Trends seem to rule everything. Whether it’s the cut of your trousers, how you take your coffee, or what makes up your stock portfolio, crazes, fads, and trends are strong motivating factors behind how all of us behave.
Many venture investors fancy themselves as both trendspotters and trendsetters. But are VCs really that good at getting out ahead of the curve? On an individual basis, probably not when it comes to identifying trends. Certainly not when it comes to individual investors consistently picking (and being able to invest in) the particular companies that take the lion’s share of a market. (If you need some convincing, just read some VCs’ regrets about missed opportunities.)
To answer this question for investors as a group, we examined four recent technical crazes—drones, virtual reality, artificial intelligence, and blockchain—to see how and where startup investing differs from the ups and downs of trendy technologies. Using data from Crunchbase and Google Trends, we’ll chart out this tendency to compare and contrasts venture investors and the general public as trend-spotters.
In many ways, venture investors are literally ahead of the curve. Oftentimes, their interest in new technologies ticks up earlier than the general public.
Entrepreneurs and their investors bandy about a lot of jargon, some more egregious than others. “Hockey stick” growth is one of the more useful terms of art, in that it provides an understandable, visual metaphor. That crook in the elbow, where growth deviates from a linear trajectory and goes polynomial – if not exponential – is the inflection point.
Where and when that inflection point occurs for different populations – in this case, venture investors versus the broader public – points to differences in awareness and risk tolerance. But in the most literal sense, they also indicate which population is generally “ahead of the curve.”
To determine how far ahead of the curve investors really are, we compared the relative trend-spotting abilities of venture investors to the broader (albeit generally tech-savvy) public. Our methods of doing so included plotting the number of Crunchbase-sourced venture deals in a given month against a Google Trends search score for several different technologies. And in an effort to reduce noise from news stories about, say, military drones, we pulled Google Trends data for interest in startups only.
Data was sourced directly from Google Trends and measured on a scale of 100. And since Google Trends data is built off of simple keyword searches, we did the same to derive venture deal volume. We found companies in Crunchbase’s dataset that mention a specific keyword or phrase (like “artificial intelligence”) and then pulled the investment rounds raised by each of those companies. And to match deal volume to Google Trends data, we then adjusted venture deal volume to be on a scale of 100 as well.
By directly measuring responsiveness to keywords, we’ve been able to produce a reasonably fair comparison of how quickly venture investors and the general population pick up on the tech trends.
Below, you’ll see when investors (as measured by deal volume, in blue) and the broader public (by way of Google Trends data, in deep yellow) begin to pick up on the artificial intelligence trend.
And below you’ll see how investors and the broader public became aware of blockchain as both a startup buzzword and technical trend.
In both cases, venture investors have seemingly gotten out ahead of these trends. Both AI and blockchain provide interesting cases of technologies that are at their peak of public awareness and excitement.
With trends of all sorts, we can see these inflection points, too. And where these inflection points fall often echoes a theoretical model developed in the early 1960s by a communications researcher named Everett Rogers. His model for the “diffusion of innovations” suggests that broader awareness and adoption of new technologies is driven by word-of-mouth, starting with a core group of innovators and early adopters. In the case of AI startups, venture investors have been keenly interested since mid-2012, whereas AI startups didn’t capture the broader public’s search interest until mid-2015. In the case of blockchain technology, venture investors have been actively interested since late 2013, but it took almost two years for blockchain startups to gain search interest in the general public.
VC Interest Peaks Earlier
If venture investors are generally good at identifying and hopping on tech trends before the general population, this might suggest a tendency for their interest to peak before the general population as well. And, as it turns out, that’s generally what we’ve found here in the case of two technology trends that have seemingly waxed and waned.
In the chart below, you will see when investor and general interest in drone startups has peaked. Interest from VCs (blue line) peaks ahead of the yellow curve (consumer interest).
And here we show the rise and fall of virtual reality startups as a trend.
Just like how venture investors are quicker to get onboard a new technology trend, they also seem to begin sliding off the trend sooner than the general population. We see this in both the case of drones and VR startups, where peak investment activity occurs many months before Google Trend scores for “drone startup” and “VR startup” reach their respective zeniths.
Given all of the above, it’s fair to say – with some due caution – that, in at least some cases, venture investment in companies applying a given technology is a leading indicator of future interest by the public at large.
Following The Herd
Entrepreneurs and investors alike are no less resistant to the siren song of the trendy. If entrepreneurs are tasked with “building something people want,” and what people want is driven by trends, nobody should be surprised when they start companies using trendy tech.
From an investor’s perspective, getting out in front of market trends around a particular technology is imperative. Many venture investors tout their foresight and claim to invest in the future of technology itself, but the time horizons of most venture investors (10 years, per fund, on average) is fairly limited. So venture investment strategies have become a kind of meta-game around anticipating the short-run future market demand for a particular technology and finding the companies that fit the thesis. But that’s very hard to do well once—let alone consistently. Why take on the risk of being an innovator when being an early adopter is good enough?