A short YouTube talk (transcript) advising startups to build granular, bottom-up funnel models per segment to diagnose and guide go-to-market moves into Enterprise. The speaker emphasizes funnel math—leads needed, conversion rates, opportunity size, win rate, time-to-win and deployment—and using historical and external data to set assumptions and identify where to correct or double down.
So often you start with your top down. You know, we'd like 10 million in ARR from the sales team or from this segment or whatever. Not enough folks are building very granular bottom up versions of what actually needs to be true to hit that. This is, it's just funnel math, we all know it. How many leads do you need? What's the conversion rate going to be? What's the average opportunity size? What's your win rate? How long does it take to win? How long does it take to deploy? How long does revenue take to ramp? Right. Like if you're in a consumption business, it's actually a long funnel. But you've got to build that and you've got, to Lindsey's point, build it per segment. The key to this actually is it gives you a diagnostic either when things are going well or poorly. So particularly as you move up market, you're going to have to make some assumptions. When we moved into Enterprise, we were able to look at that segment below Enterprise. What was our historical performance? And then we also looked at external market data. Like on average, what do you see in Enterprise? And for year one we just had to make some reasonable assumptions. But then when we were deviating, and we definitely did, we knew exactly where. In Stripe's case, actually it turned out that we were doing a lot more deals, but they were smaller and higher velocity in Enterprise in year one. And so if you don't do that, then you don't know where to correct and where to potentially double down if things are going well.
