Unicorn (finance)

Based on Wikipedia: Unicorn (finance)

The Billion-Dollar Myth That Became Reality

In 2013, venture capitalist Aileen Lee sat down to write an article for TechCrunch and inadvertently created a new vocabulary for Silicon Valley. She needed a word to describe something genuinely rare: private companies worth more than one billion dollars. She chose "unicorn," the mythical horse with a single spiraling horn, a creature that exists only in legends and fairy tales.

At the time, she counted thirty-nine of them.

Today, there are over twelve hundred. The mythical beast, it turns out, has been breeding.

What Makes a Unicorn a Unicorn

The definition is deceptively simple. A unicorn is a privately held startup company—meaning it hasn't sold shares to the public on a stock exchange—that investors have valued at one billion dollars or more. That's the entire qualification. No revenue requirements. No profitability tests. No minimum age or number of employees.

The key word here is "valuation," which deserves some unpacking because it's fundamentally different from what you might think of as a company's worth.

When a publicly traded company like Apple or Toyota reports its market value, that number comes from multiplying the share price (set by millions of daily trades on stock exchanges) by the total number of shares. It's a real-time snapshot of what actual buyers are willing to pay for actual ownership.

Unicorn valuations work differently. They emerge from private funding rounds, where a venture capital firm might invest, say, fifty million dollars for a five percent stake in the company. Simple arithmetic: if five percent costs fifty million, then one hundred percent must be worth one billion. Congratulations, you've just minted a unicorn.

The difference matters enormously. Public market valuations face constant scrutiny from countless traders with skin in the game. Private valuations are negotiated deals between founders who want the highest possible number and investors who, paradoxically, often want the same thing—because it makes their previous investments look more valuable on paper.

The Taxonomy of Mythical Creatures

Once you accept that billion-dollar startups are common enough to need their own category, you inevitably need subcategories. The jargon has proliferated accordingly.

A "decacorn" is a unicorn worth more than ten billion dollars. Companies like SpaceX, Stripe, and ByteDance (the Chinese company that owns TikTok) have worn this label. The term follows Greek numerical prefixes—deca meaning ten.

A "hectocorn" or "centicorn" describes the rarest specimens: private companies valued above one hundred billion dollars. These barely exist, which is rather the point of the increasingly elaborate naming conventions.

Going in the other direction, a "soonicorn" is a startup that appears to be approaching the billion-dollar threshold. A "minicorn" has crossed one million dollars in valuation, which sounds less impressive until you remember that most new businesses fail completely.

And then there's the "camel," which represents an entirely different philosophy. Where unicorns are built for explosive growth fueled by external capital, camels are designed to survive harsh conditions with minimal resources—companies that prioritize sustainability over speed, profits over promises of future profits.

Blitzscaling: The Strategy That Built the Herd

To understand why unicorns multiplied so dramatically, you need to understand a strategy that dominated startup thinking throughout the 2010s. It goes by various names: "get big fast," "first-mover advantage," or, in the term popularized by LinkedIn founder Reid Hoffman, "blitzscaling."

The logic runs like this. In digital markets, the winner often takes all or nearly all. Think about how we say "I'll Google that," not "I'll search-engine that." Consider how Facebook swallowed social networking, how Amazon devoured online retail, how Uber and Lyft conquered ride-hailing in country after country. In these winner-take-most markets, being second might be worse than being nowhere at all.

If that's true, then speed matters more than efficiency. Spend massively on customer acquisition. Price your product below cost to attract users. Burn through capital to grab market share before competitors can establish themselves. Worry about profits later, once you've built an unassailable position.

This strategy requires enormous amounts of capital. Traditional banks won't lend money to companies that are deliberately losing it. So founders turn to venture capital—investors willing to accept extreme risk in exchange for the possibility of extreme returns.

The math that makes venture capital work is counterintuitive. A typical venture fund expects most of its investments to fail completely. Maybe one or two out of ten will produce modest returns. The entire model depends on finding that rare company—the unicorn, you might say—that returns fifty or one hundred times the original investment. Those massive wins must compensate for all the zeros.

This creates a peculiar dynamic. Venture capitalists aren't looking for good businesses in the traditional sense. They're looking for potential grand slams. A company that might grow steadily and return three times their investment is actually unattractive because it takes up a slot that could have held a moonshot.

Why Stay Private? The Changing Economics of Going Public

Traditionally, the lifecycle of a successful startup went something like this. You founded a company. You raised money from venture capitalists. You grew. And then, fairly quickly, you went public—selling shares on the stock market to raise capital and give your early investors a way to cash out.

In 1999, the average technology company went public about four years after its founding. By the mid-2010s, that timeline had stretched to eleven years. Companies were staying private far longer, and unicorns were a direct result.

Several forces drove this shift.

First, more private capital became available. As venture capital matured as an asset class, pension funds, endowments, and sovereign wealth funds poured money into it. Startups could raise hundreds of millions of dollars without ever approaching the public markets.

