a16z Podcast - When Gross Margins Matter

Episode Date: May 11, 2022

Gross margins–which are essentially a company’s revenue from products and services minus the costs to deliver those products and services to customers–are one of the most important financial metrics for any startup and growing business. And yet, figuring out what goes into the “cost” for delivering products and services is not as simple as it may sound, particularly for high-growth software businesses that might use emerging business models or be leveraging new technology. In this episode from June 2020, a16z general partners Martin Casado, David George, and Sarah Wang talk all things gross margins, from early to late stage. Why do gross margins matter? When do they matter during a company’s growth? And how do you use them to plan for the future? The conversation ranges from the nuances of and strategy for calculating margins with things like cloud costs, freemium users, or implementation costs, to the impact margins can have on valuations.

In turbulent times, getting down to the fundamentals of how your business operates is critical. One of the key metrics to understand is gross margins. This week, in an episode from June 2020, A16Z general partners Martin Casado, David George, and Sarah Wang discuss all things gross margins, including what it is, strategies for calculating and defining it as a company matures, and how this one core business metric drives everything from cloud costs to valuations. The content here is for informational purposes only, should not be taken as legal business tax or investment advice or be used to evaluate any investment or security and is not directed

at any investors or potential investors in any A16Z fund. For more details, please see A16Z.com slash disclosures. Hi, and welcome to the A16Z podcast. I'm Amelia. Gross margins, basically a company's revenue for products and services minus the cost spent to deliver that revenue are one of the most important financial metrics in any startup. But figuring out what does and doesn't go into margins, the ideal ratio for a growing business and how this ratio changes from early to later stages of a startup is not as simple as it may sound. So A16Z general partners, Martin Casado, who invests in early stage enterprise startups, and David George, who leads our growth fund, along with Sarah Wang, on the growth investing team, share why margins matter from their vantage

points, as well as how modern software business models and technology shifts are changing the way we think about them. We also briefly touch on how margins can impact valuations. But we begin with why gross margins matter at all, especially as companies mature. The first voice we'll hear is Davids. To us, a later stage company is one that has found the all elusive product market. fit. And the risk that we believe that we're assessing is execution-based risk, right? Not a binary risk of whether the product will work or not when we're doing diligence on a later stage opportunity. Can we take some reasonable stab at what the long-term margin structure looks

like? And do we have some sense of the market, the competitive dynamics, you know, act number two in act number three from a product standpoint, such that we can make some guess as to the persistence of the growth rate for the company over time. So is this something that can grow at very high rates for 10 years? If so, that's the kind of thing that gets us really excited. So I know this might be obvious, but why do high gross margins matter in the first place? Ultimately, as a company gets big, we look for companies that can generate a lot of cash flow. If you have high gross margins that gives you more of your cost structure that you can spend on things like sales and marketing, product engineering, et cetera. So what we typically look for for a software company

is their cash flow margins, right? So this has now gotten a lot easier in the last three or four years because there are more mature software companies in the public markets that are generating meaningful amounts of free cash flow, right? There's a couple different ways that we typically try and figure out the margin structure. One is just benchmarking. So here's a really simple rule of thumb for a company. We typically see software companies that have gross margins of 70 to 80%. Right. And then below that, there's three big buckets of cost items. One is sales and marketing, which I'll circle back to. Two is research and development or product. And then three is what we call GNA, which is overhead functions. As a company gets more and more mature,

what we would typically see in R&D and GNA are like 15% and 10%, respectively. And then we say your sales and marketing expense is typically a function of how fast you're going to grow and your retention rates. And so you combine those three cost buckets with that 70% or 80% gross margin that I referenced earlier. And what that spits out is your long-term profitability. So we can benchmark each of those buckets against companies that are out there and more mature and say what's similar or what's different. And then we can also go deep into the specific company itself that we're assessing and say, hey, where are they at on this right now? What kind of progress have they shown over time? And how much confidence do we have that they

can end up looking like Salesforce in this regard or Atlassian in this regard? regard or not. Right. So it sounds like a perfect formula. Is it quite that precise in real life? No, it's definitely not that precise. I think we way oversimplified it. Every business is different. So I think this is a very important discussion because gross margins is far more applicable to mature businesses and businesses that have very specific cogs. Cogs is cost of goods, which is just like how much it costs for the product that's shipping out the door. And the reason I say that is early on in a startup, sometimes it's hard to know how much of your cogs is core infrastructure.

