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Here's where you're most likely to randomly run into a unicorn in the US

Here's where you're most likely to randomly run into a unicorn in the US
From TechCrunch - July 5, 2017

Wheres the best place to start a startup? Its a perennial and somewhat intractable question entrepreneurs love to ask. And before you get your hopes up, well start by saying there is no one right answer to this question. Like much in the world of startups and venture capital, it depends on a number of factors. But what we can tell is that networks matter.

Networking through the city

In network theory, theres a concept called homophily, the tendency for similar individuals to connect with one another more frequently than two or more dissimilar individuals. The phrase birds of a feather flock together is a common, simple explanation of what the term means. So, if an entrepreneur wants their fledgling startup to join the unicorn club the small but growing number of private companies that reach a $1 billion private valuationprior to a sale, IPO or untimely demiseor just wants to get on a firm financial footing, where is that most likely to happen?

Here, well provide an answer to that question with a bit of a twist.

Finding the metropolitan regions that give rise to the most startups, where most of the unicorns are located or where most of the companies with, say, $50 million or more in funding are located, is a bit too easy and it doesnt yield particularly interesting results. (Spoiler alert: the SF Bay Area ranks at the top of the list for all three.)

Rather, were going to find the American metropolitan regions with the highestrateof producing unicorns and well-capitalized startups. In other words, were going to take the number of unicorns and well-capitalized companies in a given region and divide it by the number of companies founded in the region.

Finding the best place to start a startup

Were basing our analysis on a data set, extracted from Crunchbase, containing nearly 33,500 companies from around the U.S. that were founded in or after 2003, the beginning of the Unicorn Era, according toAileen Lees original definition.

This data set excludes companies that are said to have raised rounds of financing before their founding dates (an occasional error in the data that introduces more noise). Because the focus of our analysisaremore typical software-driven product and services companies, the data set also excludes a number of capital-intensive business categories like energy, petrochemical processing and extraction, pharmaceuticals, medical devices and other life sciences companies.

We then aggregated the data to find the number of companies founded in each metropolitan region since 2003 which meet our criteria. Of course, there are going to be some companies that have been left out, due to missing data about locations or founding years. But were looking at a sufficiently large number of companies to narrow the margin of error caused by those omissions to the point of insignificance.

Finding where the unicorns are

We sourced our unicorn data from the Crunchbase Unicorn Leaderboard, focusing exclusively on those $1 billion or more companies that arecurrently operating and privately heldand those that havegone public or have been acquired. We counted a total of 144 current and exited unicorns in the U.S., andhere are the top five metropolitan regions where theyre located:

No surprises here. However, when you divide the number of unicorns based in each metropolitan region by the number of companies founded in that region since 2003, were able to find the regions with the highest prevalence of unicorns in their startup populations.

This way of answering the where are all the unicorns? question produces some interesting and unexpected results, which highlight smaller startup ecosystems.

Finding mature and well-capitalized startup ecosystems

Conclusion

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