Customer Lifetime Value to CAC Ratio - The Ultimate Compound SaaS Metric

Live from Schenectady, New York, it's SaaS Talk with the Metrics Brothers, Growth and CAC.

And I'm Growth, better known as Ray Reich, founder and CEO of Benchmarkit.

And I'm CAC, better known as Dave Kellogg, independent consultant, EIR at Balderson Capital, and the author of Kelblog.

And together we are the Metrix Brothers.

And we go together like Andreessen and Horowitz?

I think you need to stop letting me write the jokes because, you know, I— but I am funny, Dave.

Yeah, yeah, just like Lieutenant Hawk in Good Morning, Vietnam, if anyone remembers that fantastic movie and the scene where they fire the not funny guy and he goes, sir, in my heart, I know I am funny.

And then, thank you, Lieutenant, that'll be all. Yep.

So why are we talking about Andreessen Horowitz again? Uh, do you want to debate public policy or effective accelerationism or something like that, Ray?

I'm just trying to get Marc Andreessen or Ben on my podcast. But no, really, a16z was the catalyst for this week's episode because back in August— I mean, we started talking about this 8 months ago, Dave— They published an article on why do investors care so much about customer lifetime value to CAC ratio. So I thought it'd be fun to dive into it.

Okay, well, you know, I've been working on a seminal post on LTV to CAC for about that entire 8-month period, Ray, and, uh, you know, I'm not quite done yet.

Yeah, well, waiting for you to finish that post is like waiting for Godot.

Wow, we're getting deeply intellectual today here, Ray. Samuel Beckett plays, originally written in French, as you reminded me in the warm-up, um, but he's gonna show up any day. That I'm sure you'll have a post showing up any day, Ray.

Maybe we'll have to change our nicknames and I'll be Vladimir.

Okay. In the meantime, we're going to let you discuss LTV to CAC. I know you've got a hot take on it and we want to hear it and I want to debate you on it. But before we do that, let's hear a word from our presenting sponsor.

The Metrics Brothers is proudly sponsored by Benchmarkit, the B2B AI and software industry's largest, broadest, and most contextualized benchmarking index. Dave Kellogg and Ray Groth Wright have put the Metrics Brothers podcast on hiatus for remainder of 2026. All episodes we have ever recorded are still available on your favorite podcasting app. You can reach Dave at Kellogg and Ray on LinkedIn at Ray Reich. Thank you so much for listening to the Metrics Brothers podcast. Okay. Now, even the acronym for customer lifetime value to CAC can be debated. So I use CLTV to CAC ratio, but some people use LTV to CAC. So let's start right there. But it's really measuring what's that lifetime value of your customer compared to what it costs to acquire.

Yeah, so we, we blow up on agreement right out of the gate on this one, Ray, because I'm not— I, I don't call it CLTV:CAC like you do. I call it LTV/CAC. Uh, so I, I, I leave the C out, so I just say lifetime value to CAC ratio. So, so we could debate the name. We're going to debate everything on this episode. This is going to be more back and forthy than usual. One thing we won't debate is the point, and the point is to compare— let's call this the ultimate SaaS metric once, because we're trying to— why ultimate? Because we're trying to compare how much you spend to get something versus what it's worth. And that's really the best thing about this metric is its intent.

Yeah. And once we get into what the rate of return says, if you hit the industry benchmark, it's pretty incredible. But let's start with the customer lifetime value component. And I think this will— I know there's a debate here. So I use the formula, you take the average ARR per account You multiply that by the recurring revenue gross margin, and then you divide that by the annual customer churn on an ARR basis. And that gives you customer lifetime value. So, Dave, I think you might have a question right off the start.

Yeah, I mean, so see, there's 2 things you're doing here. You're doing it on a gross margin basis, and I don't think I do. I think I do it on an ARR basis. I can't remember. I have to go look at my post. So there's 2 debatable points when we talk about someone's value. Are we talking about their value in terms of ARR/revenue? Are we talking about their value after cost of goods sold, goods sold, i.e., recurring revenue gross margin, as you call it, or simply subscription gross margin? So that's one element of debate. Ray goes on the gross margin side. I think I go on the ARR side because you asked me how much it was worth. I didn't ask me anything about how efficiently I ran my service. Then the other issue here, and this is a little bit of sleight of hand that Brother Ray did, is he's using average ARR per account. And Ray, What do you mean by average? Average of a particular time cohort or average of what? What average?

