Live from SaaStr Europa 2023: Cantina Stage - Wednesday

Good morning. How are you? Very— this is a reasonably exciting turnout. I was going to make some sort of comment about sort of, you know, some sort of joke about the state of the venturescape, the obvious elephant in the room, but having had a lot of conversation over the past couple of days, I think it's actually a more helpful a reminder that men over the age of 30 shouldn't play football. So that's just sort of to get that out of the way. I'm very, very impressed because it's 9:30 on the second day. I'm sure you had a long and intense day yesterday, and I'm sure you probably had a couple of good after-parties. So you showed up for a talk on revenue quality at 9:30. It's pretty impressive. I'm gonna try to— it sounds pretty abstract, so I'm gonna try to be really concrete about it. I think ideally at the end of the next 10, 15 or so minutes, you'll have an understanding and framework what VCs look at these days, basically, when they're looking at revenue beyond obviously the top line, an actionable way to, you know, look at your own revenue ahead of a fundraise or, you know, just intermittently, and also a couple of benchmarks. So that's sort of the broad outline, and then we can do a bit of Q&A. Yeah, that's the full title of the talk. But maybe before I dive in, just like a couple of minutes, who am I, who are we? My name's Fred. I'm a partner at Speedinvest. We're a pan-European early-stage venture firm. So we've been around for about a decade or so. We've invested in, I think that number is almost close to 300 companies. We usually come in super, super early, and then we follow these companies almost all the way, right? And maybe one thing that sort of differentiates us, we have 6 teams as sort of like verticalized teams. And one of those teams is SaaS and infra. I'm partner on that team and that's why I'm here. And then, you know, sort of obligatory logo slide. We've done a huge number of SaaS investments over the years. The way we tend to look at, you know, cloud software generally is basically sort of, let's call them the modern building blocks, the modern software building blocks. of, of companies, right? So we start at the very top of the, like, application stack, um, the sort of what we call the application layer. And then we invest all the way down through the API layer into anything that you might need to build, ship, uh, or secure software, right? So that's just, that's just a small amount of background before we dive in. Now, it's been a reasonably tough year for fundraising. I think there was another report published 2 days ago or so from Carta. But if you're Googling, there's all sorts of numbers out there. I think the, the fundamental headline here is that VC dollars have not quite dried up, but especially at the later stages, um, it's— it have really come down, right? And I think everyone knows this here, this won't be new to anyone, but like one of the takeaways of that is good fundamentals matter again, right? That's sort of the whole premise of, of, um, uh, why, why you're here, I'd imagine. Um, and yeah, just as an additional data point, and I just realized that that should be '23, not '22, but if you look at the publics, which is ultimately where, you know, hopefully most companies, or at least a lot of companies, aspire to be in the long run, um, public market multiples for cloud software have declined quite sharply, and that's also trickled down into private markets. So what we basically did as early-stage investors, we, you know, our job is to give advice to our portfolio companies and help them navigate, you know, when they come up for Series A, B, and partially C, what's going to be expected. So what we did is we did this big outreach, you know, in our network with our founders, portfolio founders, friendly founders, and, you know, all the sort of downstream fund relationships that we have. And we asked around, you know, what actually are the sort of most common pass reasons from Series B? And somewhat astonishingly, they're not that changed. People will tell you quite similar things. They'll tell you, "Well, high monthly gross churn, low year-over-year revenue growth, so CAC payback, poor margins." Everything that's on here, and obviously this whole plethora of other reasons, cap table, team, market size, you name it. All the stuff that's sort of standard. So we were like, "Okay, well, it's a bit dissatisfactory as an answer, and it's also not particularly actionable." So we were like, "Okay, well, what are investors really looking for?" And this is where we get to the meat of this talk. Don't be overwhelmed. It's a lot of bubbles. The Sweet Invest revenue quality framework. I originally published this as a blog post, and this is sort of the expanded version on it. I will go through this bit by bit, so— and the slides will be online somewhere, so don't worry about that too much. But maybe just as a really, really high level, essentially there's a spectrum of qualitative to quantitative ways to look at your revenue, some less comparable, some more comparable, and then the color of the bubbles is just sort of like how often that reason was cited by people that we interviewed. So the sort of like more darker bubbles tend to be more core, they come up more often from the funds that we talked to, and maybe the lighter ones are slightly more esoteric. But I'll go through these sort of like, you know, the spectrum one by one now, and then hopefully that will sort of like drive home the point that I'm trying to make here. So let's dive in. The qualitative. Not all revenue is created equal. I think if there's sort of one thing to take away from this slide, and actually, probably more broadly most of this talk, it's that when a fund looks at your business, any revenue you have is treated as a proxy for product-market fit, latent demand, and expectations of future revenue. And as such, not all dollars are created equal, right? So like for like, they can be weighted or discounted differently. And on the very, very qualitative side, there's sort of like two broad things that funds will look at: your customer types and your contract terms. I think the contract terms are more obvious, so I'll start with the customer types. This is really about, you know, who are you selling to? And it, it sounds so trivial, but it really, it really does matter, right? If you are selling exclusively to early-stage companies, let's say you have a PLG go-to-market motion, a lot of your customers are sort of seed-stage companies, well, it's just kind of implied that there will probably be higher churn, you know, they'll be more likely to die, they'll run out of money. And so that's just, and also maybe it'll be harder to convert them into like larger baskets. Whereas if you're selling to more late-stage companies, you know, there are other implications that come along with that. But for example, the churn might be lower. So this is sort of just more like, okay, what's the clustering of like, what are these customer types? The second part is departments. This is something we see a lot with enterprise go-to-market motions. If you're selling into innovation departments, you know, there's less signal in that because ultimately the job of an innovation department is to bring new software into the org and test it. So it might be a lot easier to, you know, convert someone, but it's much harder to expand that basket down the line. Whereas if you're selling into a business unit or someone who owns a P&L responsibility and you are helping them directly either increase their top line or reduce their cost base, there's like more signal in, you know, in, in that problem that you're solving, that that problem is large. And so that dollar may be weighed more highly. Sectors is a similar, similar factor. This is almost like a risk analysis. I think a common example that we saw, especially in Europe, was if you are selling to like, um, exclusively like European high-end, like heavy industry manufacturing, like, and the energy prices shoot up, all of a sudden it's really hard to sell software, right? And it's just, if that's all your business like, is that sort of like sector, that is a risk factor. Similarly, if you're selling— another example, um, HR software to, you know, scale-ups or tech companies, and there's a hiring freeze, that might be— it might be harder to, to take that to market. So again, like, this is just a, like, a way to look at, um, sort of what your, uh, what sectors you're selling to and sort of how that's, um, how that's weighted. And then the last one is strategic interest. This can sort of swing both ways. There might be good strategic interest in sort of you selling to someone, and, you know, that gives you a data mode, for example, because it gives you unique access to some sort of data set, and that revenue might actually be valued more highly. Or you might be selling to someone where you are, you know, you have fundamentally long-term incompatible interests with that corporate, and they're kind of using you as a stopgap to figure out how they build it in-house, and then they'll rip you out. And like, these are all things that like, you know, a good VC will look at on a purely qualitative side when assessing the dollar value of your contracts. And then the second one is contract terms. I think this is pretty obvious, you know. Is this one-off revenue? Is it recurrent? Okay, check. I think then the duration, I think many of you will know this. Is this like a monthly, yearly, or, you know, some companies sell like multi-year contract. And there's obviously once again, there's some, some of it is just the nature of your industry, but some of it might be sort of like, you know, clearly just a sign that there's a pressing need and they're willing to commit to like a multi-year contract. And then it's a bit of like a working capital, you know, implications on that as well. And similarly, if you're having pilots, proof of concepts that are milestone attached, that might be weighed a lot lower than sort of like a recurring proper contract that's gone through central procurement. And lastly, the delivery model. I think this is more like, obviously this factors into gross margins and stuff we'll get to in a second, in a second, but I think it's just good also for yourself to understand, okay, what actually is the service component and onboarding on this sale? Because you can always kind of hide some of the, like, you know, customer success and some of the onboarding further down in the P&L. But ultimately it's about understanding, no, what is my go-to-market motion, right? And again, this sort of influence, if your baskets are really, really small, but you have a huge amount of service component that you can't price, then that might be a problem, right? And so if you were to take away one thing from all of this, the first part, the qualitative, it's really that not all revenue is created equal, and the dollar will be judged to assess your amount of product-market fit you have, the latent demand that is in your— that your product has in your industry, and what the expectations of future revenue based on this R. That's sort of the first bit. If we're moving on from here, there's what I would call the sort of liminal space between qualitative and quantitative. And this is like, you know, throwback to college, Stats 101, the descriptive statistics of your customer base. So I think the stuff on the right is