Product Led Growth and the impact on Customer Acquisition Cost

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

I'm Growth, most often known as Ray Reich, the founder and CEO of Benchmarkit, formerly RevOps Squared.

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

And together we are the Metrics Brothers.

Well, Brother Ray, what's on tap for today?

Well, can you believe it? This is our 8th episode of SaaS Talk. And the last episode we talked about CAC payback period. And at the end of that, a big question came up, and that is, how is CAC, customer acquisition costs, impacted by different go-to-market strategies like using free trials, or even a freemium model. So I thought we should talk about how CAC's impacted by your go-to-market motion today.

Awesome. Okay, but Ray, before we jump into that, let's hear a quick word from our presenting sponsor, Maxio.

The Metrics Brothers is proudly sponsored by Benchmarkit, the B2B AI and software industry's largest, broadest, and most contextualized benchmarking index. Dave CAC Kellogg and Ray Growth Wright Have put the Metrics Brothers podcast on hiatus for the 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. Dave, I'm really excited about this topic, but before we even talk about CAC and how it's impacted by free trials or freemium models. Can you just highlight why this is such an evolving trend today in the industry?

Well, there's a couple of reasons, in my opinion, Ray. I mean, one, PLG has become super hot. A lot of the VCs get very excited about PLG. For the last several years, it was hard to read anything in SaaS metrics land without hearing about how high NRRs were correlated to the PLG model and/or the consumption-based model, which we can cover in another episode. Right? The poster child always being Snowflake. And you would hear a lot about these free trial motions almost to the point, free trial or freemium product motions or even reverse trial motions. You'd hear a lot about these motions to the point where I think VCs were sometimes forcing them on companies where they didn't apply. But let's just say, right, in short, I just think the whole topic is hot. I think SaaS, the SaaS movement itself obviously created the ability to let people just try your software, right? Back in the days of yore, you couldn't do that because you had to You know, pay $20 million to a consultant and pay $2 million in software to set up and try something. So the whole notion of trying enterprise software didn't really exist in the past. And I would say with the birth of SaaS 20-something years ago, it then became possible. And I would say in the last 5 years or so, it became very popular.

Yeah, you said something that I really want to clarify because I confused myself when I first started trying to become a student of the entire product-led growth motion. I looked at these NRRs of the Snowflakes and Twilio and Datadogs, and I was thinking, oh, that's because they're product-led growth and use pricing together. But product-led growth does not mean you have a usage-based pricing model. Slack is a perfect example of that. They had a product-led growth model, right? They had a freemium product and then a very low-cost product. But then their goal was to escalate those into enterprise agreements, but they weren't usage-based, but they still had a very high NRR. I think that's one important thing is free trials or freemiums don't equate to the usage-based consumption pricing model. Does that make sense what I'm saying, Dave?

I agree that the 2 topics are independent, but let's just say correlated. Sometimes they do go together, but certainly not always. I think today we're going to focus— look, my main point on Snowflake was I just got tired of getting Snowflake rammed down my throat. Look at their NRR, look at their NRR. And the answer was usage-based pricing. So you just hit an old sensitive nerve, or we hit an old sensitive nerve in that topic. But on this topic, PLG motions, freemium models, yes, I agree with you. It doesn't have to be usage-based, but it can be. But they are different topics.

But let's pivot because this is something I found with some product-led growth and the use of freemium or free trials. Number one, it's early days. So people were much more focused on top-of-funnel performance than they were on customer acquisition cost efficiency. What I mean by that, Dave, I saw people focused on things like website visitor to freemium user, and then they looked at freemium user to paid user, and then paid user to paid company or customer. And then they focused a lot on things like activation. So for our freemium customers, did they reach that aha moment that you could then try to upsell them to a paid user or a paid customer? Let me stop there because that's a lot of things, but I don't think we are at the point yet where customer acquisition cost efficiency was the primary metric that people who are doing freemiums are worried about. It was top-of-funnel conversion, just like a demand gen function.

Well, I mean, look, to me, what would I say, Ray? I think the basic concept around premium or free trial motion Dates all the way back to open source, right? Right. And open source is kind of the original, the original free trial, right? Download it, link it, run it, run it on your own computer. So the, the notion of just, hey, just try the software, or as it said on the back of the Boston's First album about 8 times, listen to the album, right? They keep saying that, listen to the album. But to me, it's whenever I think of these models, I always think, listen to the album, right? Try the software, try the software. We can argue that goes all the way back to open source. Which I think it does. But, but in its modern incarnation, it's typically a SaaS business application that, that is an enterprise sale that has some sort of free version. And in those models, I think it's about the whole funnel, to be frank. I think it's definitely about top of funnel. I agree with you there. But, but look, we need to build the product itself to be easy to onboard, easy to expand, natural to expand, right? I mean, I think if you have to take it all the way back, right, it's the product sells itself.