And so there's always this blurry line between what is effort that's going into building the product that's non-variable versus what is customer-specific but still looks like R&D versus what is core infrastructure. I've actually got an example or a quick story from my earlier investing days on to illustrate that point and also kind of highlight a mistake that we made. So I think there's a tendency to categorize things like software licenses in R&D, sometimes GNA. But I looked at a company that actually needed these software licenses for their product to be deployed. So this is literally the definition of a variable cost to serve. But both the company and our team, we categorize this as R&D. And so it not only led to gross margins being off by five to 10 percent, but also as you think about modeling your

business forward and sort of the expenses that you're going to need, R&D typically doesn't grow with revenue. It's more of a fixed cost. But, you know, this is software licenses deploy your product obviously is completely variable. So you get into danger of double overestimating your mid-to-long-term profitability, which also has implications for how much you can spend or how much you're budgeting, maybe not for this year if you're still earlier stage, but over the next couple of years. as you move the business toward longer-term profitability.

As companies think through what that looks like, I think it does start with that first layer of, hey, what does it actually cost to deliver this revenue? Although I would agree with Martine that obsessing about it early on when there is going to be likely a drastic change as the business matures is not the right thing to do. Gross margins of companies often change dramatically over the life cycle of the company. So just because a company early in its life cycle has low gross margins

doesn't mean that it will have low gross margins forever. So one of the classic examples of this is Workday when they were going public because services, their implementations were quite large. Each deal was a million bucks or more. The implementation cost was a large proportion of their revenue. And so they actually had 40% gross margins. And fast forward to today when it's a little bit more mature,

they have 70% plus gross margins and look much more like a traditional software company. So I actually think this is great because I think these are kind of like broad situations that kind of clearly illustrate this tension between, you know, or at least the misunderstanding of what gross margin is going to pencil out over time. And that is R&D and it is cloud cost. So why do those two buckets matter? Can you break that down for us, Martine?

So the R&D early on, you just don't know what is going to be fixed and what is going to be variable. I mean, now, maybe in some products, you know, you can have a fixed number of R&D. And by the way, I'll say, I've never seen R&D actually be a fixed cost, actually. It's always ever. It's a fair point. I mean, like, just for example, so, you know, I ran, you know, a $600 million, you know, global business. And I would say 40% of our costs were maintenance costs, right? And then we kept growing R&D in order to expand sales.

And so it's not linear. It's not super linear, but there was definitely a sublinear component. And even though like everybody, we didn't really kind of include that in COGS, but also different products just have a different level of R&D required to sell the next thing. You just don't know until you're fairly mature how much R&D you can kind of pull out for a repeatable sale. The next one, which is very interesting, is cloud costs, right? So cloud costs have basically become variable costs. It used to be you'd buy a server and then you'd kind of sweat the server, you know, over a period of time.

And then, you know, you'd buy a new server. But now, basically, for every bit of compute you deliver to a customer, it's likely that you're paying a portion of that to, you know, whatever cloud server costs. And more and more, this is becoming a significant portion of the COGS, right? Particularly in the era of AI and ML where you're compute intensive and data intensive. You just end up spending a lot of money on cloud costs. Now, if you go to an engineer and you say, oh, like, you know, this is a significant portion of our margin.

Can you reduce that? The engineers say, yes, we can likely reduce it. But in this startup world, normally you're going for growth. You're not going for margins. So you've got the board members say, listen, let's go ahead and kind of, let's grow as much as possible. So then the engineers will make decisions that will optimize for feature velocity. They won't optimize for efficiency. And then you're piling that technical debt on for a long period of time.

