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17 results for “valuation metrics”
Concept10 mentions across episodes
valuation
Topic7 mentions across episodes
valuation
Topic2 mentions across episodes
metrics
...You mentioned it there, but the most common that you see again, I wanna be the best investor I can be, Dave. Like, really teach me. That's why I love my job. Yeah. We've stumbled into my favorite example, which is CAC payback period. It's it's a comp
12:35 / 13:47
from transcript12:35 – 13:47
...metrics because you're in screening mode. Right? And in screening mode, the payback period is forty eight months. I don't need to beat these people, and I don't care why. Right? It it's a great screening metric. But if you're actually trying to fix t
9:35 / 10:47
from transcript9:35 – 10:47
...Don't need doro metrics are usually popular. And at the end of the day, like, what we we initially went really hard in all the metric stuff. Yeah. What we found is that oftentimes, if they liked it, they wouldn't care. And if they didn't like it, the
39:02 / 40:05
from transcript39:02 – 40:05
...metrics should be, you have to understand the qualitative underpinnings. And a great example of this is retention. Like setting retention metrics, for example, is 80 to 90% understanding the qualitative definitions of what is the problem that you are
35:50 / 37:02
from transcript35:50 – 37:02
...In other words, incentives drive behavior. So if you tell a team, go and optimize this nurture metric, it's going to go up 100%, but then many things that you don't want to go down could go down. So for example, in the DoorDash case, you could say, I
53:13 / 54:17
from transcript53:13 – 54:17
...on these metrics right now? And then you need to go through the exercise of, okay, well, if I move this part of the system from a to B, what happens to the output and how does that differ between if I move, you know, metric B from A to B. And what th
11:55 / 13:00
from transcript11:55 – 13:00
...a set of metrics that you have some belief correlate with retention. If you're a small company, you can't run like statistically significant analysis and say this provably drives retention. But at a minimum, you can say, this is our hypothesis. You c
13:31 / 14:31
from transcript13:31 – 14:31
...and downstream metrics that you can measure. Great. Measure measure them all you want, but goal on the thing that makes your customer happy. And one example from a recent arc company that I worked with is a robotics company. The whole point is that t
16:42 / 18:23
from transcript16:42 – 18:23
...that matter, but focus on the right metrics. It can be there's a lot of shoving vanity metrics out there as a sign of something, and maybe other investors will disagree with you, but that is credibility destroying, at least for me when when a metric
41:51 / 43:03
from transcript41:51 – 43:03
...metrics we really look at. And, like, it they may be different in all businesses. I don't wanna give some prescriptive recipe that is you you have to use, but maybe we'll skip this, but this was a little bit of the debate that spilled out into the pu
42:45 / 43:54
from transcript42:45 – 43:54
...metrics. When we think about space, space is a framework. It doesn't tell you what metric to use. So I'll say sometimes people get real frustrated because I didn't tell them what to measure. Right?
14:55 / 16:04
from transcript14:55 – 16:04
If you're a small company, you can't run like statistically significant analysis and say this provably drives retention. But at a minimum, you can say, this is our hypothesis. You can come into the investor and say, yeah, we have these four core thin
14:12 / 15:19
from transcript14:12 – 15:19
...Can you tease any of the criteria without giving away the the secrets of Yeah. Yeah. We wanted to see 10,000,000 run rate. We wanna see very strong growth. We wanna see a business model that wasn't sort of 0% gross margins but gonna improve in the fu
2:15 / 3:26
from transcript2:15 – 3:26
...of evaluation, or is that mostly window dressing to get more social media hits because you're one point higher on one test or another? So, I'd say it's the labs care about the benchmarks because it's good for bragging rights. It's good for recruiting
45:39 / 46:45
from transcript45:39 – 46:45
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