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👋 Hi, I’m Andre and welcome to my newsletter Data Driven VC which is all about becoming a better investor with data and AI.
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Welcome to another edition of our Sunday “Resources” stream where we share our most valuable data & resources across four rotating formats:
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At the end of this post, you’ll find a unique deep dive on “How to Predict Startup Success With Alternative Data” with Rachel Wong from Basis Set, Jake Ellowitz from Tribe Capital, Amy Lin from Outcast Ventures, and William Mataker from Bertram Capital.
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How to Predict Startup Success With Alternative Data
I'm excited to share one of the most watched sessions from the Virtual DDVC Summit 2026 where experts from four leading VC and PE firms presented their latest research on what truly drives investment performance and predictable founder outcomes.
Watch if you want to learn:
Why co-founders who never worked together saw 26% higher exit outcomes than former coworkers
How previous founding experience increases success rates by 41%, and why teams with a previously exited female CEO outperformed all-male teams by nearly 2x
Why pedigree (think top-tier schools) barely moves the needle, while time series data like early headcount growth and hiring disciplines offers strong predictive signal
The case for using data to prioritize GP attention at pre-seed and seed rather than trying to pick winners
When to deploy deterministic models to codify human judgment vs. probabilistic models for high-liquidity sectors
Why "weather reports" on sector supply and demand should drive your negotiation posture and valuation discipline
How AI commoditizes the "how" of data processing, and why durable alpha lives in the "why"
Why grit, humility, and the ability to iterate on new data outweigh anything you can read on a resume
… and a lot more
Here’s the link to the full panel discussion👇
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