are about driving pages views.   Wanted to take a look at PUBLIC data to see if I could derive some signal from the noise.

Another lens that I thought about was, if I was going to join a startup, how would I choose which startup to join?  It is a very difficult process to narrow down the list.   As an example, on AngelList, there are ~2,900 startups in NYC, of which ~700 have posted a full time job on that site in the past seven days.

One of the public data sources is Glassdoor.   If you aren’t familiar with this service, it is essentially Yelp for employees.  Before you get up in arms, I realize that some disgruntled employees will post negative items on there but I think if there are enough inputs, it can provide some signal on the health of the company.  Not only can you provide input on the company but on the CEO as well.  For this exercise, in order to qualify, you had to have at least 20 reviews, which I thought was a large enough sample size that if there were some disgruntled employees with an ax to grind, it could be balanced by happy current/past employees but I do realize this can be gamed.  Regardless, there is some signal that you can derive from this service.  In addition, the startup needed a ranking of at least 4.6 or greater (max number is 5, larger the number, the better).  See example below.  As a side note, Glassdoor was recently acquired for $1.2B, congrats!

6470598029737984

The other data source was LinkedIn.  If you are in the tech community, LinkedIn gets trashed a lot, primarily by engineers/developers, who get a lot of unsolicited emails from recruiters,  but I can see how that can be annoying.  I don’t think LinkedIn has figured how to deeplink yet, you will see my tweets ranting about this 🙂 .  That being said, if you are in a sales or relationship driven role, this service is invaluable.  If you pay for their subscription, you get access to two data points that I used for their exercise,  number of employees and growth rate.  See below as an example for a NYC startup, Lemonade.

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Number of employees is an important data point, as it CAN provide some signal on potential top line revenue.  If you are a startup that has a clear revenue model, I assume that every employee generates at least $100K in revenue, which takes into consideration their salary, benefits and overhead (office space, taxes, electricity, etc).  So in this example, I would assume that Lemonade is generating ~$9M ($100K x 91 employees) in top line revenue.   I don’t know if this is accurate in this particular case but that would be my assumption.   For companies who don’t have a clear revenue model, I would obviously assume no revenue.  Feel free to disagree with me on this, comments are open and would like your feedback on this.

The other data point that is important is growth rate.  For this exercise, I took a look at the 1 year growth rate, in the example above, it is 69%.   In order to qualify for this exercise, I took a look at companies that are growing at least 20% in the past year.

Lastly, utilizing ChubbyBrain Insights (aka CB Insights), I took a look at a how much VC funding the company has raised.  Two data points that you can generate some signal, total funding amount and last round of financing.  If I were to join a startup, knowing when they raised their last round is critical, as it provides some signal on how much cash they have remaining.  How much total funding can provide some signal as well, especially if have ownership in the company is important to you.  Generally speaking, the more the company has raised, the less ownership they will provide to a new employee.  So if ownership is important, you might want to take a look at this data point.  For this particular exercise, I didn’t require the company be VC backed or that it has raised a new round of financing but I did provide info on that for you on Airtable (PS, I love their service)

So without further ado, here are the companies that qualified based on the all the criteria provided above (PS, if I missed you by accident, please lmk and I will update the post).

In alphabetical order:

  • Augury
  • BounceX
  • Button
  • CB Insights
  • Compass
  • Convene
  • Dataiku
  • Elite SEM
  • Fundera
  • Greenhouse
  • InVision
  • Justworks
  • Kustomer
  • Lemonade
  • SeatGeek
  • Updater

Special thanks to Bella Rubin for helping with gathering data for this post.

PS, another signal that was derived from this exercise, is looking at which VC firms were the most prevalent in backing these companies in the early days (Seed & A rounds only).  See the Airtable referenced above for a link to that information.  There were five firms (all NYC based) that showed up on two occasions: Lerer Hippeau, First Round Capital, Thrive Capital, FirstMark Capital and Box Group.  The signal strength is a bit low as 2 out of 15 is not substantial but still wanted to highlight it.

PSS, this comment from the CEO of CB Insights is a worth highlighting.  Looking at capital efficiency is good lens when taking all the data points into consideration.

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