2. 2
What’s going on in the public markets?
What are all these “unicorns”?
What’s going on in venture capital?
3. 3
0
20
40
60
80
100
1980 1985 1990 1995 2000 2005 2010
US tech IPO & private funding ($bn)
The starting point – what’s going on?
34 years of US tech funding
Source: Capital IQ, Jay Ritter, University of Florida, NVCA, a16z
IPO
Private
2014
4. 4
0
20
40
60
80
100
120
140
1980 1985 1990 1995 2000 2005 2010
US tech IPO & private funding ($bn, 2014 dollars)
…inflation adjusted
(Can you spot the bubble?)
Source: Capital IQ, Jay Ritter, University of Florida, NVCA, a16z
IPO
Private
2014
7. 7
0
10
20
30
40
50
60
0
200
400
600
800
1,000
1,200
1,400
1990 1995 2000 2005 2010 2015
ForwardP/Emultiple
Indexprice
S&P IT index (adjusted for inflation)
But, earnings, not P/E multiples, are growing
This time, profits are driving returns – in fact, P/E multiples are at early 1990s levels
Source: Bloomberg
Forward P/E
multiple
Index
8. 8
0%
5%
10%
15%
20%
25%
30%
35%
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
S&P IT index market cap as % of S&P 500 market cap
Tech’s contribution to S&P is flat
Public tech companies’ share of the overall US stock market is stable for 14 years
Source: Bloomberg
9. 9
0
1
2
3
4
5
1995 2000 2014 2020
Billion people online
And market size is for real this time
The internet is working now – from 40 million people online to 4 billion
Source: ITU, a16z
Smartphones
People online
10. 10
$0
$100
$200
$300
$400
$500
$600
$700
$800
$900
$1,000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Tech funding per US internet user ($, 2014 dollars)
Funding per person online
US funding per internet user has been roughly flat since the bubble
Source: Capital IQ, ITU, US Census, a16z
Public $ / user
Private $ / user
11. 11
0
50
100
150
200
250
300
350
400
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
US online revenues ($bn, 2014 dollars)
People are spending (lots of) money online
US ecommerce + online ad revenue has increased ~15x since 1999
Source: US Census Bureau, IAB/PwC, a16z
Online
advertising
Ecommerce
12. 12
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
US retail revenue ($bn, 2014 dollars)
And there’s more to come
Ecommerce is still only 6% of US retail revenue – far more room to grow
Source: US Census Bureau, a16z
Ecommerce
Retail ex.
Ecommerce
13. 13
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1980 1985 1990 1995 2000 2005 2010
US tech funding (IPO + private) as % GDP
So funding as share of GDP looks moderate
Steady growth in funding reflects the scale of the opportunity
Source: Capital IQ, Jay Ritter, University of Florida, NVCA, BEA, a16z
2014
14. 14
“It’s different this time.”
*2014 dollars, venture & IPO. Source: Capital IQ, Bloomberg, BEA, ITU, US Census, Jay
Ritter, University of Florida, a16z
1999 2014
US tech funding $* $71bn $48bn
Funding as % US Tech GDP 10.8% 2.6%
S&P IT index forward P/E 39.0x 16.1x
Global internet population 0.4bn people 3bn people
US ecommerce revenues* $12bn $304bn
Number of IPOs 371 53
Median time to IPO 4 Years 11 Years
17. 17
The headlines are ominous.
61 US tech “unicorns” (private company with
>$1bn valuation).
75% of the largest VC investments have
been raised in the last 5 years.