And then at some point, you know, you have David George or Sarah Wang, and they want to make an investment. And they're like, hey, wait, your margins are terrible, right? And then the startup's like, well, listen, but our, you know, Martine Casado, who is our Series A investor, said go for growth. And now, now you've got this predicament because you don't really know what your cogs are because you weren't actually focused on them. It may be the case that you can reduce them by a lot through smart engineering, but you don't really know. So again, there's this situation where you're in the early stages. Actually understanding gross margins is difficult. If you're focusing on growth, it's even more difficult. And until the later stages, you don't really know how it's going to pencil out.

So what do you do? So like, what are the, how do you not get to the point where a David George is giving you the side eye over your margin structure? He looks at your spreadsheets. But how do you, as a founder, start thinking about this earlier? Is there any way to get ahead of this? I just want to say before Martin answers that question. I am way more polite than the side-eye guy in the investor meetings. I think this is just starting to hit the boardroom recently.

All the boards I'm sitting out, even at the series A and series B, we're actually looking at cloud costs and realizing that, you know, double digits of margin are being contributed to them. And so what I think is happening now, very early on, we actually have the discussion. And the discussion is, you know, this is going to be important once you're larger. We don't want you to make architectural decisions that you can. can't unwork early. We want to understand what is basically a law of margin physics here, which

means you're not going to be able to reduce it versus something that you're taking a shortcut now that you can optimize later. Let's document all of those. And so at least you know that that discussion is going to come. Because I think, you know, as of five years ago, there was just an assumption that it was software and you have 80% margins, even though you're doing these very cloud compute intensive things. At the later stage, kind of looking back at these companies, and as they progress to the next stage in their growth, what do you see or how do you advise companies? First of all, I definitely agree with Martine

that optimizing too much on margins early on doesn't always make sense. And, you know, by the way, by no means do gross margins have to be in steady state by the time you start raising those later stage rounds? That said, you know, I think the ratio of story to results has to have come down by then. Because at the later stage, this is really when the company transitions to more of a show versus tell. At this stage, I think you're going to get a lot of credit for, one, showing that you've demonstrated meaningful margin expansion, regardless of whether it's

at steady state, could still be very far from that. But then also, too, having a credible path to what you believe steady state margins will be. Some of this is going to be very well trodden. So cloud cost optimization, economies of scale. And then there's other ones that are more specific to just your business. Regardless, having a very tangible roadmap, is going to be extremely valuable at this stage. Right. From a startup standpoint, it's very difficult to predict how much of the work that you're doing is actually repeatable.

Until you've talked with a whole bunch of customers, it may be the case that after you've served as 10 customers, you've kind of tempered the product enough that it's fully repeatable and then the amount of implementation required goes down for a customer, but it actually may not be the case, you know, notoriously in management, then number of systems you've got to connect to is this very, very, very long tail, and that just ends up being part of your cogs. And actually, we can go through a number of examples in early companies of why you don't

really know what the cogs are going to pencil out. So let's say if you had a company that was basically contract engineering, which means for every new customer, you had your engineers built new features. That's clearly a very low gross margin business because as part of your cogs is engineering, right? Now, if you go kind of a little further towards a pure software model, like maybe there is some scripting that needs to be done for like connectors. So, like, there's a number of companies where they're like, you listen, you know, we've got a core platform, but you may have some special systems we integrate with.

That's actually, we'll do that, you know, for you. It turns out in the industry, there's a long tail of those. And so there's, this isn't core engineering, but it is kind of scripting and connectors, but that's part of the cogs, right? And then, you know, you go a little further. Maybe there's just some basic configuration and implementation and it needs to be done. It's not actually development. It's not actually scripting. It's like, you know, actually just dealing with config files.

