What I Learned About Startups by Collecting 30,000 Data Points
I spent four years conducting one of the largest data-driven studies on startups, and here’s what it reveals about the difference between billion-dollar startups and startups that raised VC funding but failed to become one.
Some of you may remember a medium article I published two years ago which included dozens of colorful charts that showed data-driven facts about unicorns.
That article went viral with hundreds of thousands of readers. One key feedback I received was that I needed to compare the results from the unicorns with a control group of companies that failed to become a unicorn to put the numbers in context.
So I spent another two years and thousands of hours expanding my data and gathering the same data elements on non-unicorn startups as well.
“This is perhaps one of the most comprehensive and well researched studies by an insightful venture capitalist ever done on startups and investments. I highly recommend it.”―Ilya Strebulaev — Professor, Stanford Graduate School of Business
The results from the study were shocking and revealed many counter-intuitive insights. So I decided to write a book based on the findings. This is probably the first book that was born on medium!
Super Founders: What Data Reveals About Billion-Dollar Startups — By Ali Tamaseb
Ali Tamaseb has spent thousands of hours manually amassing what may be the largest dataset ever collected on startups…
To be better able to give context to the data. I also interviewed founders of 15 billion dollar startups including founders of Zoom, Instacart, GitHub, Cloudflare, PayPal, Kite Pharma, and Flatiron Health, as well as VCs like Peter Thiel, Elad Gil, Alfred Lin (Sequoia Capital), and Keith Rabois (Founders Fund).
The book is now coming out and I wanted to give you a sneak peek of some of the insights you’ll find in there.
There are over 20 myths that the data dispels which I discuss in the book. Here are three examples.
1) “You need to be a technical founder to succeed”
50.5% of founding CEOs of Billion-Dollar Startups were non-technical. Comparing the unicorns group with the random group (a randomly selected group of startups that raised $3m+ in VC funding), the billion-dollar founding CEOs were slightly more likely to be technical, but still, half the founding CEOs of unicorns were non-technical.
Of course, the second-ranking person in the company, who is often the CTO was more likely to be technical.
2) “You need to solve a personal problem and have experience in that industry”
With the exception of healthcare and biotech startups, only 30% of the founders of billion-dollar startups in consumer technologies had previously worked in the same industry, and only 40% of founders of billion-dollar startups in the enterprise/SaaS space had worked in the same industry before. Soft skills such as managing a team, sales, and having a strong network and resources were more important factors. Exceptional founders used their resources to learn more than anyone else about the sector they were going to disrupt by doing research and asking the right questions.
In the book, I interview Nat Turner, co-founder of Flatiron Health about how they were able to go and win into a market they didn’t have a background in.
3) “Competition is bad”
85% of unicorns had competitors from day one. Over 50% of billion-dollar startups were competing with incumbent, large, and old-school companies when they got founded, and those who did were more likely to become billion-dollar companies. 20% were competing in fragmented markets, those which have a dozen or more competitors, but none of which were dominant. However, only a small fraction of billion-dollar companies were competing with another startup that already had received a lot of funding and they seemed to have had less luck in achieving billion-dollar outcomes.
In the book, I interviewed the founder of Zoom, who built and won in a market that had strong competition from incumbents such as Cisco and Microsoft.
The data also confirmed some of the existing beliefs about what makes for a winning startup. Here are three examples:
1) Billion-dollar startups were more likely to save their customers time or money
Not only these two were the most common types of needs addressed by billion-dollar startups, but the companies solving these needs were also more likely to succeed compared with the random group. For example, in the random group, there were more startups going after convenience or entertainment. Examples: UiPath saves their customers time and money or Airbnb that save their customers money.
2) Going after a large market does matter
The companies that ended up becoming billion-dollar companies were more likely to have started in markets that were already large at the time the company was founded. (Defined by the existing demand).
Of course, there are always exceptions to the data, and many types of companies succeed. In the book, I talk about how Coinbase started in a very small market (bitcoin was $5/coin) which was growing exponentially.
3) Painkillers are more likely to succeed (but vitamin pills work too!)
One strategy is to go after well-defined and deeply annoying pain points felt by customers; like Okta did with identity and password management. In these cases, the product aims to take the pain away. Another is to improve on the way something is done, giving customers better value, efficiency, entertainment, or joy, products like Snapchat or TikTok. These products help the customer gain something rather than take away the pain. They are the so-called vitamin pills. Comparing the two groups, the traditional advice about building something people want and building painkillers is true.
However, it's worth noting that 1/3rd of all billion-dollar startups were vitamin pills. The ones that build sticky products that formed habits and created a strong brand and community around their products were indeed also very successful.
In the book, I explore 65 elements per startups (both for billion-dollar group and the random group), including:
- Founder’s backgrounds, career (title, company history, etc.), and education history (degree, universities)
- Previous entrepreneurial endeavors and their outcomes
- Origin of the idea, type of pain, competition when it was founded, defensibility factors
- Fundraising amounts, cadence, and brand of investors
It turns out that many factors that are stereotypically believed to have been linked with success are statistically insignificant but there are also many other factors that do matter.
My hope is that the insights in this book will be not just eye-opening but also useful and practical both for founders and investors and help push the venture capital industry and the startup ecosystem towards less bias.
“Ali Tamaseb offers an extraordinary look at the success and failure of startups coupled with inside stories and interviews with some of the best startup leaders. A must-read.”―Eric Yuan, Founder & CEO, Zoom