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.
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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