sort of fairly obvious. Obviously, like margin structure, like you should have a good understanding of your margin structure. Software gross margins, probably one of the most commonly talked about topics here. And then I drew the little box plot underneath on sort of revenue concentration. I think this is another thing just to have a good understanding and be able to control your narrative around is like, okay, how much of your revenue actually comes from what amount of customers? And there's no good or bad necessarily, but if like 80% of your revenue is from 2 customers, you probably should have a good story why that is and how you can actually get to more customers like that, right? And so it's, once again, it's just one of those things. It's like, it's just giving you a lens, or like showing you the lens that funds might use so that you can kind of preempt that and control this narrative, right? And then I put customer engagement on here, which I think will be like maybe unintuitive when you talk about revenue quality, but I think it's very much like core, because ultimately the engagement that your customers have on your product is the strongest predictor and earliest predictor of churn and upsell, right? So the key question you have to ask yourself is, are my customers, are my champions behaving in a way that I would expect them to, right? Like, what is the intended behavior of my product? And if the intended behavior of, you know, you're selling a software product and like they should be logging in every morning at 9:00 AM to check it because that should be the workflow, And they're not doing that, there's probably something wrong. And so there's no hard and fast rules. And these metrics I put on there, active users and so forth, they are important. There are the numbers of users that log in and the number of users that log in over a certain time. And then power users, you can define as you want how often they log in or whatever challenge they go through, whatever. Product interaction they achieve, but ultimately what it comes down to is what is the intended behavior of my product if used exactly as I had planned it? And then I wanna look at the engagement sort of against that. And if that works, it's just a good understanding of like, is this a sale that happened and then no one ever used the product, or is this a sale that happened and is currently solving someone's like hair on fire problem, right? So this is sort of the second part, the liminal space between the qualitative and the quantitative. And it's, to summarize, basically it's an added lens that you have to have a few more vantage points onto how high quality your revenue is and how people will judge it. Um, okay, so that was quite a lot of information. There's one sort of third piece to it, and this is almost like always the most contentious. Well, I'm sure we'll have some questions around it, but it's, uh, because we're moving into the, the quantitative part, which is sort of the part that almost gets— I think the first two parts are really, really important because they don't get as much airplay because it's not as easy to you know, compare them and to talk about them. Whereas the quantitative part is very easy to be like, oh, your X multiple should be this and that. So before I even go to the next slide, I'm going to like preface this by saying, you know, with all, with all, with all the quantitative metrics, A, don't look at them in isolation. If you're optimizing for just one of these metrics, there's a high chance you're actually going to have adverse outcomes. And then the second one is, especially with ratios, by definition, a ratio has a nominator and a denominator. So like, it's very possible that you're obfuscating the actual underlying problem if you're optimizing that ratio, just like mathematically. So it's all that said and done, I'm going to go through them and then, I mean, we can have a Q&A at the end, right? So let's, let's jump in. Good morning, Mr. Sachs. So there are 5, and I don't know why the slide shifted. There are 5 fundamental, like, I'd say there's 4, and then there's one that I thought was funny. There are 4, like, what I would call the most important sort of, like, quantitative metrics. And I think the first one is obviously growth. Any VC who tells you that they're not looking at growth at any stage is lying. They just are. It's just, it's the thing that matters most. It's how the fund IRR is generated. It comes down to the basic economic fundamentals of equity investing that a company needs to grow. And so, and it is also, like, obviously, ceteris paribus, like, it is the primary indicator of product-market fit because it's really hard to grow really fast unless there is product-market fit. Like, you can kind of force it, but you can't fully force it, right? So this is, like, the main thing people will look at, and there's a ton of benchmarks. There's the sort of, you know, usual triple, triple, double, double. I think the later you go, obviously, the numbers change. I think there's a number of good firms. We have a couple of benchmarks that I'll throw up later, but there's a couple of late-stage firms that have done exceptional work in their own portfolio, and you can find all that stuff online. Growth is just important. Secondly, NRR, net revenue retention. I think we are at Sastra. I'm sure all of you know it. You know, it's basically your revenue, but accounting for churn, contraction, and expansion. So it's really a more honest metric looking at how your revenue is growing and behaving over time, factoring in customers churning out and factoring out the efficiency of also your customer success team and your upsells. Those are the two ones. Then there's sales productivity, and there is a gazillion ways in which you can measure sales productivity. I'm not gonna go through all of them, but like, The main point here is to get an understanding of how much you have to spend on sales and marketing in order to generate a dollar of new ARR. That's sort of like the basic of it. And then you can drill that down and basically look at the cost per, I don't know, anything from salesperson to phone call, right? There's people that are much more qualified than me to talk about that in detail. But especially with the value of efficiency having become far more sort of en vogue in the venture world over the past year at this stage, sales productivity as a basic measure of how much you have to spend, how many dollars you have to spend to make a dollar, how much you have to spend, sorry, crucially, how much you have to spend on sales and marketing in order to generate a dollar has become just increasingly important. And then the fourth one, and I think this is why I threw him up here, is the burn multiple. And the burn multiple is a fun one because it's one of those that I think for the years of like '21, or like '20 to '21, whatever, was just entirely forgotten. And then the markets collapsed and everyone was like, All right, the, yeah, burn multiple, that's an important one. And it makes a ton of sense, right? Like it makes a ton of sense to look at how much are you burning in order to generate what amount of new ARR. And that's an objectively helpful way to look at your company. If you're looking at it alongside, you know, all of these other things. And there are tons of benchmark and I think some of them are aggressive and some of them, Some of them are fair. I think the one caveat that I would say is the earlier you are in your journey, and I know this is mostly a later-stage audience, but the earlier you are in the journey, the more you should probably ignore it because ultimately the whole value of venture dollars early in the journey, as opposed to growth dollars, is to invest into R&D, to build product, to then be successful. So the whole point is that you're probably not gonna be particularly efficient, right? Because obviously R&D expenses are factored into the burn multiple. So take it with a grain of salt, but it is, especially if you're at that like, you know, $10 million ARR plus, if you're going from $10 to $20 to $50, whatever, at that point it will just be something people absolutely look at. And then the last one is, yeah, that's more of a bit of a wildcard one, is the hype ratio. I actually forgot who coined it, I believe it was an American venture capitalist, and it's really about the capital raised divided by ARR. So it's just how much did this firm raise and where are they at? And it just sometimes makes for a very fun Crunchbase search if you ever have the time. But maybe that's just VCs who do that. It's just an additional sort of one that I wanted to throw up there. Okay, ton of information for like, 9:30 in the morning. We did briefly talk about what this could look like. Again, do not crucify me, please don't shoot me angry DMs, but we did throw a few benchmarks up on this link. They originally come from a sort of more around the Series A stage, so some of them are more Series A, centric, and then some of it is more applicable. There is a ton of diverging opinions on this stuff, right? And it's all to be taken with a huge, huge grain of salt. I believe there's also, if you want a competing benchmark, I believe ICONIQ, late-stage firm, have done some benchmarking in their own portfolio on their own portfolio data, where they're basically giving you like top quartile and top decile and so forth. So just basically plugging, plugging the competition at all, so much later stage than us, plugging in other firms' stuff here. That's really that. I'm gonna quickly go to the takeaways, and then we can just have an open conversation if anyone has questions. I think there's a mic there. Yeah, I mean, so maybe some key takeaways. A good VC will use a very broad lens, especially now, to access— access is not the word there— assess, to assess your business. And there's no reason why you shouldn't do that as a founder yourself, right? Especially ahead of a fundraise, it's good practice to basically get in the habit of understanding these things, Knowing how you're gonna be judged and basically counter-controlling almost that narrative or preempting that narrative. Now if you look at our framework, and again, the slides will be up and it's also on our blog, we sort of have this spectrum and we try to split it a little bit into qualitative, quantitative, and this liminal in-between space. And the idea really is to have as many tools as possible at your disposal. It's almost like a toolbox that you can use and some of them are more important, some of them are less important. Also crucial to stress, you probably won't excel in every metric, and that's totally fine. And also, once again, it really depends on your stage. If you're earlier in your journey, it is much more normal to spend, you know, more, probably, and be less efficient on your go-to-market motion. All of these things are entirely normal, so you have to, like, use them all together. A lot of the metrics are actually interlinked. Some of them are mathematically interlinked. Obviously, because it depends on how much you're spending and your margins will affect other things and so forth. So makes good sense and is good practice to look at them jointly. And then in combination, if you use them all, you will hopefully have a decent picture on your revenue health. And yeah, I think that's it from me, and I'm happy to open the floor, or you can just have another coffee and enjoy the day. Thank you so much.

