I’ve decided to open source my evaluation criteria for seed stage companies. This due diligence outline has evolved over my last 5 and a half years in venture investing and will continue to evolve.
To preface, my framework for investing is malleable and so attached (at the end of this blog post) is more of a rough guideline than a rigid framework. There are questions unique to each business. I continue to tweak my working outline for due diligence and add modifications based on the type of company I’m evaluating (healthcare vs. SMB SaaS, for example) and how far along it is. Due diligence is a way to better get to know the company and its founders, but it is impossible to know everything about a company! It is also many times impossible to do all the due diligence you want given short timelines, competitive rounds, and maintaining sensitivity to founder overhead.
One thing to note is that I’m not looking to achieve strict pattern matching as an investor*. I also believe that pattern matching to previous variables common in successful investments is overrated, especially in seed stage venture capital. The best meetings I’ve had are ones where I walk out surprised — surprised by a unique, unintuitive business model, surprised by an ignored market that is absent from any investor’s prescribed “thesis”, or surprised by a founders’ odd and unconventional personal story that led to the company.
I’ve seen enough successful companies where investors said “no”, to hold the view that pattern matching is at best a way to mitigate downside and at worst a way to miss out on the next Facebook. And, pattern matching can even be sexist if you remember this John Doerr quote from 2009. **
Open-mindedness is core to Trifecta Capital’s ethos. I try to avoid dogmatism or the creeping feeling that you know-it-all that comes when you’ve been an investor for too long.
With that being said, I’ve attached my basic outline for due diligence when evaluating a prospective seed stage company. It’s evolved from a variety of teachers. I started working in venture for a former managing partner at Sequoia Capital, Mark Stevens, who defined a due diligence packet for the firm in the 80s. Since then I’ve learned by doing and through mistakes (it’s too early to claim any success).
The document covers the basic areas where I like to get to know a startup. This includes the founders/team, market, customers (essentially part of the market, but worthy of it’s own section), technology, metrics (also known as traction), and regulation. Reference checks, both on the team and from customers are really useful in helping me understand a company from secondary sources.
Bottom-line: half the battle in venture is sifting the relevant questions to ask from the irrelevant. On one side there are always many drawbacks, unproven assumptions, or risks inherent in a seed stage investment. On the opposing side, there may be many merits and assumptions proven correct.
What are the couple things that have to be right for the company to succeed? That is what the due diligence needs to parse.
https://docs.google.com/document/d/1cMW1-_a7etrX1NVfZ-y1gY8VbKAHKLxErfHEEg3W3pk/edit?usp=sharing
*In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact.
**“That correlates more with any other success factor that I’ve seen in the world’s greatest entrepreneurs. If you look at [Amazon founder Jeff] Bezos, or [Netscape founder Marc] Andreessen, [Yahoo co-founder] David Filo, the founders of Google, they all seem to be white, male, nerds who’ve dropped out of Harvard or Stanford and they absolutely have no social life,” he said.
I’m sure he regrets this quote now (it was used against him in the Ellen Pao trial), but it shows the systemic bias that gets reinforced over time and get’s labeled “good pattern matching.”
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