Three months ago, we set out on a mission to crack the innovation code of Silicon Valley and share it with the rest of the world. Today we are releasing the first Startup Genome Report which covers in depth research on what makes Silicon Valley startups successful based on profiling over 650 startups.
The first Startup Genome report aims to lay the foundation for a new paradigm of assessing startups and understanding the drivers of entrepreneurial performance.
Many entrepreneurs that we have talked with, especially younger ones, considered describing the repeating patterns of startups an impossible task or even a disgraceful reduction of the artistry of entrepreneurship to numbers and graphs. With this report we do not mean to imply that there is no art to entrepreneurship but rather that entrepreneurship is strongest at the intersection of science and art. By gaining a deeper understanding of the repeating patterns underlying success and failure entrepreneurs can dramatically increase their ability to innovate.
The window of opportunity for this project has only recently been opened. In just the last 2-3 years the number of people extracting and codifying the informal learning of Silicon Valley has hit a point of critical mass. Concurrently the costs of startup creation have fallen dramatically triggering a huge increase in technology entrepreneurship all over the world.
The theories and models that have had the most widespread adoption are effectively applying scientific management principles to startups, with the two most well known theories being Customer Development and the Lean Startup. Yet despite this huge knowledge base emerging about how startups work, startups have been able to absorb little more than the basic patterns of how to build a startup. Most founders don't know what they should be focusing on and consequently dilute their focus or run in the wrong direction. They are regularly bombarded with advice that seems contradictory, which is often paralyzing. And while startups are now gathering way more qualitative and quantitative feedback than they were just a few years ago, their ability to interpret this data and use it to make better business decisions is sorely lacking. The primary cause of these problems is that we lack the necessary structure to assimilate and build upon our accumulated knowledge on the nature of startups.
Here are 14 the insights the foundational structure of the Startup Genome was able to reveal.
You can read the full Startup Genome report and learn more about each finding here:
1. Founders who listen are more successful: Startups that have helpful mentors, track metrics effectively, and learn from startup thought leaders raise 7x more money and have 3.5x better user growth.
2. Startups that pivot once or twice times raise 2.5x more money, have 3.6x better user growth, and are 52% less likely to scale prematurely than startups that pivot more than 2 times or not at all.
3. Many investors invest 2-3x more capital than necessary in startups that haven’t reached problem solution fit yet. They also over-invest in solo founders and founding teams without technical cofounders despite indicators that show that these teams have a much lower probability of success.
4. Investors who provide hands-on help have little or no effect on the company's operational performance. But the right mentors significantly influence a company’s performance and ability to raise money. (However, this does not mean that investors don’t have a significant effect on valuations and M&A)
5. Solo founders take 3.6x longer to reach scale stage compared to a founding team of 2 and they are 2.3x less likely to pivot.
6. Business-heavy founding teams are 6.2x more likely to successfully scale with sales driven startups than with product centric startups.
7. Technical-heavy founding teams are 3.3x more likely to successfully scale with product-centric startups with no network effects than with product-centric startups that have network effects.
8. Balanced teams with one technical founder and one business founder raise 30% more money, have 2.9x more user growth and are 19% less likely to scale prematurely than technical or business-heavy founding teams.
9. Most successful founders are driven by impact rather than experience or money.
10. Founders overestimate the value of IP before product market fit by 255%
11. Startups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely.
12. Startups that haven’t raised money over-estimate their market size by 100x and often misinterpret their market as new.
13. Premature scaling is the most common reason for startups to perform worse. They tend to lose the battle early on by getting ahead of themselves.
14. B2C vs. B2B is not a meaningful segmentation of Internet startups anymore because the Internet has changed the rules of business. We found 4 different major groups of startups that all have very different behavior regarding customer acquisition, time, product, market and team.
(Image source: James Duncan Flickr photos)