That's lower cogs. And then, you know, in some models, like maybe there's nothing that you have. have to do. And that would be kind of the highest gross margins. There are many cases where even if it's not core R&D, but it is some sort of scripting or some sort of integration, it's simply something that you're going to have to pay per customer. Okay. So we've covered how margins can be messy and how they evolve over the course of a startup's growth. So now let's talk about how modern software companies, particularly SaaS companies, et cetera, are changing how we analyze margins. How did we used to analyze them, and then what is different now? A lot of like original views of gross margin

came from the days of shipping software. And the world is very different. So if you ship software, you have an R&D team, they write software, you put it on a CD, for those of us that remember those. And then you ship that CD and you're done, right? And so what are the characteristics of that? One of those is you're done with features the moment the CD ships. So you don't have like, you know, a lot of feature velocity. The second one is you're not running. it on your own servers, you're running it on a, you know, the customer's servers. And so in those cases, there's things that you don't really think about, like you don't think about like, what is the amount of compute relative to dollars? What is the amount of like data munching relative to

dollars? You're like, listen, I've kind of put these bits on the CD and I don't have to look at it again, and you've got this, you've got this great business. On the other hand, today, almost all software, not all, but so much software is actually delivered as a service. And so there's a couple of things that implement. So you have operating teams that actually manage the operations like the care and feeding in that service, right? In order to deliver it, you need to have those operating teams. That's different. Two, you know, you are paying for the infrastructure and, you know, the efficiency of your software greatly impacts your margin, which you don't really have in the other world.

Right. Three, there's no reason why you can't have featured velocity that will absolutely increase that your customer base. because the amount of features that are dropping will unlock new markets, which, you know, is going to have a hand on your growth. And so that's why this is very interesting because we are at such an inflection point with SaaS and with infrastructure. The one fundamental business model change that's a huge benefit that's come along with this trend has been recurring revenue versus one-time sales. Right? I mean, think about that. Like the quality of being able to collect your revenue on an ongoing basis as opposed to just selling a disk once and being done with it. Yeah, you know, yeah,

you'd have 20% maintenance per year. But now all of your revenue being in the form of subscription is just such a tremendous advantage. And I think that's part of the reason why software companies have been valued so much higher than they were historically. Why is having your revenue in the form of subscription such an advantage when it comes to your margins and valuation? So one of the big advantages of subscription business models is that they add, predictability to your revenue stream. For every dollar of cogs or sales and marketing that you're spending today, you know how much they're going to bring in not only today or this year, but actually also next year and the year after that. If you think about it, company management are actually

the real ultimate investors because you are deciding at every single moment, what is the highest value added place that you can invest your resources, your time, your energy, and the money that you've raised. And this predictability of your revenue stream makes it easier to optimize for your margin because one, you know what you're spending and then two, ultimately what will net you from a dollar perspective. Obviously, strong retention goes hand in hand with this. And, you know, in terms of valuation, fundamentally when businesses are trading on high revenue multiples, you hear a lot of that in the press, what does that actually mean? The fundamental underlying reason is that the markets believe the company can grow in the long term with steady cash flows.

And when businesses have this high retention in a subscription business, companies can trade at these higher multiples because investors have the conviction in the consistency of both their long-term growth and their long-term margin. That's really interesting because, one, you know, external investors can see predictability. But two, the internal operators, the management team, can also see predictability. and then they can make better decisions. So it has a sort of two-fold advantage. Absolutely. If you think about it,

if you think about a founder or management team as an investor, you know, when you put that engineer or that dollar of, you know, the equity that you've raised into a particular line of the business, does that get you 50 cents one time? Or is that something that's bringing you a dollar and a half, you know, for the next five years?

And that's going to influence where you're going to invest. again, your time, resources, and money. I actually have one more sort of nuance around gross margins that's emerged from yet another kind of new type of business, which is businesses with a freemium component. So this is really only emerged probably in the last, I don't know, eight, ten years or so. But for companies that have a freemium component, so a big user base that they're not actually monetizing, but ostensibly can in the future be monetized. We've seen varying approaches of how to treat the cost of serving those. Some people put it up in cost of goods sold. Some people put it in

sales and marketing. What we've been telling our companies is, hey, look, this is basically, the whole reason you have this premium line of business is as sort of legion for customers that you can monetize. So we would like to see that cost of service go down into the sales and marketing line as opposed to in the COGS line. So Slack obviously has this dynamic and they keep it in their sales and marketing line. And so they have very high gross margins. In contrast, when Dropbox went public, they actually had it in their cost of goods sold. And it kind of confused investors. So what we've been telling our companies that have this dynamic is, hey, very clearly call out this component, be strict about how you define it, but put it in sales and market.