Second, going public became more burdensome. After high-profile frauds at Enron and WorldCom, the United States Congress passed the Sarbanes-Oxley Act in 2002, imposing extensive new requirements on public companies. Financial reporting became more complex and expensive. Chief executives became personally liable for accounting accuracy in ways they hadn't been before. For a fast-moving startup more focused on growth than governance, public company status looked less appealing.

Third, a 2012 law called the Jumpstart Our Business Startups Act (the acronym spells JOBS, which was intentional and slightly groan-worthy) quadrupled the number of shareholders a company could have before triggering public reporting requirements. Companies that might once have been forced to go public simply because their employee count grew could now remain private indefinitely.

And fourth, the public markets sometimes disagreed with private valuations. Square, the payments company founded by Twitter creator Jack Dorsey, was valued at six billion dollars in private markets before its 2015 initial public offering. Public investors thought that was too high and priced the stock at a significant discount. Trivago, the German hotel search engine, experienced similar disappointment.

When your last private funding round valued the company at a certain level, going public at a lower valuation means acknowledging that the previous valuation was inflated. Nobody involved in those previous rounds wants that. Better to raise another private round, at an even higher valuation, and postpone the reckoning.

The Sharing Economy's Role

Three of the largest unicorns of the 2010s shared a common business model: Uber connected passengers with drivers; Airbnb connected travelers with hosts; DiDi (sometimes called the Uber of China) did for Chinese cities what Uber did for American ones.

None of them owned the primary assets that generated their revenue. Uber owned no cars. Airbnb owned no properties. They were platforms, marketplaces, connectors—what business academics call "network orchestrators."

The sharing economy emerged from the 2008 financial crisis, when suddenly frugality was fashionable and everyone with a spare bedroom or an underused vehicle was looking for ways to monetize their existing possessions. But it scaled to unicorn dimensions because of smartphone penetration. When everyone has a GPS-enabled computer in their pocket, coordinating transactions between strangers becomes trivially easy.

These network businesses have unusual economics. Traditional companies face diminishing returns: the tenth factory costs roughly the same as the ninth but serves progressively less attractive markets. Network businesses often experience increasing returns: the more drivers on Uber's platform, the more attractive it becomes to riders, which attracts more drivers, which attracts more riders, in a virtuous spiral economists call network effects.

Network effects tend to produce winner-take-most markets, which explains why investors were willing to fund billions in losses at Uber and Lyft as each fought for dominance. The prize for winning would be enormous. The penalty for coming second might be oblivion.

E-Commerce Eats the Mall

Another category of unicorns rode a different wave: the shift from physical retail to online shopping. Amazon, now a trillion-dollar public company, was once a unicorn. So was Alibaba, its Chinese counterpart. So were dozens of smaller players attempting to digitize various niches of commerce.

The numbers tell the story starkly. In 2005, American malls generated nearly ninety billion dollars in sales. By 2015, that figure had dropped to about sixty billion. The decline has only accelerated since, especially after the COVID-19 pandemic forced consumers to discover they could live without trips to the shopping center.

Traditional retailers noticed. In 2016, Walmart paid three point three billion dollars for Jet.com, an e-commerce startup that was barely two years old. The retailer from Bentonville, Arkansas, was essentially paying for the expertise and technology it needed to compete with Amazon.

This points to another path to unicorn status: acquisition. Many startups achieved billion-dollar valuations not through funding rounds but by being purchased for that amount. When Facebook bought Instagram in 2012 for one billion dollars, Instagram became a unicorn in the moment of its acquisition. When Unilever bought Dollar Shave Club for the same price, the razor subscription startup got the same retroactive mythical status.

Large technology companies have particular reasons to prefer acquisitions over internal development. Apple, Google, Meta, and Amazon all sit on enormous cash reserves. In a low-interest-rate environment, that cash earns almost nothing. And in mature technology markets, it can be faster and easier to buy innovation than to build it. Why spend five years developing a new technology when you can buy a startup that's already solved the problem?

The Skeptics and the Bubble Question

Not everyone found the proliferation of unicorns encouraging. Bill Gurley, a legendary venture capitalist at the firm Benchmark, warned as early as 2015 that valuations had become "speculative and unsustainable." He predicted the emergence of "dead unicorns"—companies whose billion-dollar valuations would prove illusory.

William Danoff, who managed Fidelity's enormous Contrafund, suggested that unicorns would "lose a bit of luster" as they became more common. After all, something can only be rare if it's actually rare.

Academic research supported the skepticism. A 2018 study by Stanford professors calculated that unicorns were overvalued by an average of forty-eight percent. Half of all unicorns, in other words, probably weren't worth a billion dollars at all.

The concerns centered on the nature of private valuations. When a venture capital firm invests at a billion-dollar valuation, they typically negotiate special terms: liquidation preferences that ensure they get paid first if the company is sold, anti-dilution provisions that protect them from future down rounds, participation rights that give them a share of any upside.