Source: Capital IQ, CB Insights, a16z
18. 18
0
20
40
60
80
100
120
140
1997 1998 1999 2000 2011 2012 2013 2014
US IPO and private tech funding by round size ($bn, 2014 dollars)
But, the funding surge is in late-stage only
The funding explosion in 1999-2000 was at every stage – in 2014 it isn’t
Source: Capital IQ, a16z
Private $40m+
Private $1-40m
IPO
19. 19
0
2
4
6
8
10
12
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Aggregate funding for top 20 US tech private deals ($bn, 2014 dollars)
Yes, there is more funding for larger deals
The top 20 private deals have suddenly become very large
Source: Capital IQ, a16z
20. 20
0
2
4
6
8
10
12
14
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Aggregate funding for top 20 US tech deals ($bn, 2014 dollars)
But, this is just a rebalancing from IPOs
The top 20 deals used to be mostly IPOs – now they’re almost all private
Source: Capital IQ, a16z
IPO
Private
21. 21
0
50
100
150
200
250
300
350
400
0
10
20
30
40
50
60
70
80
1980 1985 1990 1995 2000 2005 2010
NumberofIPOs
IPOfunding($bn)
US tech IPO funding ($bn, 2014 dollars) and number of IPOs
And tech IPOs are essentially dead
The tech IPO market is at early 1980’s volumes
Source: Jay Ritter, University of Florida
IPO funding
Number of IPOs
2014
22. 22
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1980 1985 1990 1995 2000 2005 2010
US tech IPO & private funding
IPOs used to be the norm – but no more
For most of the ‘90s the majority of tech funding was public – this has reversed
Source: Capital IQ, Jay Ritter, University of Florida, NVCA, a16z
IPO
Private
2014
23. 23
0
50
100
150
200
250
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Median revenue at IPO ($m, 2014 dollars)
The bar for an IPO is now much higher
It used to be routine to hit $20m revenues and go public – not any more
Source: Jay Ritter, University of Florida
24. 24
Many companies that would in the past have
done an IPO are now doing late-stage
private rounds.
As you get to $40+ million rounds, these are
effectively “quasi-IPOs.”
These deals have different financials,
investors, and risk profiles to classic venture.
25. 25
0
10
20
30
40
50
60
70
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
US tech IPO vs. quasi-IPO late-stage rounds ($bn, 2014 dollars)
Mix shifted from IPO to late-stage rounds
Quasi-IPOs are now 75% of investment dollars vs. 40% in the bubble
Source: Capital IQ, a16z
Private $40m+
IPO
26. 26
0
20
40
60
80
100
120
140
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
US tech IPO versus quasi-IPO late stage rounds ($bn, 2014 dollars)
Public and private tech funding merge
And at modest levels – even combining public and private financing
Source: Capital IQ, a16z
Private $40m+
Private $1-40m
IPO
27. 27
As IPOs are delayed, returns move from
public to private investors.
Thus, traditional public market investors and
buyout funds, who would not typically invest
in companies at this stage, have moved into
the private markets.
28. 28
0
5
10
15
20
1998 2000 2002 2004 2006 2008 2010 2012 2014
Number of top 20 US tech deals with participation from non-traditional investors
Non-traditional investors drive growth rounds
Source: Capital IQ, a16z
29. 29
Because the returns have moved
Tech returns used to be in public markets – have now shifted to private
* Market cap at IPO. Source: Capital IQ
0%
20%
40%
60%
80%
100%
Apple
(1980)
Microsoft
(1986)
Oracle
(1986)
Amazon
(1997)
Google
(2004)
Salesforce
(2004)
LinkedIn
(2011)
Yelp
(2012)
Facebook
(2012)
Twitter
(2013)
Private versus public market value creation for select public US tech companies
Public value
creation*
Private value
creation
30. 30
Almost all the returns are now private
Old world tech giants returned plenty in public markets – new ones have not
Note: see endnotes for methodology. Source: Capital IQ, Pitchbook, Quora, a16z
0x
200x
400x
600x
800x
1000x
1200x
Apple
(1980)
Microsoft
(1986)
Oracle
(1986)
Amazon
(1997)
Google
(2004)
Salesforce
(2004)
LinkedIn
(2011)
Yelp
(2012)
Facebook
(2012)
Twitter
(2013)
Private versus public market return multiples for select public US tech companies
Public value
creation
Private value
creation
32. 32
741
374 369
277
212 199
171 151 151 145
111
77
40 38 29
0
100
200
300
400
500
600
700
800
Market Cap ($bn)
Finally, all unicorns combined = ~1 Facebook
If you’re investing for growth, would you rather own 2/3 of Microsoft or the index of
unicorns?