marketing. Right. So another common line item is implementation and services. So how do you think about that component? So one of the things that I typically see when a company is in the process of going from kind of early stage and trying to validate that customers actually want what they're selling to making it a repeatable process is there's often gross margin leakage or like inefficient gross gross margin in the pricing that gets attached to implementation or the services associated with selling the software. So if you've got three months of implementation work that needs to be done, oftentimes an early stage company is in the habit of just saying like,

okay, these are my first few customers. I have to make sure it works. I don't want to charge them for this or I want a way undercharge them for this just to make sure they're happy. And then as you scale that up, that's sort of a hard cycle to break out of. And so you'll often, at least I've often seen a bunch of companies that are sort of call it like in the 10 to 20 million of ARR range, they have what we would characterize in late stage world like software like gross margins for the software piece of what they sell. But they're losing a bunch of money on implementation, which is dragging down their overall cost. To me, that's something that can be fixed. It also, you know, you know, if you can kind of boil it down into simple terms, it's kind of priced also, right?

I think this is such an important point that kind of harkens back what we're talking about previously, which is it is not clear to me that implementation can always be fixed. This is where I think a lot of funny games get played in this area, which is there are some products

that when they get mapped into a customer environment, they're mapping onto a very, very fat, long-tailed interface. Right? And it's integration with systems, it's dealing with legacy systems it's maybe a bunch of data work that's happening and it's tempting to be like oh we just haven't waived the magic software wand enough to make this repeatable and in some cases you can do that but in other cases that's just too long-tailed and too complex and too eclectic and you just end up with a lower margin business and it's actually inherent in the product market fit and so i think it's great that you brought that up david because i agree 100% with what you're saying The only thing I would like to point out is that I think we like to will away complexity, and you can't always do that. Yeah, I totally agree.

As you scale up, it makes sense to charge for that complexity, right? 100%. Exactly. Charge an amount that, like, hey, you're not going to lose a ton of money when you're going through this painful process with the customer. And, oh, by the way, if you go through that painful process and it's a really tough services challenge, right? Again, this is exactly like workday that we were talking about earlier, right?

Like, it is a huge cumbersome implementation process, but like that just makes your software so much stickier once it gets in, right? The point I would make is like, just charge for it, right? I know that it's easy to say. I think you're absolutely right. I think it's a very critical point. And I just think it means that if you're running your business, don't delude yourself to the true nature of the problem.

Because sometimes I feel we're like, oh, we just haven't focused on that, which is why it's complex. Oh, if I just put a couple engineers, that will go away. And I'm telling you that's sometimes not the case. A very, very classic market segment for this is ETL. It just turns out data is messy. And you have lots of data sources. And it doesn't matter how magical your product is. It's going to require a lot of implementation. And so you're far better as a founder to just like acknowledge that to David's point, you know, suck it up and charge for it. And make sure that's part of of your business, rather than kind of hold on to this hope that somehow you're going to address it in the product, because it just may not happen. What about emerging new technologies? Like, for

example, A.I. and M. How should those founders think about managing their margins over time? So, you know, it's not clear to me that if you look at, you know, what we broadly consider AIML companies, that they even have the same margin structure as SaaS. And I think there's two reasons for this. One of them is fundamentally a technical reason, which is the amount of computation and data handling costs actually increase over time. In traditional software development, you know, you do the software and then you can optimize it. And then the cost per compute over time reduces because, you know, the cost of chips get cheaper. The cost of servers get cheaper. The cost of class service gets cheaper, you know, et cetera, et cetera.