Hi.

Good morning. I'm Alon Mason from UserWay.

Can you talk just a bit about how you look at churn metrics as it goes from segmentation from SMB to enterprise customers and what numbers are healthy?

Yeah, yeah, yeah. So I mean, we throw some stuff on the benchmarks. I think in general What I would say is much, much, much more normal to have logo churn if you're more SMB, right? So like, it's just that there will be like a higher churn on average on the logo side. That's just what happens the more you go long tail, right? The more your enterprise logo churn should be more concerning. That's sort of as a broad trend. And in general, I mean, the benchmarks on NRR, your NRR should obviously be above 100. If it's 120, it's great. If it's 140, it's excellent. Those are sort of like the historical historic figures that people use. Once again, use them with a grain of salt, right? But like on average, if you're in a row, it should be— it should obviously be over 100.

So that's sort of—

does that answer the question to some extent? Any takers for any questions? Someone's getting up.

Hi, Heather, founder of a street group SaaS company. On churn, if you know you can make money from customers that you know are highly likely to churn, but are obviously going to impact your churn metrics, would you take them on anyway and just accept that you're going to have higher churn?

So just to repeat the question, because I think it was a bit quiet. So the question—

I can try.

Yeah, if you've got a client who you know is highly likely to churn, we call them bad-fit customers, but you know you will make money from that client because they'll be tied in for 6 months or 12 months, would you still take them knowing that they're going to ultimately impact your churn metrics? Or as a VC, would you take a view on that?

Well, I guess the question is, I mean, ultimately I think you should run your business in order to have a successful business and not please VCs. So I guess the question is, why is that customer likely to churn in the first place, right? And so, like, I wouldn't overly stress on that because at the end of the day, it's more important to understand, like, Okay, why are they likely to churn, and is there something I can do about it? If it's your business model that, like, you know, I don't know what exactly your business is, but like, if in your business model it's just priced in that, like, churn is a certain level, because, like, again, the more we go into consumer, for example, or like consumer-like economics, like, churn is just higher. Well, then I guess that's fine as long as you can make your money back on the acquisition side, and as long as you're growing enough that you're still growing, right? So it's a tricky one. I think ultimately it comes down to the fundamentals of like, what is my product and am I solving a problem and why are they churning? I wouldn't over-optimize for the VC lens. But yeah, if you know that customers, like if you know there's a huge group of customers that will likely churn and you're about to go fundraise, I would probably think about it a little bit. But like, yeah. Is that a vague enough answer?

Hi.

Hi there. A question on sort of revenue quality. Yeah. We currently include implementation and support as part of our, like, total fee for buying the software.

It's not charged separately.

