They say that whenever two Angel Investors team up, there are at least three investment strategies in play. Here at the AI News, we hope to entice a few well known angels to share their strategies. The post below is by Fabrice Grinda.
I was reading The Checklist
Manifesto by Atul Gawande which shows the efficacy of checklists in complex
situations. It resonated with me, because Jose & I use a checklist as part
of our angel investing strategy. The checklist does not lead to an invest /
don’t invest answer, but it helps us make sure we cover all the bases and keeps
us grounded. It’s especially useful when we encounter very eloquent founders or
products we love, which tempt us to be less disciplined.
I alluded to the checklist in my
last angel investing blog post, And then there were a 100…,
but here it is more explicitly:
- Is the product live?
- Are the unit economics attractive?
- Do we like the market?
- Do we like the team?
- Do we like the deal terms?
The thinking behind the heuristics
You might argue that as early stage
seed investors we should be willing to invest in pre-product companies.
However, it’s so inexpensive and easy to launch a site these days, that if
someone can’t get the site out of the door with $50-100k of love money, it
speaks negatively of their ability to execute leanly and convince others to
join them. It also makes us question their ability to raise money if they can’t
even get love money from fools, friends and family.
With regards to unit economics, we
don’t expect the business to be large and successful. They would not need angel
money otherwise. $10k / month in revenues are enough. We don’t expect the
business to cover its fixed costs, but we want to make sure the business is
profitable on a unit economic level. We typically invest in a company if the
net contribution margin per customer over a 12 month period is 2x greater than the
customer acquisition cost. We also want to see that the customer acquisition
channel can scale. For instance we want to see that there is enough volume in
the keywords the company buys such that it can increase its marketing budget
from $1k / month to $30k / month without needing to increase the CPCs. There are counter examples of
massive businesses that did not have business models or unit economics for a
long time and figured it out later when they got to scale. Google, Facebook and
Twitter notably come to mind, but it’s a much riskier approach.
Note that our requirement of unit
economics does not mean we expect to see financial projections from startups.
When a plan meets reality, reality wins every time! Startup financial
projections are not worth the paper they are written on. However, if founders
know how much money they are making per customer and know how much each
customer costs them, they should have a good sense of where they can be in 12
months with a $500k – $1 million seed investment.
Attractive unit economics are not
enough. It’s possible that the business has attractive economics in a small
market and is more suited to being a lifestyle business than a venture funded
business. We use our 9 business selection criteria
to evaluate the market.
What makes for a great team varies
based on the category. As we focus on consumer facing businesses we come across
many super smart product driven founders – which we love. It’s also not enough.
In consumer facing businesses, it’s essential to have a viable customer
acquisition strategy. Of late, we have been disappointed by the lack of
business savvy of otherwise super smart, product centric founders. This is
especially true of Y Combinator founders, who also have a tendency to be very
arrogant. This is unbecoming given how early all their businesses are. In
startups so much of the success comes from rapid iteration, entrepreneurs need
to be accept that they don’t typically have the definite answer and that they
will figure it out through execution.
With regards to terms, we are price
sensitive. 99% of startups sell for less than $30 million, many for less than
$10 million. Entrepreneurs think that raising money at a high valuation or with
a high cap is a badge of honor, but raising money at a high valuation prices
you out of exits and makes it harder to raise follow-on capital. There is so
much frothiness in the seed market today that it’s not uncommon to see startups
raising on convertible notes with $5-10 million caps. Given the Series A crunch
and the difficulty of raising follow-on money, we are seeing startups with $5
million in revenues raising at $5-10 million pre. As a result if we deem the seed
valuation too high, we just wait for the Series A.
We also expect all the terms to be
fair, not just the cap on the note. For instance if the company sells before
the note converts we expect to get the greater of whatever our equity stake
would had been if the note converted or a multiple on our investment, not just
our money back. After all we are equity investors, not debt investors. We use
notes only because they are cheaper and easier to setup.
Why this approach works for us
I would actually not be using this
strategy if I was running a $200 million venture fund based in Silicon Valley.
As Peter Thiel points out in his venture class, venture returns follow a power
law distribution (read Blake Masters Class 7 notes for
more details). A VC portfolio makes money if the best company ends
up being worth more than the whole fund. In this type of environment it makes
sense to come up with convictions about companies that can be bring 10x returns
and not worry too much about what the entry valuation is or whether they
already have unit economics. Such a fund does not need to worry about
minimizing losses from bad investments, it’s all about finding THE investment
that will make the fund.
As I previously mentioned, with our
heuristics we would not have invested in Facebook, Pinterest or Twitter. But
it’s also important to note we did not have the opportunity to seed invest in
them either. There are plenty of great companies coming out of New York,
London, and around the world, but if you look at the Internet companies that
created most of the value ($10+ billion exits), they are highly concentrated in
Silicon Valley. I choose to live in New York for a combination of personal and
professional reasons and Jose lives in London. As a result we don’t see the
best Valley deals. If we wanted to be professional angels or venture
capitalists, we would move to the Valley. We don’t intend to do that and thus leave
the best companies to Y Combinator, Ron Conway, Jeff Clavier, Mike Maples,
Founders Fund, Sequoia and the like.
Given we don’t expect to be able to
invest in the next Facebook, Google or Linkedin, we came up with an approach
that makes it probable for us to get 3-5x returns on most deals while
minimizing our downside. That’s why of the 30 exits I had in my angel portfolio
(which don’t include the companies I created or incubated), I made money on 17
and lost money on 13 – a 57% success rate. I made money on many of the exits
that were below $10 million and even several below $5 million. I also managed
to recoup part of my investment on most of the 13 companies that I lost money
on. Overall for these 30 companies, I invested around $2 million and recouped
around $10 million with a 62% IRR.
That’s not to say we don’t have
stellar performers in our portfolio – I made 31x on one of my investments, but
even that standout performance only accounted for 15% of my overall returns.
Admittedly our approach is suited for the limited amount of capital we deploy
and would not work if we had to invest significantly more capital. However, as
we don’t want to be professional investors, it serves our purposes. It allows
us to support many entrepreneurs, while keeping our fingers on the pulse of the
market.
For many entrepreneurs, especially
first time entrepreneurs, our approach works as it increases the probability
that they make money on an exit. On top of that we don’t join boards or have
reporting requirements. We decide rapidly whether to invest or not and give
direct and honest feedback. We also bring expertise on how to maximize unit
economics: long tail dynamic bidding on keywords, purchase funnel
optimizations, liquidity building strategies in two-sided marketplaces, etc.
It’s probably worth pointing out
that the heuristics and strategy are not set in stone. We adapt to changing
market circumstances. I will publish a post in early 2014 detailing how we
modified our strategy in 2013 because of the dual impact of seed stage
frothiness and the Series A crunch. However, even when we change the approach
we keep using a checklist to add rigor our thinking. This might reflect my
Cartesian way of looking at the world or assuage the need of my inner economist
/ management consultant for frameworks and models, but it seems to work.
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The post above appeared originally in Fabrice Grinda's blog, Musings of an Entrepreneur, under the title "Why We Play Moneyball Rather than Powerball." He
describes himself as an Internet entrepreneur, angel investor, student and
lover of life, aspiring Renaissance man and co-founder of OLX, one of the
largest free classifieds sites in the world. He
currently lives in New York.
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