How VCs Actually Evaluate Startups Before Investing
The criteria VCs say they use and the signals that actually predict their decisions are not the same. Here is what the real data shows.
The official VC framework is simple: great team, large market, strong product. Every partner at every firm says some version of this. It is not wrong, but it is also not particularly useful, because it does not tell you what great, large, or strong actually means in practice.
The Gap Between What VCs Say and What the Data Shows
Market size framing is one of the least predictive elements, despite being the one most founders spend the most time on. Almost any market can be framed as large with the right construction. VCs have seen enough of those constructions to be appropriately skeptical.
Traction is highly predictive, but not in the way most founders assume. The question is not whether you have impressive growth metrics. The question is whether the growth represents genuine organic pull. Users who come back, customers who pay and keep paying, referrals from existing users.
Founder-market fit shows up repeatedly in retrospective analysis of successful portfolios. The founders who built durable companies were often not the most generically impressive people in the pool. They were the ones who had a specific, structural reason to be building in that particular space.
The Three-Leg Framework Most Strong Evaluations Use
Demand: Is there real evidence that customers want this and will pay for it?
Supply: Who else is in this space, how are they positioned, and what does the competitive history tell you about who wins and why?
Winnability: Given this specific team, with their specific advantages and disadvantages, what is their realistic path to owning a meaningful position in this market?
What Weak Applications Have in Common
The deals that do not make it past initial screening almost always have the same gaps. Large market claims without a specific, concrete beachhead. Traction that is early-stage and hard to interpret as signal versus noise. A team that is impressive on paper but lacks a clear structural reason why they specifically should win in this space.
Valtr grades startup ideas against real comparable venture outcomes, giving founders and evaluators a data-grounded picture of demand, competition, and winnability before the pitch process begins. The first grade is free, no card required.
Ori is the named coach inside Valtr. It reads your Reality Index with you, points at the riskiest assumption, and never cheerleads. Evidence, in plain language.