There's interest from our new CS leader in splitting that out and charging for that separately, but still on a recurring basis. Yeah, but without changing the total cost to the customer. So basically taking what we charge today and taking a percentage of that and showing that on an order form or an invoice as a service fee. Yeah. With the idea that they will potentially value that service more as a customer, make better use of that, a more efficient use of that. If there was no change to recurring revenue and no change to gross margin, would you view that any differently looking at that revenue profile from an outside perspective?

So again, like, so I just have to rephrase it and then you tell me if I got that right. Currently you charge an upfront fee for sort of onboarding services and implementation and then you want to split it out? No, we don't, we don't charge separately at all. You don't charge it at all?

No.

So it's included, right? But it's recurring, all of it's recurring. So the total number doesn't change, it's just a different line item.

Exactly.

I mean, doesn't make a huge difference to me. I think if you have some sort of story where you're saying, look, actually, this is a separate business line that we're building out and we think we can increase this business line because we're providing value-added services and it somehow makes sense in your reporting structure and in your hiring structure, then sure. But I think if someone looked at it and previously it was $10 a month and now it's $7 and $3, but they have different names, that makes no difference.

No difference.

Like there needs to be some narrative or some story why that is such. Otherwise it's basically like a— it's just a reporting thing.

Sure.

Yeah, you can shout as well.

That's all right. Just a quick one on the recurring revenue. Just looking at fixed versus usage-based pricing models.

Oh yeah, on that, uh, yeah, yeah, not an expert. I have a few companies going into sort of, um, into usage-based now. It's been, it's been a big, big trend. I think again, you have to kind of pick the pricing that makes sense for your customers first and foremost. So I wouldn't over, overcomplicate it on the optimizing for VC side, right? Like, um, if it's like People will want to understand it a bit better, what the usage is based on, and like, can it literally drop to zero? In most ways, it's set up where it can't. Like, usually it's set up, there is a fixed component, and then there's some amount of usage. And also, there should be some sort of lock-in where, you know, if your product's properly locked in, like, there will be some fluctuation, but it shouldn't drop to zero in most SaaS businesses. I think personally, if it helps you grow your business and if it helps you make your customers happy, then I think usage-based pricing can be the right thing to do. Because it can help with conversion early on. It can help actually increase baskets. It's shown to do that in a few portfolio companies of mine. It will be a bit more of a conversation, but then again, a sophisticated VC should know about it, and it's not like the topic's only been around for 3 months, right? So I would say, if it makes sense, then go for it. We operate in a relative niche, which makes for great capital efficiency economics, but our TAM isn't that great on the flip side. And I'm trying to work out how concerned I should be about people who say, you know, who get quite sniffy about our TAM, saying it's not that big and that guess what you can eventually be.

How do you see that world?

I mean, it's really, really tough because I think in general with TAM, I think people like— it kind of depends what kind of business you're building, right? First and foremost, like, there are investors who are completely comfortable with a smaller TAM because their business model is, you know, they like— they're more like growth equity or more in the private— towards the private equity side where they want to like reliably make a 3x on something. And if you can show you can do that, and it's sort of downside protected, then there's no issue with that necessarily. So it's a little bit, it's a question of talking to the right people. If you're on the super early side and you want to raise traditional venture, you probably have to show in one way or another that the TAM can be expanded. And annoyingly, VCs often overestimate their ability to estimate TAM because A lot of it is TAM expansion that happens over time by virtue of the fact that this business grows. It's actually category creation happening. So it's a little bit a question of what kind of business do you want to build? Do you think there's a credible way for you to build a venture-scale business there by expanding this TAM? And then you just got to tell that story and own it. But obviously there will be people who won't believe it, and that's just part of fundraising and the nature of things. Does that answer the question? I'm not sure what your business is or where you're at, so it makes it hard. We're now multi-multi-million revenue, so we're quite big, but we are within a niche. But I think if you're there and you're capital efficient and you are, I don't know, close to or have visibility on profitability, then there will be funds that find that kind of thing exciting. I guarantee you. They might not look like your typical venture investors because the best way— sorry, it's a bit of a tangent, but the best way to understand it is really understand what are the economics of this fund, right? Are they a $1 billion Series A fund that needs to have every hit have the ability to create like a $3 billion IPO, if that's their business model, then they're probably not the right people to speak to. But there are loads of funds that, you know, have the business model of coming in, holding period 5 years, 3x-ing their money, ideally zero default rate, and then that's their business model, and then they generate good IRR on that. So that could make total sense, right? So it's a bit about who you speak to.

It's just one—

sorry. Yeah, yeah, no, go on. Again, from the merits of—

and it's as much as my selfish shareholder hat on in our eventual exit, um, uh, broadening within your existing market, generating additional revenues by broadening your existing market efficiently versus going to new, particularly geographies where there's a whole risk component, but then suddenly opening up, hey, how big could this be?

It's really tough. It's really something to discuss with your board members, I have to say. But, um, If it came up in my board, I think I would ask, what's our right to win on this expansion, right? Like, are we just picking places on the map because we wanna show some story, or do we have a right to win in that market and a credible reason to do so? As opposed to the broadening, which might be more natural. Really, really hard to give you a carte blanche answer, I'm afraid. All right. Do we have— Any more questions? Otherwise— oh, there's one more. Yeah. So we try and target our sales and marketing spend to be lower than our revenue from sales, from new business sales particularly. Yeah. We fail on that target most years, but we are fairly efficient when it comes to net revenue retention and looking after renewals. Yeah, is there any kind of guidance as to— Oh, yeah, I mean, again, that's kind of the point. That's kind of the thesis of the talk. You have to look at them together. The question, I guess, is, I mean, if I understand you correctly, and I guess it depends what you count into sales and marketing and where your customer success sits and where your AEs sit, but if I understand correctly, what you're saying is, Once you get customers, you're really good at upselling them and they don't churn, but the new acquisition is not quite as efficient as you'd want it to be. Okay, that's the summary. I mean, then you have your answer, right? That's your story. So you've gotta figure out why the new acquisition isn't as efficient, or you gotta make a story that, like, right, we're gonna be a bit slower on new acquisition, but we can calculate our cohorts and actually they look banging, right? And that's the story that you can potentially tell. Ideally, you're great everywhere. No one's great everywhere. It's a conversation. More vagaries and general platitudes. Yeah, I hope it helps. Yes.

All right, question around lifetime value, so payback period, LTV. If you're a company, and we're SaaS companies, say we're 3, 4, 5 years in, you have customers, they haven't really churned, your NRR is above 100, how would you look at modeling your LTV?

Most funds will just take a cutoff. They won't believe you anything above like 2 years, really. Like, I mean, you should have an internal analysis of it.

So even if you have companies that are around for 3, 4 years, you just discount it to 2?

Yeah, I mean, people will eventually— like, maybe they'll take a 3-year lens, but like, it just doesn't really make sense to model it out too much in the future because it just becomes a bit like faffy in their models. So like, a lot of later-stage funds will sort of take a cutoff where they're like, Because realistically, you should have recouped your CAC at that point anyway, right?