Yeah.

That's kind of the hidden value prop or the desired value prop behind all of this, no?

Yeah. If you look at Atlassian, Atlassian was one of the first product-led growth companies. I was just recently talking to their chief marketing officer, Carrie-Lou Dietrich, and she was there from $50 million to $400 million IPO. A lot of their marketing was done in development communities. The StackOverflows and GitHubs. And what they measured was how many of those people would come and activate a license, a free license. And then they looked at the virility quotient of, did that one software developer or one team, how many users did that result in 3, 6, 12 months later? We're still not getting into whether it was CAC or not, but they really looked at how the leads became paid customers over time as the first conversion point.

Yeah. I mean, that's the whole premise of this. By the way, I think you meant virality, not virility. We could have a separate episode on that if you want. But don't disagree, Ray. I think the whole idea is how do we get people interested in trying this stuff? How do we get them to try this stuff? How do we eventually convert them into paid customers? In the case of Atlassian, the original modern PLG company, How do we then— because I think even they eventually collapsed and hired salespeople and started doing big enterprise deals. I think, I'm not sure. I know Slack did relatively early, but I think in the end, like all roads lead to Rome, all roads lead eventually, even for Atlassian, I believe, to having salespeople go kind of round up all these users into big multi-year enterprise contracts.

Yeah, you know, it's funny, Dave, we started the episode wanting to talk about customer acquisition costs and how free trials or freemiums kind of impacted that. But I did want to highlight one thing because it just came to mind. There was a report about a month ago. I believe it came from Jamin Bald, Cloud of Judgment.

We're thinking of the same report. I don't have it in front of me, but we're thinking of the same report that it's a lie, basically, right? They're not actually have lower sales and marketing costs.

PLG companies have a higher percent of revenue going to sales and marketing Once they hit a key inflection point, it's around $50 million, then it sells lead. But I still think we want to talk a little bit about how this whole free trials or freemium impacts CAC. You want to talk a little bit more about that?

Sure. Well, if you want to talk about it, let's have you talk about it, Ray. Talk to us about how either— and I wish we had a better term. Do we want to say PLG motion, freemium, or free trial? I want to call it PLG. We'll see if that works for you. How do PLG motions impact customer acquisition cost metrics?

First of all, the key is you're trying to get people to your website and you're trying to convert them to a free user. You're using top-of-the-funnel marketing measurements there, website visitor to free user, and then activation rate. Now, Dave, I don't consider a free user of a freemium product a customer and specifically not a paying customer. So what I have done with my clients I've worked with is we looked at getting a free user, not as customer acquisition costs. We looked at once they converted to a paid user, then what was the cost of getting each paid user? So customer acquisition cost was only calculated once they become a paid customer. And then what we would do after 3, 6, and 12 months We would see if that grew organically or virally, if I said it right this time. And then we would recalculate CAC at the end of a 3, 6, and 12-month period. Because if we went from 5 paid users to 100 paid users, i.e., customers, I wanted to see how CAC changed from initial customer status to A year later customer status.

Yeah, this is back to an issue we touched on in the last episode. But, but in a kind of land and expand model, where do we draw the line between the land and the expand? And is the land the one user who presumably has a horrifically high customer acquisition cost? Or is it the 100 users you get within the first 12 months, which in this convenient example divides whatever the CAC was by 100? Right. So it can be a major, major difference in your CAC ratio. And to me, conceptually, we're having to draw a line between what's land and what's expand. It sounds like you don't quite look at it that way because you do it on a trailing 6 and 12-month basis. My tendency would want to be to say, pick 6 months, pick 12 months, and just say, whenever I tell you the CAC, I'm going to tell you how much it costs not to acquire that one user, but the 100 users that we reliably— and I better be able to prove that reliably and predictably— get after we land with one.

And it's really key there is measuring what your normalized ramp period is. And as you can probably imagine, it also is based upon ICP. So what I see the best-in-class organizations doing and saying, hey, if that free user who became a paid user customer was then the enterprise, then I'm going to apply a different normalized ramp period to that Versus if they were in the SMB market where I know that it typically ramps within 3 months. So they will have different ramp periods and different calculations for SMB versus enterprise. Not saying that's right, but that's what I've seen done.

Right. And to a certain extent, the other end of that spectrum is consumer, where once Calendly gets Dave Kellogg's $90 a year, that's all they're ever going to get from me. Right? So, so I think that's the scale. If you're, if you're ultimately individual consumer, the land is that first license. And I think if you're an enterprise on your scale, the land is gonna be everything you get from that person and everyone touched by them in year 1, right? So it was 100-unit land. And by the way, that the, the good news is that reduces your customer acquisition cost, right? We divide it by 100. The bad news is it's gonna lower your NRR. You, you can't have your cake and eat it too. and calculate NRR off the 1 and calculate CAC off the 100. You need to be consistent. I'm sure you agree.

