What VCs Can Learn from Startup Genome Project

What separates the most successful venture capitalists from the rest of the pack?

According to the Stanford University researchers behind the new Startup Genome Project, the biggest difference between the simply good and the absolutely fabulous lies in how each group assesses startups. After interviewing venture capitalists of all stripes over the last five months, the Genome team — Max Marmer, Ron Berman and Bjoern Lasse Herrmann — found most investors rely on a limited snapshot of a few data points (such as team, traction and market).

But after matching that strategy up with investors’ deal lists and track records, they found that practice often led to nowheresville, especially early on:

While these can be good validators that entrepreneurs are onto something, a snapshot of the team and traction can often be misleading. A great set of resumes can’t tell you how well the team actually works together. And traction was often measured in absolute numbers of users and revenue, but those metrics are second- and third-order effects of progress for an early-stage startup. In the early stages of a startup’s conversion, funnel is a much better indicator of future growth than revenue.

The VCs with the largest track record of hits operated under the principle that startups themselves are actually just the process of searching for product-market fit and a scalable business model.

The result: these investors drew conclusions based on “more subtle” data points like the founding team’s pace of learning, the reason the team made certain pivots or major changes in the business, stage-specific metrics and even the body language between the founders.

Here are four other lessons VCs can learn from the report:

1. Don’t get too pen happy. A big check doesn’t help. According to the Genome Report, the average seed round hovered around $100,000, yet the findings suggest a seed round of just $10,000-50,000 reduces the risk for investors and has no negative impact on startups.

The basic idea is that investors should not place a large bet on most types of startups until they see them find problem-solution fit and produce something that at least solves a piece of the problem. This can help prevent investors from betting on teams that look great on paper but ultimately have no chemistry and fail to execute. The constraint of having less than $50K probably even positively influences first-time entrepreneurs, helping them to not get too far ahead of themselves.

2. Analyze the team based on type. Different types of startups require different kinds of teams to make them work, and investors can get into trouble when they fail to account for these subtleties. Startups were categorized as technology-heavy, business-heavy or balanced. The analysis found business-heavy founding teams are 6.2 times more likely to successfully scale with sales-driven startups than with product-centric startups. However, technical-heavy founding teams are 3.3 times more likely to successfully scale with product-centric startups with no network effects than with product-centric startups that have network effects.

3. Count the founders at the table. According to the data, investors over-invest in solo founders and founding teams without technical cofounders, both of which have a much lower probability of success that other combinations. In fact, solo founders take an average of a whopping nearly 70 months to reach scale while teams with two founders are the fastest at around 20 months.

4. Resist the urge to rush. It’s not too surprising, but actually acquiring customers was one of the most often reported challenges that startups cited in this report. The authors believe many startups fail to get customers at the speed they would like because they either “build too many features or they overcompensate for a non-functional product by creating lots of buzz.” Investors need to watch out for these warning signs.

Image courtesy of Flickr user Rob Lee.