The Metrics Brothers
00:06:36 · Ray Rike
[00:06:36] S1: Well, I do find if you look at revenue growth, if you look at back in early twenty twenty one, the R squared for revenue growth to the enterprise value to revenue multiples was 49. And that's all the way down to 20% today. And Rule 40 back then in the go go growth days was only at 12% and now it's up to 34%. So that's the one thing. And then Dave, I have to go to slide 14 real quick, that R squared. What's really important is even though rule of 40 is bouncing growth and profitability, free cash flow margin, Growth is still about 1.9 times more important to that multiple than free cash flow margin. So I think that's important to read.
00:07:20 · Dave Kellogg, Ray Rike
[00:07:20] S0: Yeah. And that's pretty stable over time, right? That's the genesis of rule of acts. I think when they published that note, they felt it was 2.3 X. If I remember the number and Dave Kellogg said, I just use two X. Like to me, the best overall predictor is a two X growth rated rule of 40. And the funny thing, Ray, is I'd actually argue that you can use this relative importance as a bubble indicator. So when this metric's running around two, we're looking at slide 14 here, that's normal times. Growth has two times the impact of profit because it should, right? Because growth compounds, profit doesn't. But when that multiple gets up to four or five, 10, you can know that you're actually in a bubble. So I kind of use this metric backwards maybe to say, Hey, revenue growth alone is predicting revenue multiple better than R40, or if the relative impact of growth in R40 is like five to 10 times free cash flow, hey folks, we're in a bubble. [00:08:20] S1: Dave, the only thing I'll say is I'm thinking back to our State of AI episode where we talked about supernovas and shooting stars. Yep. I would love to see the balance of growth to free cash flow in those private AI companies.
00:08:20 · Ray Rike, Dave Kellogg
[00:08:20] S1: Dave, the only thing I'll say is I'm thinking back to our State of AI episode where we talked about supernovas and shooting stars. Yep. I would love to see the balance of growth to free cash flow in those private AI companies. [00:08:34] S0: Yeah, well they got plenty of both, right? So hopefully it's still offsets. That was the whole point of R40. So quick look at slide 17. There's a lot of capital going into AI. The most interesting thing about this chart and why I call it out is it looks flat. This is a bad charting practice folks, but they're showing, they're ending the chart with 1H twenty twenty five comparing it all to all of 2024. And it makes it look like things are flat, but the reality is it's flat when you compare the first half of twenty twenty five to all of 2024, I. E. It's on track to double. Dollars $377,000,000,000 in the first half of twenty five compared to $363 in '24. Any thoughts on that one, Ray? [00:09:16] S1: No, I totally agree with the chart. The only thing I would say is I'd love to know if this is just VC and PE money or if it includes corporate investments also, because there's so many corporate investments in AI companies today.
00:09:16 · Ray Rike, Dave Kellogg
[00:09:16] S1: No, I totally agree with the chart. The only thing I would say is I'd love to know if this is just VC and PE money or if it includes corporate investments also, because there's so many corporate investments in AI companies today. [00:09:28] S0: Yeah, I suspect it has to, but the short answer is I'm not sure. I'm going to slip over now to slide 19 where they talk about some key top line and efficiency metrics and how they're trending longitudinally, I. E. Over time. I was just going to eyeball some of these charts. In my opinion, rates have basically stabilized. They're down from like the twenty twenty days, but growth by segment is roughly flat. There's a couple of small trends that I won't bring up here. One on slide 21 I will bring up is that NDR seems to have settled into a new range that we can now remember as a rule of thumb, which is what I like to do. In the first half of twenty twenty five, for companies less than 100,000,000, the top quartile, not the median, there we go again, never quite sure what you're looking at at the Iconiq data, so redefined print, is 121%. And for greater than a 100 million, it's 110% roughly. Thoughts on NDR and where it's stabilizing, Ray?
00:09:28 · Dave Kellogg, Ray Rike
[00:09:28] S0: Yeah, I suspect it has to, but the short answer is I'm not sure. I'm going to slip over now to slide 19 where they talk about some key top line and efficiency metrics and how they're trending longitudinally, I. E. Over time. I was just going to eyeball some of these charts. In my opinion, rates have basically stabilized. They're down from like the twenty twenty days, but growth by segment is roughly flat. There's a couple of small trends that I won't bring up here. One on slide 21 I will bring up is that NDR seems to have settled into a new range that we can now remember as a rule of thumb, which is what I like to do. In the first half of twenty twenty five, for companies less than 100,000,000, the top quartile, not the median, there we go again, never quite sure what you're looking at at the Iconiq data, so redefined print, is 121%. And for greater than a 100 million, it's 110% roughly. Thoughts on NDR and where it's stabilizing, Ray? [00:10:28] S1: No, I think the only thing I take away from this slide beyond that it's stabilizing is the end count. The end counts at the bottom of each of these slides. And the end count was like two thirty three for the less than a 100,000,000 in 2020. And now it's down to 41. Above a 100,000,000, it's 33. So I'm just questioning why the end count's going down so much, but that's the benchmarker in me.
00:10:28 · Ray Rike, Dave Kellogg
[00:10:28] S1: No, I think the only thing I take away from this slide beyond that it's stabilizing is the end count. The end counts at the bottom of each of these slides. And the end count was like two thirty three for the less than a 100,000,000 in 2020. And now it's down to 41. Above a 100,000,000, it's 33. So I'm just questioning why the end count's going down so much, but that's the benchmarker in me. [00:10:53] S0: Yeah, and we're gonna see this. Look at slide 23, Ray. You'll see, I'm gonna go to the end count or the end size and basically at the bottom of the slide. And this slide is looking at CAC payback period. And it goes from 142 in their pre-twenty twenty benchmark to 21 today. And when these numbers get that small, you got be careful what you're looking at. Even last year in 2024, it was up in the nineties. So I don't know why you have a sample of 127 companies and only 21 are included in this question. I'm not sure why, but keep an eye on the end. I think that's the rule. [00:11:26] S1: Yeah. The other thing, since you're on slide 23 here, which is CAC payback period, which is at fifteen point nine months. The only thing I would recommend on this one also is that if this is only private companies, because they calculate CAC payback period on new ARR, but public companies calculate CAC payback period based upon implied net new ARR. So there is a difference between private and public.