Yeah, definitely agree. And here's the other thing I've seen in CAC calculation for these PLG motions. Number one, I've seen a lot of companies form a growth marketing team, and the growth marketing team in the PLG model are the people responsible for taking free users converting them to pay and getting them to ramp to become enterprise customers. And that is dedicated growth marketing. And similarly, I've seen product development organizations take engineers, and those engineers are not responsible for core feature function of the product. They're responsible for in-app Upsells, cross-sells. So based upon a user and their usage behavior, getting them to that aha moment, hey, did you know you could do this? And that aha moment forms something called a product qualified lead, and that's when they try to upgrade them. And the cost of those product development resources, Dave, I argue, have to be part of your customer acquisition cost.

So look, I think this is one of the nice things. One of the many nice consequences of freemium style models is that they kind of force the creation of growth teams. And I love growth teams because to me, I define a growth team as a cross-functional group responsible for kind of maximizing revenue from that free funnel, right? So from all the free users, how do we get money from them? To your point, it's a 2-hop funnel. A lot of people think of it as 1 hop, but it's really 2 hop. The first hop is from free to paid. The second hop is from paid to enterprise. And they're most of the time they're responsible for that first hop. It's interesting if they're also responsible for the second one. But for sure, the growth team is responsible for the first hop. How do we turn free users into paid users? And what I like about it is it's cross-functional. So we don't get all the— you kind of breaks down the silos. So to me, you typically see sales represented, marketing represented, SDRs represented. The ones I've seen, right, it's just product, it's product management, i.e., product, not also engineering. And I would agree the product person's cost should go in. But if they're just drawing a little bit off some centralized engineering pool, I might get off the bus. If you actually have dedicated engineers as a separate team to do PLG-driven features, then okay, I think I'm with you. But, but much as I viewed ABM as a silo buster, account-based marketing, hey, let's get sales and marketing and SDRs working together with a goal to crack this account. I view growth teams as kind of a sibling or the same concept applied differently. Let's get salespeople, marketing people, product people, SDR people all working together to convert free users to paid users.

Fully agreed. Now, Kyle Poirier, who is at OpenView Ventures and one of the better thought leaders out there, he actually came out a couple of months ago saying that the SaaS Metrics 101, this CAC payback period and CAC ratio, that you and I are talking about need to be recast for this whole PLG model. He didn't really come up with too many cost or efficiency metrics. It was more conversion metrics. But, Dave, I actually think we do need 2 or 3 new metrics to measure the cost efficiency of converting freemium to paid.

Before we jump into that, yes, I found the data. I'm pretty sure we were both searching for it while we were talking. But, but the whole notion that PLGs spend more money in aggregate on R&D is true. This is again OpenView data and this is Insight Partners data here in this case. But in the most recent quarter, PLGs spent 28% of sales on R&D versus 24% for non-PLG. And then on sales and marketing, right, you think, oh, we spend more on R&D to make the product cheaper to sell. But kind of, you know, the great lie is no, they also spend more on sales and marketing. In the most recent quarter, 47% sales and marketing expense for PLG companies versus 34% for non-PLG. So doing this is expensive. It's definitely not the product selling itself, but it's worth doing for a lot of reasons we can talk later, including high growth, higher NRR, eventually high valuation. But back to your question, I just wanted to get the data out there because we love data here, right? Yes, I think we need new metrics. I think you need to start looking at funnel conversion metrics and I'm pretty sure you know which ones people should track.

Yeah. And that's where the number one thing, honestly, even though I hate MQLs and maybe you like MQLs, it's this concept of product qualified leads. And that's a scoring model that says, based upon the ICP of that freemium user, their product usage behavior, how many times they come back in, but also do they hit that aha moment in the application that delivers to real business value? Those 3 primary things, there's a lot more that creates a product qualified lead that is a signal to whoever's responsible for converting freemium to paid users. There's a 25% conversion rate at median day from a PQL, product qualified lead, to a paid customer. The overall conversion rate from free premium users to paid users is only 10%. So PQLs have a 2.5x higher conversion rate. And to me, that's one of the most fundamentally important metrics for any freemium model.