Sure, well, yeah, I hope so.

Yeah, so it then becomes more about understanding, so they're happy with that, and then it's more about, okay, how does acquisition look like, right? But I think if you have a 36-month lifetime where you quickly recoup your CAC, I mean, nothing to worry about there. And if you know internally that actually your lifetime is even longer, Excellent. But just take a conservative lens and calculate the lifetime value and see what it looks like on 24 and 36 months. Take those numbers, do the little division with the CAC, see where you're at. If you're still in top-quartile territory, excellent. That's sort of how I would look at it.

Cheers. Thanks.

All right. I might call it here. If you have more questions, I'm kind of limping around, so you'll see me. Pretty easy to find, honestly. And I can't run away either. So, um, thanks so much for your time. Uh, have a great day.

It's Astra.

Please welcome Verdaen's partner, Helaina Svancaar, and Onomondo's VP of Growth, Jennifer Montague.

Alright, hi there everyone. Thanks. Thanks for joining us for some fast and furious 10 minutes. My name is Helena Swanker, and I'm a partner at Verdane, one of Europe's most active growth-stage SaaS investors. And with me on stage today, I have Jennifer Montague from one of our portfolio companies, Onomondo.

Hi, thank you, Helena. So yes, I'm Jennifer Montague. I'm the Vice President of Growth at Onomondo. Onomondo is a Copenhagen-based global cellular connectivity provider. It's quite a mouthful this early in the morning, where we focus particularly on the Internet of Things. As the Vice President of Growth, I have a team of 12, and we work on a variety of initiatives combining both the buyer and the customer journey end-to-end, which I'll talk a little bit more about in today's presentation.

So capital probably used to be your number one growth lever to supercharge your go-to-market strategy. And even in this market, as we, we move beyond that growth at all costs, SaaS is still thriving. And, and, but we cannot deny that the markets have changed. Uh, not only do we see fewer capital raisings globally, but we also see that the amounts have decreased. But nevertheless, companies do want to grow, but you have to balance that growth with profitability. Sorry, I'm moving a bit too fast here with the cursor. But so in today's presentation, we want to go through the top 3 growth levers that we see to supercharge your go-to-market strategy. And Jennifer, please, can you tell us what you see as the number 1? Sorry, it's actually a bit different. Sorry, I'm a bit confused. A bit here with the clicking, so bear with me.

No worries. Thank you very much. So yes, as Selena mentioned, there is a— there was a— we're here. So yes, so what I mentioned earlier, one of the things that we do at Onomondo— let me steal that one, thank you— is that we have kind of reframed the buyer and the customer journey. So a lot of people here are probably familiar with this. If they call it a funnel, you might call it a flywheel, whatever you call it. It is generating awareness and educating the market right and then inspiring some kind of decision. And usually what happens is a traditional marketing team, once they made that decision, it's on to sales, right? And then once sales get that person to sign on the dotted line, it's over to CS. And this disjointed experience for the customer isn't really conducive to creating an advocacy, a customer advocate, and helping that customer throughout the journey. So what we do at Anamondo is we've combined both the buyer and the customer journey. So once that prospect signs that piece of paper, our relationship with them is not over. We are there along with them throughout the purchasing process, throughout the onboarding process. We work with them to, one, make sure they're happy, and two, turn them into advocates so they get on stage and say how wonderful we are. And we do that through focusing on what I call the four pillars of growth. So of course acquisition is a huge part of what we do. We still have to get new customers, right? So we do look at, for example, increasing the amount of customers, increasing the average deal size, reducing the sales cycle to get that velocity of deals going through. But we also look at activation. We want to make sure that our customer gets value out of our product as soon as possible to get them to that wow moment quickly. We also look at retention initiatives. We own the help center, for example. We have video to make the help center more interactive. We have animations and things like that because my team is in a better place to create these assets than say a CS team. Then we also look at expansion. Our business model is based on if our customer grows, we grow. So it's in everyone's interest to help facilitate that expansion for the customer. And the results work pretty well. I don't know if you can see them in the back, but we've seen a 33% average deal size. We've seen a 270% increase in meetings booked. Nearly cut our cost per MQL in half, and our deals are closing twice as fast as an outbound deal. But also with activation, we've doubled new feature adoption through content, educating people on the new features, how to use new features. We do webinars, things of that nature. We've seen that the activation time has decreased by 23%. We've also seen an 18% decrease in churn, and we have around 200 customers on average showing up for our CS webinars that my team runs. And last but definitely not least, we've seen a 30% increase in expansion MRR from existing customers. And so even though we focus— we do a lot of work with acquiring customers, you can see here that 75% of our focus is actually on our existing customers and helping empower them to use the product properly and get the most out of it, turning them into advocates. And they would not be able to do this if they didn't trust us to provide the value that they expect from us.

Thank you, Jen. And in fact— now it's right. In fact, we consider that trust to be the new driver for sustainable growth. And we create that sustainable growth through what we call the Earned Growth Strategy. And that's our second lever of growth today. So let me start with an example here. You might have a customer that in year 1 buys products of you for some $30K. In year, year 2, that adoption increases further, which is obviously great. But not only does that customer buy more products from you, that customer also recommends your products to, to another customer. So all of a sudden, without having spent a single dollar on sales or marketing, you've gained another customer. And that's illustrated in pink here, and that's what we call the, the power of earned growth. So, so the fact that customers advocate for your product, that has an even bigger impact on your revenues because they're lowering in CAC, and they also bring obviously more customers onto your platform. Of course, we also think retention is absolutely, absolutely key to sustain your revenues, but for growth, customer advocacy is really what you should go for. Okay, to create that earned growth, we suggest you ask yourself 3 questions. Number 1, what does customer value look like? Number 2, what is required for the customer to realize value? And thirdly, what does a world-class CX look like? And we think that if you map out the answers to these questions, you really created a powerful earned growth strategy. Okay, that leads us to our third growth pillar for, for a successful growth-to-market strategy, and that's pricing. Let's see if we manage this in, in 2 minutes, but let's give it a go. So, uh, oh, now there is something wrong with the slides. Um, okay.

There we go.

So one of the things that we as an investor see in today's market, that the buyer journey is taking slightly longer in, in many cases today compared to 12 to 18 months ago. And this obviously has an impact on pricing dynamics. A customer that had the big budget before summer 2022 might have no budget today, but you still have to work on your pricing strategy. And focus should then be on really keeping your customers. What is essential to your customer? How can you actually grow them? But then coming back to the power of your own growth strategy, really creating that sort of customer advocacy, we think is, is really important. What do you say, Jennifer? Does that resonate with what you see at Onomondo?

