275. Doubling Down on Data to Discover Overlooked Founders, Teaching and Coaching CEOs, & Bullpen's Approach to Measuring Fund Success (Paul Martino)
The Full Ratchet (TFR): Venture Capital and Startup Investing Demystified - Podcast tekijän mukaan Nick Moran | Angel Investor | Startup Advisor | Venture Capitalist
Paul Martino of Bullpen Capital joins Nick to discuss Doubling Down on Data to Discover Overlooked Founders, Teaching and Coaching CEOs, & Bullpen's Approach to Measuring Fund Success. In this episode, we cover: Can you first refresh us on the thesis at Bullpen and then maybe give us an update on the firm over the past three years? How do you define post-seed today... and is it moving as other stages have? Are you still one of the few specialized at post-seed or have you seen increasing competition? Is there still a strong emphasis on metrics and using the data as an early filter of deals? How are you using data to source? What do you look for in founders? Why are you committed to coaching/supporting companies? We all know the scorecard of success in VC... DPI, TVPI, IRR, PME, etc... what are the leading indicators of success that you measure and manage to make sure you're driving success in those metrics. You are a founder yourself, what advice would you give to founders right now that are building during the Coronavirus Recession Wrote article: "The 2008 Recession Saved Our Company. The Coronavirus Recession Might Save Yours, Too" Let's say you have a chance to speak w/ a younger Paul, circa 2010... what advice to give? What does the underdog founder look like? or What do you look for in founders? What's broken in the venture ecosystem? This question is called three data points. I'm going to give you a hypothetical situation w/ a startup and you can ask three questions for three specific data points. Let's say you're approached to invest in a post-seed stage SaaS startup... The founder does not come from big tech. Her HQ is in St. Louis The sector is retail. They launched 12 months ago. and they currently have $80k MRR. Again, the catch is, you can only ask 3 questions for 3 specific data points, in order to make your decision. What three questions do you ask?