Note: Market cap data as of 6/5/15. Source: Capital IQ, CB Insights
All 61 $1bn+
US tech
“unicorns” as
of 6/9/15
All $1bn+ US
tech
“unicorns” ex
Uber
34. 34
0
20
40
60
80
100
120
1970 1975 1980 1985 1990 1995 2000 2005 2010
US tech VC fund inflows ($bn, 2014 dollars)
No surge in VC fundraising
Source: NVCA, a16z
VC funding is growing moderately
2014
35. 35
And relative to output, fundraising is down
VC funding as a percentage of tech GDP is down by half from 1980
Note: Value-added Tech GDP used for Tech GDP. Source: BEA, NVCA, a16z
0%
3%
6%
9%
12%
15%
18%
1980 1985 1990 1995 2000 2005 2010
US tech VC fund inflows as % of tech GDP
2014
36. 36
0
20
40
60
80
100
120
140
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Dollars raised by round cohort and year ($bn, 2014 dollars)
Large rounds raise lots of money (obviously)
Overall dollars raised are dominated by quasi-IPOs (which arguably aren’t even really VC)
Source: Capital IQ, a16z
Private $40m+
Private $25-40m
IPO
Private $10-25m
Private $1-10m
37. 37
0
10
20
30
40
50
60
70
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Dollars raised by round cohort and year ($bn, 2014 dollars)
Funding looks more moderate elsewhere
The total money going into deals under $40m is back to 2001 levels
Source: Capital IQ, a16z
Private $25-40m
Private $10-25m
Private $1-10m
38. 38
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Companies raising rounds by round cohort and year (000s)
Late-stage is a small part of the ecosystem
But things are changing elsewhere, as the number of companies raising capital has doubled
since 2009
Source: Capital IQ, a16z
Private $40m+
Private $25-40m
IPO
Private $10-25m
Private $1-10m
39. 39
0%
50%
100%
150%
200%
250%
300%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Indexed US tech funding for $1m-$40m rounds (2014 dollars)
More rounds, smaller rounds
2.5x more rounds while the round size dropped by a third – the mix is shifting
Source: Capital IQ, a16z
Average round
size
Number of rounds
Aggregate $
raised
40. 40
The collapse in the cost of creating tech
companies in the last two decades means
many more are being created.
With each one needing less money to get
started, there are a lot more small rounds.
That is, there is a surge in seed-stage
funding.