Yes, absolutely. So one of the One of the things that we've approached, obviously, at Anamondo is looking at our pricing strategy, and we do this through data and experimentation. Ultimately, in order for us to make the right decisions, to test and know what we should be testing, you have to really know your customer base. You have to know how they use your product. So we look at how they're obviously using the product and how much they're willing to pay. Obviously, two very important decisions when you're deciding how much to charge people. So we not only ask people, but we also analyze data using a mix tools like Mixpanel and Hotjar within the product to see actually how they are using the product. And then based on those findings, we do a rigorous growth hacking process that involves MVPs, minimal viable tests, that let us get something quick and dirty out the door that is gonna tell us what we need to know. And doing this kind of approach, we've tested messaging, we've tested tiering, we've tested new pricing packages, and we've even tested if colors have an impact. So analyzing the data, asking yourself the right questions, and then you know what to test, and then you know how to iterate and improve upon your pricing strategy to help you grow. So just quickly wrapping up the 3 main takeaways from today's talk, hopefully, that you're walking away with. First is reframing your buyer and customer journey from end to end. So looking not only just at acquiring new customers, but how do you get more value to those customers throughout their journey, and how do you support them throughout the journey to the point where they're excited expanding. Trust is also the new currency, and earned growth is essentially the impact of customer success plus customer experience, which is going to help you lower your CAC and increase your growth. And last but definitely not least, pricing is complex. It's always been complex, and it's even more complex now than ever before. So be customer-centric, know how people use your product, know what it is that they're looking for, measure, test, and iterate upon that to constantly be improving. Thank you so much.

Thank you. We made it in 10 minutes.

Good baby!

Good baby!

[FOREIGN] Please welcome PSG Equities Managing Director, Head of Talent, Corianne van Drimmelen, and PSG Equities Managing Director, Product and Technology, Europe, Anthony Edwards.

You tricked me. Oh wow, nice. Sorry, we were told to talk loudly, so I'll talk loudly.

We should have practiced that one.

Thank you for joining us for this talk, which is all about how to scale up your management team. I'm Antony.

Good morning, and I'm Koriyama.

And we're from PSG, a growth equity firm that has invested in over over 150 scale-ups. So this is a topic very close to our heart, and I love it when technology works. And this is why it should be close to the heart of everyone in this room— every CEO, every CXO of every scale-up. This is a picture we see over and over again. You get a great startup, it grows really quickly, it does really well, and then it hits $10 million, $12 million ARR, and the growth just stops. It goes really flat. And the reason The reason for that is because during that initial growth period, people weren't scaling up their management team. It's the same 3 to 4 people still running the company, still doing everything, and they hit their limit. In the good case, the CEO realizes— someone realizes this, they start rebuilding the management team, and then 18 months later, things get back on track. In the bad case, they don't get back on track. So the point of this talk in the remaining 9 minutes is to tell you what do you need to be doing during that initial period. I was also told not to walk. During that initial period to make sure growth doesn't stop, make sure you can keep scaling. But that's the hard bit. So over to you.

Okay.

So I think the most important words on this slide are, what got you here won't get you there. And it's the there that we need to focus on. So how to do this? Let's think 3 steps. First of all, if you haven't got a plan, which I presume most of you have, create a plan and design explicit goals. Think about experiences and think about capabilities that you need. Then next, think about self. Presuming that most of you have either as a CEO role or C-suite role, it is really important to understand what are my strengths, what are my limitations. I mean, I can even share yesterday we were with a portfolio company. They're really difficult conversations in regards to a merger.

Dutch people.

I'm Dutch, hence I was there too. But it is so emotional. It's not just about the numbers. It is so emotional. You as a leader need to enable people. So that's your biggest involvement as playing a leader. You need to become an enabler. You need to become an enabler of change and a people leader. A people leader, because your future company will be successful if your team is successful. And work together. So number one, future plan. Number two, you as a leader. What are my limitations and what do I need around me in order to deliver the plan in the future? Don't think here, think there. Now we come to the senior leadership team, and everybody is asking, do we have tools? Tools? Can we just use a tool to actually understand what we have in place, what we've got? And we've tried various things, and we keep on being open about various tools, but essentially it's about conversations. It's about coaching conversations. What is your motivation? What is it that you thrive on? What is your strength? And if you do that with the whole team individually, you create a good sense of, are those individual people the people that are going to take the company there? Now we're talking current team. Let us give some examples, because this is with experience, and I'm sure some of you will recognize, but it's good to have it pointed out to you. Essentially, when you get from what is made successful here, you have some people in the team that you will recognize. We're pointing out the two that we come across as, um, a lot. The first one, great individual, truly has met or even exceed all the objectives but doesn't get the support from the rest of the team, his team, her team, or even the wider organization. This is a problem in order to grow the company. Number 2, again, one that we see a lot. It is the person that joined you, or the people that joined you, that helped you to grow emotionally, financially, and those are the hardest ones to let go. But they tend to create layers in the middle, and it stops you growing. As soon as you understand what you've got, there is no right time, but the sooner you start recruiting, the better, because recruiting for good people in your leadership team takes time and a lot of energy. I'll hand you over to Anthony to go through the roles.