And there's also a finite amount of work to do that you can optimize. In AI and ML, the accuracy of your solution is dependent on the amount of data, and the amount of data required increases. And so it's not clear you can actually get the same levels of cost deficiencies. Because in order to improve your product, you may need to deal with 10 times more data. And to improve it again, maybe 100 times more data. So the tail of complexity in the problem domain is just quite a bit different. And you actually see this. Like if you have two companies that trying to do, let's say, some sort of a vision application. Let's say there's two companies that are building drones that identify crops. You know, one that's been doing it for a very long

time, maybe have 96% accuracy. And one that's been doing it for maybe, you know, far less time, we'll have like 90% accuracy. So getting to those extra bits of accuracy requires much more investment, you know, the more accuracy you get, which means that you'll always be kind of fighting this kind of data management accuracy game. And that fight will get hard. as you get as you go along. It doesn't actually get better. The second reason is, and this is a bit more of a difficult one to describe, but I'm going to try to do it in the general way, which is sometimes we see AIML companies basically taking

operational costs from their customers and internalizing it. So it's almost it's almost the exact opposite. So I'll give you an example. Let's say that I'm building my AIML company that automates, you know, filling in entries, you know, data entry. That's what I say. I go to a customer, I'm like, you have all of these people that do data entry. I'm going to automate it for you, right? So the customer's like, that's fantastic. I get to take this kind of variable cost of data entry off of our books. You do it. And then if you actually look at what the startup is doing, it's actually just, you know, internalize this variable cost. And it does require some humans to do it, not all of it's automated. And it still has the data handling the AWS cost, et cetera, et cetera, et cetera. And so, you know, even though they've got like good growth and good revenue and good customers, the reason they haven't is they've basically taken somebody else's operational. operational costs and put it on their books.

And the nature of these problems to the first point is you can't always make that go away. It may be an increasing operational cost, even if you have software doing it as opposed to humans or software-aided with humans. It still is, you know, maybe, you know, it'll still impact your margins. So we're not sure. I'm personally not sure if these AIML companies have the same margin structure and software. And there's definitely a range of them. But I think we're seeing them to be lower. And of the boards that I'm on, we see 50% margins to be pretty standard for this class of company that's really reliant on data, for example, in order to create a solution.

And I think that actually gets to one of the underlying anxieties around margins, which is if you have software-like margins, then you also expect that you should get software-like valuations. And I think this is part of why people get hung up on, well, I can't have all these services because I need to be able to have like those 70, 80% margins. And so can we talk a little bit about how y'all think about valuations when maybe the traditional, like, 75% software margin, therefore you get software multiples. Like, does that still hold true in these scenarios? I think the first principle's way of answering, you know, I think maybe the question you asked Amelia, which is why do gross margins matter? You know, a little bit tongue in cheek here, but I actually think they don't matter per se. What really matters is the return on invested capital that a business generates. For practical purposes, it's often easier to build a higher return on capital if you have a higher gross margin

because you have more points to reinvest back in your business, whether that's product or sales and marketing. But there are a lot of low gross margin businesses with a deep moat that can generate very high returns on invested capital. And it really is at the end of the day, you know, how are you building a durable, competitive advantage that, you know, makes the particular service or product you provide indispensable and irreplicable to the value chain? And by the way, the interesting thing is oftentimes those companies do have pricing power to sort of tie it back. You know, not only do you maybe start charging for implementation, but we see a lot of companies as they build that brand or that moat start to actually charge more for the software or if they're a marketplace, maybe it's the take rate, especially in something like vertical software where you can have, you can build relatively high market share. Yeah, there's maybe one example to like bring this to life, right? because these companies are highly interrelated with one another. So Alphabet or Google is one of the best companies, I would say,

if you were to ask just what are the best companies out there in terms of competitive depreciation and modes and defensibility, Google is high on the list. They have 55% gross margins. Contrast it with a company, also a very high-quality company, but I think few would argue a better company, like booking or Expedia and those companies have 90% gross margins right but they actually pay a massive tax to Google themselves you know booking and Expedia are actually the largest customers

of Google so like I think that's an easy way to see it of like in that specific example like where does the power lie like it lies with the business with much lower gross margins than the company with with higher gross margins one thing that that I wanted to just add is I think this conversation has been very focused on enterprise SaaS. And so a lot of this may be more directly applicable to that. And, you know, I do want to recognize that if you do take something more like a marketplace model, you know, I think we have seen a lot of businesses successfully take gross margins much higher because the play there is really to, it's, you know, it's a winner take all market. The play is really to grab