Yeah, this is a debate. So I typically like to do this on an annualized basis, or I can look at a trailing 12 months, and I'll look at the total ARR for that time period, and I divide it by the average number of customers on contract during that same time period. And the reason I said that, because you're going to have, um, the number of accounts keeps going up, right? And even though you have churn, so I use the average ARR per account. If you read the Andreessen Horowitz article, 2 things. They did it more B2C, so they used ARPU, average revenue per user. And they did a version not gross margin adjusted, then they did another version gross margin adjusted. So they hedged and said, we do both. Now there is a debate, Dave. Should you just use the ARR for a cohort of customers acquired in a specific period this year? I don't. I do it across the entire customer base. And the reason I do that is it then includes the benefit of expansion revenue. So I don't factor it using NRR. I just use the average revenue per account.

Yeah, it's pretty implicit there. I want— I wanted you to hear Ray's explanation of what Ray does. Because, um, it's not how I do things, first. And second, it's pretty implicit. So if you ask Ray, how do you factor expansion into this, he'd say, yes, I do, right? Um, he'd say, I've got it captured by using the average ARR per account, really, as of that moment in time, for all time. The last time we had this debate, Ray, it was effectively just look over all time, tell me how big the ARR pool is, divide by the number of customers, bang, there's my average ARR per account. So kind of snapshot as of now. That's how Ray do it. I do it differently. I look at this as a period metric. So I would calculate it for a quarter or for a year. Why do I view it as a period metric? Because you asked me how much it costs as well. So I need to know how much it costs to get all those customers I got in Q2. Therefore, I get Q1 sales and marketing, right? I've already just looking at the CAC side of it, it's inherently a period metric. So I keep that philosophy when I look at lifetime value. I say, okay, then what was my most recent churn? Let's invert that and multiply by the new ARR on the period, I would include both new customer, new logo ARR, and expansion ARR there. So I would include expansion ARR because it's a subtype of new ARR. But, but that's how I would do it. I would, I would calculate LTV to CAC for a time period like Q2, and therefore what— therefore I'd use Q1 sales and marketing, Q1 churn rate, right, as the actuals to try and do the calculation.

Yeah, well, and the other reason I do it, and, and there's no right or wrong here, But I was taught this back at GE years and years ago, and we were doing customer lifetime value. If you have a customer that's around for 4, 5, 6 years, you really don't know what the lifetime value is unless you have a predictive variable that says, here's how much a customer expands their relationship with you every year. And then we would— there we would multiply it by that growth factor.

If a 6-year life, you got to use Yeah, it helps when you're a couple hundred year old company with a lot of operating history, right? As opposed to a 2 or 3 year old startup. So, I mean, Ray, you're actually hitting on one of the biggest flaws in this metric is you have very young companies getting very long lifetimes off very low churn rates, and that's a problem. So this is why I don't like this metric, frankly. Uh, you know, at one point I really called it the ultimate SaaS metric because that's its intent. It wants to be all in. How much are we spending to get somebody? And after we get them, how much are they worth? And, and I actually think that how much are we spending Spending metric, CAC is a pretty good metric. We've talked about that a lot already. It's the LTV part where I get nervous because it's an attempt to value the install base. Basically, that's what it's trying to do. How much are those people worth in the fullness of time? In LTV to CAC, you do it, but you get the lifetime by inverting the churn rate. You get the lifetime value by multiplying that times some ARR figure, either Ray's average ARR for the whole base or my average ARR for the set of customers we just acquired, one or the other. But the problem is, due to long lifetimes, driven by low churn rates, you can get ridiculously large numbers. So that's the flaw in the metric.