41. 41
0
200
400
600
800
1,000
1,200
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Number of rounds by cohort
Seed rounds have grown dramatically
$1-2m rounds have increased over 7x in the last decade (and this data probably doesn’t
capture all of them)
Source: Capital IQ, a16z
$3-6m rounds
$1-2m rounds
42. 42
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Aggregate US tech investment by round size cohort ($bn, 2014 dollars)
But absolute seed dollars remain small
Amount raised in $1-2m rounds is up 7x over 10 years, but still only $1.1bn (~5% of all sub-
$40m deal funding)
Source: Capital IQ, a16z
$1-2m rounds
$3-6m rounds
43. 43
0
5
10
15
20
25
0 1 2 3 4 5 6 7 8 9 10+
Total private + IPO funding by company age at funding, 1995-2014 ($bn, 2014 dollars)
Company age makes the shift clearer
The bubble saw a surge of funding of very young companies that’s not been repeated
Source: Capital IQ, a16z
1999–2001
2012–2014
44. 44
0
10
20
30
40
50
60
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Total US tech funding by age cohort ($bn, 2014 dollars)
55% of bubble $ to <2 year old companies
Versus 80% of current funding going to +3-year-old companies
Source: Capital IQ, a16z
0-2 years old
+3-year-old
45. 45
0
500
1,000
1,500
2,000
2,500
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Number of US tech deals by company age at round
Deal volume is back up…
More tech companies are being created
Source: Capital IQ, a16z
0-2 years old
+3-year-old
46. 46
0
5
10
15
20
25
30
35
40
45
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Average US tech funding size by age at funding, IPO and private ($m, 2014 dollars)
But round sizes are down for early-stage
Source: Capital IQ, a16z
0-2 years old
+3-year-old
47. 47
0%
50%
100%
150%
200%
250%
300%
350%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Indexed US tech funding for 0-2 year old companies (2014 dollars)
The cost of tech company creation is falling
Source: Capital IQ, a16z
Average round
size
Number of rounds
Aggregate $
raised
48. 48
0%
20%
40%
60%
80%
100%
120%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Indexed US tech funding for 0-2 year old companies (2014 dollars)
Let’s take a closer look at round size
Average round size is flat over the last 6-7 years, while deal count has more than doubled
Source: Capital IQ, a16z
Average round
size
Aggregate $
raised
49. 49
Less money, more money
Which one do you want to believe? Both!
Order of magnitude reduction in the cost of
creating a software company
Shift from expensive hardware and
software to cloud, open source, GitHub,
etc.
So, more company creation, more rounds,
smaller round sizes
The seed surge
It’s never been cheaper to create software
companies
Funding is cheap
But scaling to address 3bn people is not
War for talent (and office space) in SF
Round sizes for hot deals have moved
upwards
But scaling to address the opportunity
costs money
50. 50
The shift in mix
Less money, more early stage
Source: Capital IQ, a16z
70.9
48.1
1999 2014
Total funding by deal type ($bn, 2014 dollars)
$1-10m $10-25m $25-40m $40m+ & IPO
2,192
2,293
1999 2014
Number of companies raising rounds
$1-10m $10-25m $25-40m $40m+ & IPO
51. 51
Round sizes are mostly flat (to down).
Late-stage round sizes are not spreading
down the chain.
It’s never been cheaper to build a tech
company.
Company creation is increasing (good!).
53. 53
A note on data
Sharing the perspectives and analyses presented in this deck required a time series of overall funding. However, there is no source of
comprehensive (let alone granular) deal-level data that goes back before the late 1990s. Therefore, we were obliged to vet and combine
incomplete data from multiple sources.
Where some data sets were more comprehensive on broad parameters but limited in historical range, others were broader than our
definitions of software tech (e.g., they included medical devices). There were other screening differences as well; for example as larger
deals became more commonplace but were not referred to as “venture” funding, we looked to a different source that would allow us to
roll up that deal-level data as shown in this deck.
To ensure as much rigor as possible in sourcing our data, we compared data from several sources against each other and then collated
and de-duped it into a master data set for a few years which we then checked for accuracy across each of those sources to determine
the best ones. While there are many caveats (and counterarguments!) we could make about the data given various tradeoffs, here are
some of the key things to note when reviewing this deck:
1. Historical transaction-level data is much more robust after 1996 than before it. We also had to fuse together different data sets, using
Jay Ritter & NVCA before 1996 and Capital IQ after 1996 and merging them at the join.
2. The data set for age at funding is not complete and becomes less complete the further back we go, especially before 1996. From 1998
to 2001 we are also missing founding year data for 20% of deals, versus 3% for later deals. The missing companies will skew heavily to
small and/or young companies, so adding this data would show an even greater swing than the one we point to in this presentation.
Notes for slide 30: Microsoft, Oracle & Amazon Series A valuations assumed at $3m for illustrative purpose; Series A to IPO represents
return multiple from Series A valuation to market cap at first close post-IPO