market share in the early days that may be through lower price and depressed gross margins. But then expand as they do become, you know, the winner in that market. And so I do want to pay homage to that because, you know, I think a lot of this when we're talking about 70, 80, 85 percent gross margins doesn't really apply there. But that by no means, means that those are not good businesses or, you know, again, generate high return on invest capital. Do, do marketplace businesses need to think about the same cost centers as more enterprise companies? Do they have the same considerations for their long-term margin structure? Or do you see that they have some very different? considerations. I think for both marketplaces and more of these enterprise software and infrastructure

companies, there's definitely a couple of shared cost centers. So if you think about, we mentioned customer support being one of them. That's very much a part of both. But overall, I think that the cost centers can often look very different. And your long term margin structure for both types of companies, but especially in these marketplaces, is a product of the defensibility of the moats that you're building in the business. And I think, the note that I'd add about marketplaces is that we know it takes a really long time to build and oftentimes scale is really the name of the game. And so marketplaces can underpriced for a long time to build this, which weighs very heavily on their gross margins. And so what investors will

do is look through what your current margin is in a marketplace that is being built and start looking for the indicators that you've built those network effects. Are your cohorts of customers retaining at higher percentages than the earlier ones because you've built that density in your marketplace. Are you creating a dynamic that becomes winner take all? And only when you become winner take all, do those margins actually start to trend towards steady state? You know, there are, I think at that scale, you see examples of what sustainable gross margins

look like in similar businesses. And marketplaces will often get a lot of credit in between getting to that point. If they've been able to show some of these network effects and other signs, of moats that they are building along the way. Yeah. So it's, it's sort of the same, some of the same points you talked about earlier where there's a bit of show and tell, just like with, you know, the enterprise companies, right? Absolutely. Because, you know, if you think about what ways on, I mean, there's, there's several layers to think about in a marketplace. Um, oftentimes, you know, if you're, if you are aggregating certain end markets, right? Whether that's houses for rent or

a labor marketplace. So it's, it's people. The first layer of cost is actually what are you paying out to the Airbnb hosts or what are you paying out to the laborers? There's obviously cost buckets that are layered under there. But initially in early days to build that scale and to differentiate from the incumbents in the market that maybe don't have a marketplace structure and don't have this technology supporting, you know, building a broader marketplace, then, you know, you often do see lower gross margins. In fact, we sometimes see negative gross margins for these companies. To make them bad companies, absolutely not. And how do you get to, at the later stage, that belief of, hey, you can hit a steady state that is sustainable, that will generate cash in the long term. Well, it's really showing these proof points along the way of the moat that you're building to become the winner in the sector.

Right. Are there any other, like, very practical pieces of advice that you want to make sure founders know and hear and internalize? I really believe that companies go through three stages. It's the product stage, the sales stage, and then the operation stage. And the product stage is you're finding product market fit, and that can take years, and many companies don't actually do it. And then you have to get to a repeatable sale. So let's say you found that you get to repeatable sale,

and then you focus on sales expansion, repeatability, etc. And then operations is where you're actually working on, like, really focus on margin in economics because, you know, now your later stages and it really matters kind of like the hygiene of your business, just so, you know, to Sarah's points earlier, you know, like how much cash you have to invest in the business. So that said, if you're in the product phase or the sales phase, I just wouldn't worry too much about gross margins, A, because I think it is kind of unknowable. Like, you don't really know where things are going to land. It's much, much more important to David George's

point to actually get a business that works than to kind of over-optimize it before it works. And so I wouldn't spend too much time obsessing about it. That said, we've talked a lot about these pitfalls that you can run into later on. So be conscious and cognizant of them, have the discussion with your technical team, have the discussion with the business team as far as how you're structuring things and then don't delude yourself. And I think, you know, all that in, you know, you will not trip up by focusing too much of it, but be prepared once you get to maturity. Well, thank you all for joining us on the A16D podcast.