It's back to me. So, um, so the key thing from Koryana there is what got you here won't get you there. So when you're thinking about your management team, always be thinking, what are the challenges we're going to have to face next? But what are those challenges? So these are the challenges we see in 90% of cases, and it's really role by role. So for CROs, the key thing is when you really need to start building that sort of sophisticated sales engine, you need to do proper market segmentation, build the ICP, do targeted lead generation campaigns, have a sales process, do forecasts, do pipelining, scrubbing properly. It's also when you need to start doing two things at once. It's not just new business, it's cross-sell, it's worrying about churn, it's selling into multiple geographies, it's all these different things. Most startup CROs are great at new business hustling. They're great at bringing in new deals and just running, running, running. What they're not so great at a lot of the time is stepping back and really managing that sales machine. And that's what you need as you become a scale-up. The ones I've seen who do do it successfully are the ones who, when the business is around $4 to $5 million of ARR, find a good mentor, find someone who's been through the journey before, start adapting their style. They can be successful. For CTOs, it's— look, it's similar. It's when they start having to manage multiple priorities at once. It's, it's when it's about about having multiple products, multiple geographies. It's maybe about having legacy products as well as new innovation. How do I deal with tech debt when I'm dealing with customers, specific customer feedback, but I'm also going after a new segment? Most startup CTOs, we find, they love the MVP. They're all about the MVP. They love burying themselves in and just charging towards it. What they're not so great at is stepping back and again managing responsibilities. The CTOs we've seen be successful, the ones who from 6, 7 million of ARR are able to start delegating. And delegating doesn't just mean bringing in people beneath them. It means bringing in people beside them as well. CTOs pick up a lot of additional responsibilities in startups. They usually run a lot of oper— all the operational stuff ends up with them. Support, professional services, random things. The ones who can bring in people people beside them are the ones who can be successful. Chief product officer, a lot of startups don't have them. A lot of the time that's the CEO. They've had a vision, they're running towards it. Once you get to 10, 12 million of ARR, you need to start placing big bets. What do we do next? Do we go international? Or do we do product diversification within the geographies we're already in? The classic error, certainly in European, especially British startups, is to go to the US too early, and that's often because you don't have that CPO helping guide where's the right place. CHROs, well, most startups just don't have them, so you need one. You're gonna need one when you get to about 50 people. And CFOs, it's M&A that brings it undone. And while I'm on M&A, I do just really want to highlight that because that's the thing that brings most startups, scale-ups undone if they haven't built up that management team. And it's simple. I mean, firstly, integration is hard. It's really hard. But also it means a bunch of these milestones happen all at once. Suddenly you get a bigger team, you get a multi-site team, you're selling into multiple geographies, you have a product portfolio, you have different sort of segments, different ICPs, and how do you manage all that? So if there's one thing you take away from this as well, it's please don't start doing sort big M&A, big integration, until you've built that scale-up management team. And that's really it. If there's 3 takeaways we wanted you to have from this presentation, number 1: when you hit $7 million of ARR, start thinking about becoming a scale-up management team, not a startup management team. Start bringing in new people, start developing the people you have, start thinking about this, or I guarantee your growth is going to stop in a year's time. Number 2, what got you here won't get you there. When you think about the team, I mean, we all know this, it sounds so obvious when I say it, but I bet you when you think about your management team, the first thing you think about is all the great things this person has done for you over the years. Oh, they've been great, they've been— they've done this, they've done that. It's the wrong place to start. You need to start with what do we need to achieve in a year's time, in 2 years' time? What are the skills, what are the behaviors we need in the team. And the third thing is, because a lot of the way I talk, it might sound like I'm saying, hey, you need to ditch your startup team and bring in a whole new scale-up team. That's definitely not what I'm saying. Startup executives can make great scale-up executives, but they've got to think about it. It doesn't happen naturally to any of us. And to do it, you've got to start seeking out mentors, start learning how to delegate, let go of that ego that's making you want to control control everything and become an— as Koyana said— become an enablement-first mindset rather than an action-first person.

Think about the support that you need in order to evolve.

And we're bang on time.

Yes.

That's excellent. So thank you very much.

Thank you very much.

Are we doing questions?

Please welcome Notion Capital's general partner, Joss White, and Notion Capital's principal, Stephanie Optum.

Hey everyone, lovely to be here today. As said, Joss, Stephanie, both from Notion Capital, where we invest in European B2B software companies as well as fintech companies across the different stages. And we're here today to share a few of our observations with you. We collect data from our portfolio companies, from the companies we speak to on a daily basis, but also from our Notion Cloud Challengers Report, which is this annual report we're running where we select the top 100 of early-stage companies that we believe will define tech in the years to come. And what we see happening is that there's actually 4 changes to business models. That used to be ingrained in the SaaS playbook but are now changing in the light of the current difficult environment we find ourselves in, but also a maturing software market. Now, before we dive into some of these business model changes, I'll briefly cover what has been happening in the market. As you can see here on the left-hand side, on the left graph, you see the public SaaS multiples over time. And we all know that COVID has been a massive tailwind for the software adoption worldwide, helped by the abundance of capital available, which kind of really sent the multiples rising. And more recently in the last year, they have come down by quite a bit. Fears of a recession, rising interest rates, possible quantitative tightening, which means that they're now back at levels that were last seen in 2016, stable, stable hovering around that level. But we, we do think it will remain like this for, for the next year or so. And so what is then interesting to see is that most companies raised in 2020, 2021 when the multiples were high. And so now more than ever is it important to grow your revenues very very fast to counter the decline in multiple to— in order to generate at least flat round or even an up round of your last fundraise. And that all at greater cost efficiency. So the investors really are doing a flight to quality at this stage and holding companies to a higher standard.

Thanks, Steph. Hi, everybody. So this is a framework that we use to plot where companies fit in terms of the way that we look at our portfolio and the way we look at the wider market. It's a framework that we've used for some time, but I think it's become more important over the last couple of years. So you can see on the, on the right side, on the, on the high-growth side, this is where we want to be. This is where we want to be investing in companies. This is where startups startups want to be in terms of that venture track, high-growth venture track. But I think what's changed over the last couple of years is it's not just about growth, it's about efficient growth and actually delivering growth in some sort of predictable, efficient way. So looking at metrics like burn multiple, looking at metrics like CAC payback and things like that, so you're actually growing but you're growing in some kind of efficient way. So this is the, the venture track that I think we're all kind of focused on and where we want to be. But if companies are not on the venture track, then this is the, the kind of the valley of death that we talk about. So if you're no longer on the venture track, so growing by more than 100% a year and with, with, with strong metrics in terms of your efficiency, then it's more important than ever that you push push hard towards profitability. That, uh, that means that you're actually able to, to buy time, that you have optionality, uh, in terms of what you're going to do to take the company forwards. It means you're not at the mercy of the markets in terms of having to go out and raise money without the right metrics in place. And so it's the kind of middle ground is really where you really don't want to be. So I think startups need to be realistic about whether they're on the venture track, and that's growth combined with efficiency. And if not, then push hard for, for profitability to give themselves more time and space to regroup and figure out what their— what the best options are moving forwards. So that— I think the framework, the framework that I talked about helps to inform the, the 4 business model changes, or the 4 emerging strategies that we're talking about today. So the first one is the way that, um, sales-driven growth is very much evolving into product-led growth. So product-led growth is something that's been around for a few years, but it really is becoming a much, much more significant, uh, way for SaaS companies to grow and to expand. And one of the main reasons for that is it means that you can reduce your cost of acquisition and you can actually create a more efficient model for growth as opposed to sales-driven growth, which tends to be very much headcount-based. And, you know, you have to— to grow, you have to actually hire more people. So the, the cost of growth is very, you know, um, tied to the number of heads that you have within the sales team. So for the right kind of company, it tends to be companies that operate within SMB and maybe the mid-market, but for the right kind of company, product-led growth is, is, um, is— can be that more kind of efficient model. And we've seen, in terms of the data, we've seen, uh, out of the— in the last 3 years, all the investments that we've made at Notion, nearly 50% have been PLG companies. And you can see on the slide all the public companies now that are predominantly PLG companies are actually outperforming the overall kind of SaaS cohort pretty significantly. And the, uh, the Cloud Challenger Report that Steph mentioned, where we picked the top 100 emerging cloud companies in Europe, 40% of those were PLG companies. You can see that PLG becoming more and more significant as a, as a growth model for And then headcount-driven growth. So when times were— in the boom times and when it was relatively easy to raise money, we had low interest rates and it was relatively easy to raise money, what startups tended to do is to grow by adding headcount. And that was a— it was a model that that, you know, I think the kind of free and easy money environment led to. But I think that the, the, the headcount-driven growth model is now being challenged, um, pretty significantly. And companies will— certainly investors like Notion, but also startups themselves are starting to look much more closely at revenue per head, which is a really good measurement efficiency for a startup. So if you're like a Series A, Series B stage startup, you should be around about $100K per head, and then for a later stage, maybe $150K, $200K per head. The best-performing public SaaS companies are at about $300K or more per head. And so it's to try to, to try to break that relationship between your cost base and your revenue growth and to to find other ways to grow, whether that's PLG or investing in technology, investing in process, rather than just investing in sales-led growth and kind of, you know, headcount-driven growth.

