As a venture capital investor, I review, assess, and track hundreds of startups every year and have seen some of these companies, including some of my investments, grow to billion-dollar outcomes. But, I still could not tell what was really different between those which did become great successes and those that did not, and neither could anyone else, at least not backed by real holistic data on all startups that succeeded or failed, instead of relying on just a few examples each investor has personally seen.
I spent thousands of hours over the past four years manually piecing together 30,000 data points and analyzing over 65 factors per startup. I gathered information on everything from a company’s early competitors to its defensibility factors; from the founder’s age to his or her university rank; from the quality of a company’s investors to the timing of fundraising rounds — and much, much more. No study is meaningful without comparison to a baseline group, so I also collected the same data on a similar-sized group of randomly selected start-ups founded in the same time period that didn’t go on to billion-dollar valuations. This is one of the largest and most comprehensive studies ever conducted on startups and investments, and why some succeed and others do not.
In my new book, “Super Founders: What Data Reveals about Billion-Dollar Startups”, I discuss what I found in the data and interview founders of billion-dollar companies, such as Zoom, Instacart, GitHub, Cloudflare, Confluent, and Nest, as well as investors in companies like LinkedIn, Stripe, DoorDash, and Airbnb to go deeper into their success.
In this article, I will walk you through some of the findings from the data that would help you become a more successful angel investor and discuss some common reasons angel investors pass on an opportunity for the wrong reasons.
Only a small fraction of startups founded each year end up achieving billion dollar outcomes. Most angel investors are lucky if one or a couple of their investments reach billion dollar or more outcomes. If, as an angel investor, you had a chance to know about one of those companies that would go on to become a billion dollar outcome in the early stage, could have had access to make an investment, and passed on the opportunity for the wrong reasons, you have made a costly mistake. Afterall, the returns of any angel or venture capital portfolio relies solely on the top one or two companies in the portfolio. To become a better angel investor you need to minimize the anti-portfolio, the companies you passed on that ended up becoming massive successes. Dozens of angel investors said “No” to Airbnb when it was raising $150,000 for 10% of the company, valuing it at $1.5 million. That is not a single occurrence. The same thing is true for companies like Uber, Instacart, Peloton, and many others. In most of these cases, the investors said “No” for the wrong reasons.
The following are 8 reasons why angel investors will pass on an opportunity that the data shows are not important:
- “You are a solo-founder, first go find a co-founder” My data showed that solo founders are not less likely to build unicorns. One out of five billion dollar startups was founded by a solo founder. That is less common than dual co-founder startups (38%). However, comparing the distribution of the number of co-founders between those that became successful and those that had raised adequate funding but failed, showed no advantage or disadvantage to any number of co-founders, including being a solo-founder or having four or five founders.
- “I don’t invest in non-technical founders” Many angel investors reject startups based on the fact that the CEO is not technical. While being technical helps founders be able to prototype their ideas faster and technical founders were slightly more likely to achieve success, it is notable to mention that 50.5% of billion-dollar startups founded in the past 14 years had a non-technical founding CEO. It is important to note that my study includes billion-dollar startups in all categories, not just in tech, but the trends are still the same. As an example, the co-founder and CEO of Canva, Melanie Perkins, was non-technical, yet she built a decacorn in the design software space. In many cases, even the first two people in a company were non-technical.
- “You don’t know anything about this industry” Many investors would like the founders to have come from the industry and to have domain expertise. Very counterintuitive, but the data showed that within consumer tech billion-dollar startups only 30% had experience in the same industry and in enterprise/SaaS billion dollar startups only 40% were coming from that industry. This is not to say these founders did not have any work experience. The founders of billion-dollar startups had on average 11 years of work experience before starting their unicorn, but in many cases they were successful in jumping from one industry to another. Outsiders could do well in these industries because they look at the market differently and are not chained down with current orthodoxies, thus allowing them to solve problems in unique ways. Healthcare, biotech, and hard sciences are generally exceptions in which 80% of the founders did come from the industry. In the book, I interview Nat Turner, co-founder of Flatiron Health, which was acquired by Roche for $2 billion. Nat and his co-founder, Zach, were outliers to the data as they had both come from the Ad-Tech space to the cancer and medical data space.
- “This is a crowded space” Many investors get spooked by competition. The key thing that scares investors is “What if Google [or replace it for any big tech company] also does this”. Turns out 55% of billion-dollar startups were already competing with the large incumbent companies of their time at the time of founding. Only 20% of unicorns did not have any competition. However, the worst case of competition is when a startup was copying and competing with another highly funded startup already a few months or a year ahead of them. If there is another startup building a similar product and they are already highly funded, then those investments are less likely to succeed.
- “This idea has been tried before and failed” The data showed that less than 30% of all billion-dollar startups were the first company to try the idea, yet were first to market. Another 30% were between 2nd and 5th, and 40% were the 6th times or later that an idea was being tried. In the book, I interview the co-founder of Instacart, who tells me investors were passing because they said Instacart was like Webvan (a similar idea that died in the dot com bust). I also interviewed Tony Fadell of Nest, and co-inventor of the iPhone, which talks about General Magic, a silicon valley startup in the 90s that was the first to build something like the iPhone, but failed; yet, the same product reached massive success later on when other companies and Apple introduced smartphones years later. Sometimes it takes time for the market to catch up, the best products are not first or last, but those that are closest to an inflection point in the market.
- “It doesn’t have founder-market fit” Many investors pass on companies when the founders haven’t personally experienced the problem they are solving. Many investors are looking for founders who have “ulterior motive” to create a company. However, the majority of billion dollar company founders were not solving a personal problem and were not their own customers. Many of them were opportunistic. They saw a trend, found a good idea, and pursued that to success. They used their resources and soft skills to learn more than anyone else about the space they were about to disrupt.
- “Only looking into companies graduating from accelerators” If you had only looked into accelerator programs, you would have missed on 85% of unicorns founded in the past fifteen years. That is not to knock the value of these programs. The attention, resources, and networks provided by accelerators and incubators can certainly give startups a leg up. Compared with the random group, companies that had gone through Y Combinator, for example, were indeed more likely to achieve billion-dollar valuations. The point, however, is that going through such programs should not be the big end goal, and that most billion-dollar companies did not.
- “The founders are family members, I don’t like the dynamics of that” We tend to knock family businesses, but this is how the world operated for most of human history. There are many examples of family members as co-founders of companies that ended up becoming massive successes – husband and wife, fiances, brothers, and father and son co-founded companies have all succeeded at becoming billion dollar companies. They are a small percentage of all the companies that get founded, and they are a small percentage of all the companies that become billion dollar outcomes, but it does not mean that they are less likely to succeed. Stripe, Tanium, VMWave, Houzz, and Eventbrite are just a few examples here.
Of course, it is also very important to look for and find factors that make one more likely to build a successful startup. There are many such factors that the data revealed that angel investors could look for in their next investment. I discuss those in detail in the book and provide actionable insights for investors and entrepreneurs based on the data.
Takeaway
Forget the myths. There are many stereotypes about what does and what does not lead to success that are statistically wrong. Data is a great tool both to avoid missing on great investments for the wrong reasons, as well as creating a metrics-driven investment framework that could help investors compare investment opportunities and pick the right one. My recommendation for angel investors is to look at their portfolio of angel investments as a portfolio of people rather than a portfolio of companies. Some founders may fail the first time around but come back much stronger the next time. Invest in the founders you like in their back to back endeavours until they land on the billion-dollar one.
