In the 1980s, venture capitalists relied heavily on intuition – and got away with it. The market permitted only a finite variety of tech businesses. VC’s could act on instinct because they were well informed oN the possibilities. It didn’t take a rocket scientist to figure out that every PC needed a disk drive, operating system, and a handful of chips.
Today, the technology market is much more open-ended and the nature of product development has evolved. Eric Reis introduced the lean method, urging founders to make something based on customer demand, then iterate repeatedly until it achieves product-market fit. Data – not intuition – determines whether you’re iterating effectively.
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The lean methodology was quickly embraced by VC’s as well. Intuition remains vital, but over-reliance on it can lead to overlooking opportunities that a more quantitative approach would highlight.
When investors ignore the data, chances are their judgement will be hijacked by hype, FOMO (fear-of-missing-out), and the “bright, shiny object” syndrome. Some investors choose startups the way 5-year-olds pick breakfast cereals. The coolest toys and best commercials win out, nutritional content and the cereal’s place in the ‘balanced breakfast’ equation are hardly considered.
To find hidden gems, investors need a healthy balance between intuition and data. We should aim to be at least as quantitative as the startups we evaluate. To accomplish that, my partners and I at Bullpen Capital use three tests in our decision making process.
No, I’m not worried about other VCs ‘stealing’ them. A fellow investor once told me, “That’s not what real VCs do.”
Take them or leave them. These tests can help you distinguish the gems from the junk.
Has product-market fit been achieved?
From B2B SaaS, to marketplaces, to consumer apps, measuring product-market fit gets increasingly complex. The key is to avoid false positives that burn FOMO-zombie investors.
With SaaS, product-market fit depends on monthly recurring revenue (MRR), cost of customer acquisition, churn rates, and lifetime customer value. Quantitative seed investors target companies with $25K – $50K MRR.
Series A investors look for $150K and $200K MRR. I hunt around 100K MRR, in the “post-seed” gap. I benchmark those other metrics against companies in the same weight class.
Marketplaces are trickier because they often have a consumer and SaaS component. Sourceeasy, a marketplace for fast fashion, is a good example. They provide a platform for managing apparel-in-process that helps brands manage their designs across multiple factories. Seed investors aim for $100K gross marketplace value, Series A VCs look for $500K to $1M, and I look in the space between.
Consumer products are the hardest to evaluate. Five years ago, VCs looked at downloads. Seed investors wanted 1M downloads, and Series A wanted 10M. Today, I care more about engagement. What do daily, weekly, and monthly active user stats look like? How does the newest cohort of users compare to those who downloaded the app a year ago? Engagement improves over time in apps that have a future.
Meerkat is the exemplar of a false positive. It was the unmissable deal in spring 2015 – now it’s in hospice. The metrics didn’t lie. Don’t even get me started on Yo or Secret.
Is there an inflection point on the horizon?
Put differently, will the company be ready for a Supersize A round ($10 to $15M) within a year? Currently, most A-round investors ignore anything smaller because they’re skittish from the SaaS market’s bubblier days. If a post-seed company can’t hit this inflection point in 9 to 12 months, it’s growing too slow.
So how do you know if a startup can meet that timeline? Look at the customer acquisition cost and strategy, which place hard limits on growth. Is the acquisition model repeatable? Could it be better?
By crunching that data alongside the retention rate of new user cohorts, you can estimate where a company will be in 9 to 12 months. It’s okay if there are kinks left to work out.
This was the case with Verbling, a marketplace for language lessons over video chat. The company had product-market fit, but it’s paid acquisition strategy was inefficient. To get them on a Supersize A track, my partners and I have set them on a path to target enterprise customers.
Before investing, I have to know that I can help fix the company’s problems. If it would take a miracle to solve the equation, no thanks.
Does the CEO have the chops to make it?
In this test, intuition is priceless. VCs used to bet on experienced entrepreneurs with glitzy track records. At Bullpen, we’ve figured out half or more of successful companies have first-time CEOs. Whacky 25 year olds with horsepower are ideal.
“Chops” are subjective, but I still use specific markers. First, if the CEO claims to have product-market fit, look at how the company spends money. If half or more of the budget is spent on product, I call bullshit.
Second, how well does the CEO understand the customers and market? The CEO needs to know the market scary-well because more likely than not, he or she has to pioneer demand for something people don’t know they need (yet).
When Bullpen was looking at HomeLight, a system for finding real estate agents, their CEO Drew Uher knew his business stone cold. He realized that consumers hated the real estate “finders” that were just paid lead gen forms.
So, HomeLight took a quantitative approach to rating agents. Who sold houses fastest? Who negotiates best relative to the listed price? They used public data and peer reviews to create ratings that consumers could trust. He blew us away with his knowledge of the industry. When a CEO knows his or her stuff, it shows.
Finally, we look for grit. Will the CEO be persistent in the face of failure and obstacles? Startups are not for the faint of heart or the romantic windmill chasers.
No More Beauty Contests
Investing solely with intuition is like judging a basketball game by the players’ uniforms, instead of points scored. It’s a beauty contest susceptible to egomania, hype, FOMO, and shiny object syndrome. A tech ‘bubble’ signifies that intuition has been unhinged from reason and logic.
Like my fellow investor said, quantitative VCs don’t do what “real VCs” do. We keep it lean and iterate our methodology, just like the startups we champion. We balance intuition and data because it’s good for founders and vital to building a stable technology ecosystem.