It is a flaw. But now, why do investors love it so much, right? Because I— and maybe it's wrong— but I always look at a metric, is it more operator-friendly or more investor-friendly? But investors love this because let's say, you know, the benchmark to common wisdom was 3x. So customer lifetime value is 3 times more than a customer acquisition cost. The last 2 years of benchmarks say that's closer to 4x. So CLTV is 4 times customer acquisition cost. So let's use an example. If I'm in a business where it's $50,000 to acquire a new customer, I have a 4x, that's a $200K lifetime value. Dave, you did the math for me, but over a 5-year period, that's a 61% compounded annual growth rate, right? Not a growth rate. I'm sorry. Well, I totally said that wrong. It's a rate of return.

I trust you on that, right? Keep going. So you're basically saying it approximately gives you an ROI, basically, that LTV to CAC is One step away from ROI.

Exactly. And I think that's why investors love it. Now, there's a big risk here, and, and I, I can't believe I even hear this thing, but I've had seed-stage companies said, well, the investor just asked me what my CLTV to CAC is. And I'm like, well, how long have you had subscriptions that you've renewed? It's like, well, we've had 9 to 12 months. Yeah, so how can you know your churn rate in the first I always say you should have 2 annual renewal periods, Dave, not just one.

Yeah, so I approach this differently, Ray. Um, so look, there's 2 questions you asked. One is, why do investors like it? First, because it actually predates NRR as a metric. Let's be clear, LTV— in the beginning there was LTV to CAC, and then people came along and said, hey, wait a minute, isn't NRR a better way to value the install base, which is really what the LTV part of LTV to CAC is trying to do? Um, so, so one, I think history is on the side of LTV to CAC. It came first. It is the standard way do things. And I think your point's well taken that— I mean, again, the reason people like LTV to CAC is that you're trying to measure what something's worth versus what you paid for it, and you could express that as an ROI if you want to. So I, I do think, for whatever, for whatever it's worth on my side, that a multi-year NRR— if I want to know what happens to the customer base over time, I could invert the current period churn rate, and that's pretty dangerous for reasons discussed. Or I could just say, if I've got 3, 5 years of operating history, what happened to the people I acquired 3 years ago? I could do a 3-year NRR. That's something most people talk about and just calculate an ARR for the 3-year period and then use that to get a 3-year LTV to CAC, right? So there are other, in my opinion, better ways to answer the question, how do I value the installed base, than inverting the, the most recent churn rate.

And now for everyone who's listening to us can understand why at the SaaS Metric Standards Board it's so hard to come out with these standards because there's so many great perspectives and trying to get the industry to rally around one standard, Dave, It's really important because if the benchmark is, like I said, closer to 4x to 1 versus 3x to 1, how do you know that? Is it using gross margin adjusted? What is the calculation for the average revenue, right? It's really hard to use benchmarks when you don't have standard calculations.

Yeah, that's why I applaud the work you're doing, and that's why this one's particularly hard because it is a compound metric. It's got so many questions wrapped into it. But, but look, I'll be practical for a minute. You are going to get asked about this if you're a SaaS company, an early-stage SaaS company. You should calculate it. In my opinion, you should calculate SaaS metrics by default to your advantage. So by default, so I would do it on an ARR basis, not a gross margin basis. And I would calculate the churn side of it exactly the way Ray does, which is just 1 minus GRR, then invert that to get lifetime, and then multiply by average ARR. I do it for a time period, Ray does it for the whole base. If you're an early-stage startup, it probably won't be that much different. So, um, the place where that really comes into play, Ray, is when you're an older startup and you're starting to drive your ASP up, and I'd argue your formula makes me carry the baggage of all the old small customers, and it will show less progress on my kind of upmarket initiative. And by the way, and conversely.

Yeah, but you know me, Dave. I don't think any metric as a company matures should be calculated if you're not calculating it by segment. So my SMB versus mid-market versus enterprise, I think you should be calculating CLCV to CAC across all 3 of those segments.

That's excellent. It's an excellent solution to the problem, Ray, uh, to be honest. Yeah, because I was assuming a blended one and the old guys are going to hurt you. If you segment it, that solves that problem. Yeah.

Now here's another thing, and I— one of my favorite presentations I've ever heard you do is why you can't fix a CAC payback period. So same with CLTV to CAC. You can't fix the CLTV to CAC, but you can identify the primary input variables that are creating a lower one than a benchmark. Would you agree with that?