These terms make the investment worth more than simple equity. A share that's first in line for repayment is worth more than a share that isn't. But the headline valuation ignores these distinctions, treating all shares as equivalent. Strip away the special terms, and many unicorn valuations deflate substantially.

The 2022 Reckoning

In 2021, unicorn creation reached a frenzy. Three hundred and forty new companies crossed the billion-dollar threshold. Investors poured seventy-one billion dollars into newly minted unicorns. The total count exceeded all unicorns created in the previous five years combined.

Then the music stopped.

Several factors converged. The COVID-19 pandemic's economic disruptions caught up with overextended companies. Central banks, fighting inflation, raised interest rates from near zero to the highest levels in decades. Suddenly, the cheap money that had fueled blitzscaling became expensive. Regulators grew more skeptical of big technology companies. And some heavily hyped startups simply failed to perform.

Unicorn valuations fell. Companies that had been worth ten billion found themselves worth three. Some discovered that no one would fund them at any valuation. The dead unicorns that Bill Gurley had predicted began appearing, though the tech industry prefers euphemisms like "down round" or "valuation adjustment" to anything as morbid as death.

By May 2024, CB Insights counted 1,248 unicorns worldwide. That's still a lot of mythical creatures—more than existed when Aileen Lee coined the term—but the growth rate had slowed dramatically. The era of unicorn abundance had given way to something more like normal.

How to Value a Dream

Understanding unicorn valuations requires understanding how venture capitalists think about value, which differs substantially from traditional corporate finance.

A mature company can be valued by examining its cash flows. You forecast how much money the business will generate over the coming years, then discount those future payments back to present value. This is called discounted cash flow analysis, and it's the foundation of conventional valuation.

Unicorns rarely have cash flows to discount. Many lose money deliberately, following the blitzscaling playbook. Their value lies not in what they earn today but in what they might earn tomorrow—or in ten years, or never.

So investors use proxies. They look at the total size of the market the startup is addressing. They examine growth rates. They compare the company to others that have already gone public or been acquired. They study the founding team, the technology, the competitive dynamics.

They also consider game theory. A venture capitalist deciding whether to invest at a billion-dollar valuation isn't just asking whether the company is worth a billion dollars. They're asking whether someone else will pay more later. If the next funding round will value the company at two billion, then paying one billion today might be a bargain—regardless of whether any objective measure supports either number.

This creates a peculiar dynamic where valuations can become somewhat detached from any underlying reality. As long as someone will pay more tomorrow, today's price is justified. The moment that chain of escalating expectations breaks, the whole edifice can collapse.

The Geographic Distribution of Magic

Unicorns are not evenly distributed across the globe. The United States, particularly Silicon Valley, has produced the most, but other hubs have emerged.

China became the second-largest unicorn producer, home to ByteDance, the most valuable private company in the world for much of the 2020s. India developed its own startup ecosystem, with companies like Flipkart (in e-commerce) and Paytm (in payments) achieving unicorn status. Israel, with its population of just nine million, produced unicorns at a rate far exceeding its demographic weight, driven by a strong technology sector and mandatory military service that produces a generation of young adults trained in cybersecurity and communications technology.

Europe lagged, which became a source of policy concern. The European Commission explicitly adopted the goal of enabling more unicorns, though critics questioned whether this was the right metric for economic success. A policy focused on unicorns might inadvertently favor high-risk, high-growth ventures over the steady medium-sized businesses that provide stable employment and consistent tax revenue.

The geographic concentration reflects something important about startup ecosystems. Unicorns tend to emerge where venture capital is abundant, where technical talent clusters, where failure is culturally tolerated, and where previous success stories create networks of experienced entrepreneurs and investors who recycle into new ventures. These conditions don't exist everywhere, and they're difficult to create through policy.

What Unicorns Mean—and Don't Mean

The proliferation of unicorns tells us something about the nature of technology in the twenty-first century. Digital businesses can scale in ways that manufacturing businesses cannot. A successful social network or marketplace or software tool can expand to serve millions of users with relatively modest additional investment. This creates the possibility of enormous value creation—and the temptation to see enormous value where it may not exist.

But unicorn status itself tells us less than you might think. A billion-dollar valuation doesn't mean a company is profitable, or sustainable, or socially valuable. Many unicorns have destroyed capital rather than created it. Some have caused harm to workers, consumers, or communities. A few have been outright frauds—Theranos, the blood-testing company valued at nine billion dollars, turned out to be founded on lies.

The term has also become somewhat elastic. Private equity firms sometimes buy divisions of public companies and claim them as new unicorns. Real estate projects and cryptocurrency ventures have adopted the label. What started as a specific description of rare software startups has become a general marker of aspiration.

Perhaps this is inevitable. Once venture capitalists made unicorn status a goal rather than a description, founders began optimizing for it. Companies that might have been content with steady growth at a modest valuation instead pursued strategies designed to maximize headline numbers, regardless of whether those strategies made business sense.

The mythical creature, having escaped from fairy tales into business journalism, has shaped the world it was meant merely to describe.