I mean, look, Ray, that PQL to close rate or PQL to customer rate sounds more to me in traditional like sales-led growth, like an opportunity to close rate, right? In my mind, a typical, what I call stage 2 opportunity to close rate runs 15% to 25%. And then MQL to sales accepted opportunity runs at like less than 10%, right? So, and it's the product of those 2 rates that you're comparing, right? You're saying PQL to deal is effectively 10% times 20%, which is 2% in my world. And in your world, you're saying it's 25%. So it's massively more qualified. And yes, I'm a believer in PQLs. I like PQLs. They are a thing. I mean, if you're running this kind of model, it's going to pop something out for sales to go pursue or BDRs to go qualify. And that's a PQL. In the marketing world, right, an SDR pops out an MQL. And in the ABM world, they pop out an AQL. And depending on your model, I think you need all those metrics, and they do have very different conversion rates.

So we're already coming up to our 20 minutes, and this is such a complex, nuanced, and evolving kind of dynamic. Do we have a specific recommendation for our listening audience?

So I have one, Ray. When it comes to CAC, and this is going to be rather conceptual, but I think the most interesting question on this Are these people, I'm just gonna call them, just imagine we have this 2-hop funnel, free to paid, paid enterprise. In that 2-hop funnel, are the people who make the first hop customers or not? Because you can, and the answer to this question ultimately is how much revenue do you get from those people? Because if you get 100% of those people, right? Just say you're Calendly and they probably also do enterprise by now, but just say you're a consumer product where there's just one hop, right? You try it and then you become a customer and you get $100 a year and we're done. Then in that case, there's one hop and it's 100% of your revenue. But imagine the two-hop model where, no, I turn somebody into a solo user at $90 a year and then I eventually sweep all those up and turn them into enterprise deal at $100K. Then I wanna see the revenue distribution across those two modes because the customer count might look something like we have 100,000 customers on the left giving us $100 a year, which is gonna be $10 million. But I have $100 million of enterprise customers over here off maybe, you know, 1,000 customers. So I have a very small number of customers with a very high ASP. And the question is, you ask me churn, if I do it on an account basis, i.e., not a dollar basis, it's a disaster, right? If I count the people on the left as customers, because I'm way overweighted to these teeny micro customers. So I think, Ray, since we're coming up on time, the most interesting question in all this Or are your individual paid users, are they great leads because they convert at a phenomenal rate into opportunities and deals? And rather than costing you money, they actually give you money, right? So are these the world's best leads or are they in fact crappy customers who churn at a, you know, 40% annual rate and give you almost no money? And to me, I always start there. I start at the very top and saying, what do we consider these people? Because by the way, a lot of your behavior will be driven by the answer to that question. If you consider them customers, you will instantly conclude that it's a bad segment because they have a very high churn rate and a very low ASP unless you then step back and say, wait a minute, they're kind of customers because what they actually are are leads because they're feeding the other engine. But I do think a lot of confusion happens in that dichotomy.

I'm pretty— it's not black and white, but I have a pretty strong opinion on this. I recommend 3 financial return models or metrics. Cost per free user, that's a cost per freemium user. Then I go to cost per paid user. So if that freemium user becomes that $90 a year Calendly customer, that's a cost per paid user. And then I do cost per paid customer. And you can say paid corporate customer. And now I have across those 2 hops, 3 segments. I know my cost per freemium user. It's like a cost per lead. I have my cost per user, which is my cost per that initial revenue, then my cost per corporate user once they convert to an enterprise customer.

Got it. I think those are 3 really good metrics. The question is, how do you calculate churn? And I'm guessing your answer is you segment it. So when I ask you what churn is, you're not going to give me a blended rate. You're certainly not going to give me a count-based rate. You're going to look at it by segment.

And by the way, I don't believe in logo count churn anyhow. I believe in GRR, so I'm going to do it on GRR by segment. But that might be a topic for another podcast in the future, Dave.

Yeah, agree, agree. Glad you don't do count-based churn either, Ray. You're a good man.

All right, well, that's a wrap to today. I, I love the conversation, and it really highlights There's just a lot of thought and maturity that needs to go into how do you determine the cost in a PLG model of acquiring a customer, starting with what in the hell is a customer?

Thanks a lot, Ray. Another great episode.

Thanks, Dave. Talk to you next week.

See you next week.

The Metrics Brothers AI, SaaS, and More is a production of the Metrics Brothers Growth and CAC and a member of the Benchmarket 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.

Information, opinions, and recommendations presented are, according to our spouses, probably wrong and provided for information purposes only. This podcast should not be considered professional or, for that matter, unprofessional advice. We disclaim any and all liability for any direct, indirect, indirect, misdirect, incidental, special, ordinary, consequential, inconsequential, or other damages arising out of any use of, or God help you, relies upon the information presented here. Ray Grothreich is based in New York City and available on X @rayreich. Dave Kellogg is based in Silicon Valley and available on X @kelblog. Schedectady, which is French for unspellable, is not our actual production location. Thanks for listening.