The Logic of Crazy Valuations
August is the traditional vacation month for venture capitalists, who stream out of their Sand Hill Road offices to quieter points, ostensibly to reflect on the year so far and prepare for the heavy fall fundraising season.
And what a year it has been! We now have several companies valued at around $10 billion and above, including Airbnb, Dropbox, and Uber. Those valuations seem tame compared to the wild fundraises raised by a myriad of startups over the past few months. Medium raised $25 million in its series A in January while Secret secured $25 million a few weeks ago — just nine months after its launch.
Such largess isn’t exclusive to just consumer companies. Slack, for example, raised $53.5 million in April across two connected rounds just eight months after launching its collaboration software service (the company has existed for longer, having pivoted from an earlier game product).
In hindsight, the investment decisions of the 1990s that propelled Amazon, eBay, and Google to stardom now seem almost quaint.
Such investments have fueled Silicon Valley’s favorite parlor game, namely predicting the next collapse of the economy. After almost 15 years, many of the key statistics of the region have risen to peak dot-com levels, including the number of investments and venture capital going into high-tech startups. Those numbers are even more incongruous given the declining rate of entrepreneurship in the economy that was reported on this week.
Venture capitalists, like all investors, can certainly succumb to herd mentalities and groupthink. But they also face the same set of incentives in the marketplace, and it is there that we will understand more about the dynamics of high prices and what it means for startups today.
Faster and Faster Product Adoption
Perhaps the most important social change for startups is that the speed of adoption of technology products has greatly accelerated. Just a few years after their launches, messaging apps like WhatsApp, Snapchat, and Line are already on hundreds of millions of phones. And thanks to the changes underway in hardware development, that compression of the adoption cycle applies equally to hardware. Tablets like Apple’s iPad, which was first introduced in 2010, are now quickly becoming a saturated market.
Our ability as consumers to learn about new products and services has never been better, thanks to dense and deep social networks. And once we have found out about something we want to download or purchase, we can do so in seconds. You might even call it the new elevator pitch: in 30 seconds, a founder can describe an app as well as have a potential user download and try it.
That speed of virality means startups can quite literally be overnight successes. A company like Secret, which was founded in October 2013, can reach millions of users in just a few weeks. This compressed growth directly impacts startup valuations, which no longer rise at a fairly continuous rate, but instead face discontinuous moments where the price jumps due to the company’s public success.
The Rise of Data-Sophisticated VCs
This acceleration of startup growth is complemented by the increasingly sophisticated use of data in venture capital decision-making. Firms such as Sequoia, Andreessen Horowitz, and Google Ventures employ entire teams to analyze data like app rankings and social network sentiment to determine the next breakout success.
The concern we should have is much further down the road when these companies eventually need to exit to provide their investors with returns.
Now, firms like Bloomberg Beta are starting even earlier and trying to identify founders before they even know they want to start a company. In fact, that faith in computers to identify great opportunities has come so far along that Deep Knowledge Ventures has even named an algorithm to its board of directors.
In hindsight, the investment decisions of the 1990s that propelled Amazon, eBay, and Google to stardom now seem almost quaint. No longer are a handful of people listening to a slide presentation and then lobbing a few million dollars at a team. Through comprehensive data streams and better analysis, VCs are now reaching a point of total situational awareness, in which they have almost as much data about a startup as the startup does itself.
The Challenges of Speed and Competition
For investors, the combination of rapid adoption cycles and better information flow greatly narrows the window of opportunity for investing in a company. Since startups can achieve extremely rapid growth in a short period, an investor has to invest before that moment or risk seeing a massive spike in valuation as every VC witnesses the same data.
The challenge is that VCs (and humans more generally) are quite poor at making fast decisions in times of uncertainty. We are hard-wired to delay our decision-making if we believe there is an opportunity to wait and receive more information. That thought pattern was valuable for surviving in nature, and was not much of a liability in the equally carnivorous venture industry. Now with greater competition from an infusion of capital, VCs have to make such weighty decisions under incredible pressure.
Mark Suster and others have commented at length about the changing structure going on right now in the venture industry. In my analysis, there is a bifurcation underway between those firms that invest in the pre-traction phase, and those that invest in the post-traction phase of a startup’s life. Those that invest early build broad portfolios and develop methods to identify founders, while those who invest later use data to quickly identify rising stars and are willing to be relatively price insensitive.
This dynamic explains how a startup like Secret can raise a $1.4 million seed round in December, an $8.6 million Series A in March, and a $25 million Series B just four months later in July. Essentially, any startup is going to have a handful of pre-traction investors to get a product out to market. If the company finds a formula for growth, a handful of post-traction investors will join shortly thereafter. If growth continues, late-stage investors including hedge funds and investment banks will join to get the company to whatever exit it is seeking.
While there has been an intense discussion about a possible bubble, these market incentives seem to explain most of what we are witnessing. By using a variety of data sources and algorithms, early-stage venture capitalists are moving faster to identify winners before others find them first. For post-traction investors, there is intense competition to get into the best deals, which quickly pushes valuations north.
The concern we should have is much further down the road when these companies eventually need to exit to provide their investors with returns. Making venture-scale returns at a price of $250 million or higher is incredibly difficult. While the number of billion-dollar-valued startups has reached an historical high-point, it is difficult to see how valuations will grow as quickly in the next few years as they have in the last five. Everyone in the developed world is now on the internet, nearly everyone who wants a smartphone has one, and the same can almost be said for tablets. The raw user growth that fueled valuations isn’t going to happen again.
Thus, any exuberance that is emanating from the dark corners of Sand Hill Road won’t be realized in some cataclysmic crash like we saw in 2000, but rather in the continual red ink that will flush across portfolio pages as exits fail to meet expectations. Ultimately, VCs are professional investors, and it is their job to ensure that the valuations they pay are risk-adjusted and rational. If they fail, their August vacations may just become a tad bit more permanent.