Yeah, I think the point, Ray— and thanks for saying that nice thing about that presentation— the whole point of that presentation was you can't fix a compound metric, right? And investors— this is back to what you talked about earlier— investors like compound metrics because they're great for screening. They're— they work at a high level of abstraction. Uh, there's, there's plenty of nice things to say about compound metrics, but when you actually want to fix problems, if you tell me your LTV to CAC is 2, I go, well, that's bad. We can all agree that's bad.

But, but like, what do we do about about it.

Where's the problem? Is your deal size too low? Your CAC too high? Your churn too high? Your churn too high, right? We, we need to drill in. So, so yeah, in the same sense that you can't fix CAC payback period because it's a compound metric with many levers, you can't quote unquote fix an LTV to CAC for the same reason.

Yeah, but it does, you know, we've covered so many of these metrics. If you look at the CAC ratio, how much sales and marketing you're investing to acquire each customer, And specifically each dollar of ARR, that might be one of the input variables. Or maybe you need to look at your GRR. Hell, if you're using the gross margin, even 1 or 2 points of gross margin improvement can increase your LTV to CAC. So you got to look at all the input variables and decide which ones have the biggest impact on this.

Amen.

Okay, Dave, anything else we should talk about on this CLTV to CAC since we're in such great alignment on it?

So I think— what do I think? I don't think so. Look, when I do my post that I've never done, when I do the Waiting for Godot LTV to CAC post, I'm going to drill into the problems with LTV. And we hit most of them already. You get heavily forward-loaded lifetimes. If you are going to forward-load them, just say you're going to try and tell an investor you have a 20-year lifetime. Not something I would do, but say you were going to do it, then with these inflation rates today, you're going to have to discount it. Right? You can't just— but like back in the day of ZIRP, you could just go, oh, I've got a 20-year lifetime, so if it's 100 units of ARR, then it's going to be the 2,000 lifetime ARR value, right? No discounting. Well, now you're going to have to if you want to be credible. Not that you're that credible anyway with a 20-year lifetime, but if you want to play that card, get ready for the next card to come back and say you need to discount that because there's material interest rates.

Yeah, it's funny. I even had one VC tell me once, he goes, Yeah, so when we do CLTV to CAC, if any of our portfolio companies have higher than 10, we limit it. We never count more than 10. I'm like, well, that seems like an easy mathematical way to try to take out some of the, the outliers, but maybe you should really look at how they're calculating CLTV.

Yeah, by the way, that's an increasingly popular solution, which is you cap it, you cap the lifetime at either— I've seen 5 years, right? You, you call it a 5-year LTV to CAC. So 5-year LT, or kind of— it's really a 5-year value to CAC, not an LTV. It's a 5YV, not an LTV. But you could do a 10YV to CAC as well. At least those are more descriptive names. They may not be more meaningful, but if you want to get rid of being gamed, which I suspect some investors are tired of, it's not a bad example. Just say, hey, we calculate a 5-year LTV to CAC around here. And what it is mathematically is it just puts a constraint on how bad your CAC can be. I'd have to do a little quick algebra to figure it out, but it's effectively— it's changing the metric. But you're right, if you— well, I'll do the math offline.

There's a new episode, Constraint-Based SAS Metric Calculations.

There you go.

There you go. Well, Dave, well, thank you for, number one, talking about an Irish playwright and Waiting for Godot. But thank you so much for going ahead and having this discussion because I know you wanted to try and have the opportunity to put all your thoughts together. And I really appreciate you using this as One of the ways hopefully to see that post finally come out, CAC.

Okay, well, thanks a lot. It will hopefully— this will hopefully serve as a motivator. Great talking about this topic with you, and, uh, I think that's it for me.

Okay, thank you everyone for listening to us this week, and we'll talk to you next week. Bye-bye now.

The Metrics Brothers AI, SaaS, and More is a production of The Metrics Brothers Growth and CAC and a member of the Benchmarkit Podcast Network. By accessing this podcast, you acknowledge that the Metrics Brothers make no warranty, guarantee, or representation as to the accuracy or sufficiency of the information provided or the humor content of the jokes told.

Ray?

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