And Joss has been talking a little bit about the cost optimization areas, but pricing is one of the most important commercial levers you can pull to optimize your revenue, and we see some changes there too. So The SaaS subscription model used to be treated as the sacred cow, but in recent years we've really seen the adoption of usage-based pricing where you charge your customers based on how much they utilize the product, which then creates this really nice low barrier of entry for new customers start using your product, but also more heavily monetizes your heavy customer base. The other thing, benefit, is that you can and more optimally align your marginal revenue per customer with that of the marginal cost per customer to create an equal kind of profit opportunity per customer. And so if you look at kind of data from the US, OpenView sees that about 62% of companies have adopted usage-based pricing in some form, growing to 80% over the next 2 years. What we are seeing in our cloud challengers And across our portfolio, about a quarter of companies have adopted what you could call a sweet spot use-based pricing model or a SaaS+ model. And especially in this environment, really recommend you looking into the SaaS+ model where you keep your existing revenue base, but you start layering on these additional revenue streams. Portfolio company of ours, Muse Systems, recently saw actually their usage base revenues overtaking that of the SaaS base, showing the, the scale you can achieve adopting this. Now this is all about optimization of revenue, but if you actually start looking at the quality of revenue, then we find some interesting findings as well, especially when you start considering the cost of sales required to generate that revenue. So you can see on the slide here that a small improvement in your gross margin can actually mean or demand a higher multiple in this market today. And not just that, it obviously has an effect on your bottom line too. So if you then start breaking down those cost of sales, you see that on the one hand you have the professional services. We saw over the last couple of years that professional services could make up 30% of total of total revenue. Now it has come right back down to 10%, and that's the maximum we would allow to see. And then on the other hand, the cloud hosting cost making typically up 40% of a company's IT budget, a small improvement here, i.e., using a broker to adopt a pay-as-you-go model or using cloud optimization spend tools, of which many has popped up, have popped up in the last year or so can really make a meaningful difference.

Um, so on the key takeaways, okay, so just quickly to wrap up, um, I think SaaS, the SaaS business model is, is maturing. I think it's now— that's been accelerated by the current environment that we're in. So, you know, sales-led growth is now often leading— it is turning into product-led growth Companies are looking at their headcount and trying to extract value, extract growth without necessarily adding to the headcount, trying to drive efficiency through technology and process and, and scale. Pricing is becoming a key commercial lever. It's no longer just about fixed subscription pricing but trying to extract more, more value from your, from your pricing model and greater focus not just on revenue but on the quality of that revenue in terms of the, the margins and retention. So, you know, if 2021 was all about revenue and revenue growth, it's now, I think, about revenue, but what sits underneath that revenue in terms of your efficiency, in terms of your margin, and really putting your business on a sustainable track that will appeal to investors right now but also will be sustainable for the long term. Thank you.

Thank you.

Please welcome Next47's partner, Mika Smurthwaite, and Stride VC's principal, Lena Zakharouskaya.

Stand here, right? Cool. Hi, I'm Micah. I'm from Next47. We're a venture firm that invests Series A to C, and prior to this role, I was the first sales hire at Cloudflare, where we scaled revenue from $1 million to over $100 million. Today, the company is at that over a billion in revenue and publicly trades at $25 billion market cap. And while we were successful along the way, now as an investor, my role is to help founders and entrepreneurs avoid the mistakes that we made along the way. So hopefully you get some of those lessons in this talk.

Hi, Saastrs. Lena from Stride VC here. We are an early-stage fund based in London, uh, that invests in B2B and B2C projects at Seed. Before going to venture, I was a head of growth at Secret Escapes, a luxury travel marketplace with over 70 million members globally. So today, 10 lessons on scaling from our times in the trenches. Mic ready?

Let's go.

So the first question you should be asking yourself when you want to ramp up the team, show growth, take a load off of people, is actually do you have the onboarding infrastructure in place to make people productive quickly? At Facebook, an engineer famously ships code into production by the end of their very first day. At Twilio, every new hire, technical or non-technical, learns how to build an app and use Twilio's SMS functionality. Even a scrappy way to do this is just throw your new hires into the the support queue and have them answer support tickets. But as you're scaling and building this onboarding infrastructure, you should track this KPI of how long does it take before somebody becomes productive and use that as your KPI of when to actually scale.

Oh, the leaky buckets. You know, I don't think I've ever seen a business that has a marketing funnel in a perfect shape of the pipe. These drop-offs as you go from acquisition, activation, engagement, and retention, it's inevitable. But the question is, it's one of these where the size does matter. And so if you're signing one new client each week but churning two at the same time, what you have is a leaky bucket. And no matter how big the marketing and sales spend, it's not gonna fix things long-term. And so focus on figuring out the real levers behind your funnel, analyze the biggest drop-offs and what drives it, and create a product experience that can really optimize and deliver the above. And then, you know what, then you're ready to really scale and ramp up your marketing spend.

The common thread of every mishire that I made in an early-stage org was that they came from large organizations and they didn't know how to function in an early-stage org. And I would be seduced by their logos and think, wow, they're coming from Google, Salesforce, they're gonna teach us how the pros do it. But in reality, they would join and say, where are my training videos? Where's marketing to help me with the webinar? And I realized that people who functioned well in a resource-rich organization often were not successful in a resource-constrained organization. So as you're considering your leadership layers, I have a personal bias for promoting from within and hiring someone that can grow into a role, someone that is hungry to prove themselves. But if you do hire externally, make sure that person has worked in a small organization so they can be set up for success.

A little confession, I was a scientist back in the day, and academia, while Well, it might not be the fastest pace of growth. One thing you do learn is the power of the scientific method. And so I'm not suggesting that you need to analyze and measure every single bet that you make inside your business, but mastering that culture of scientific rigor and experimentation and measurement and growth, it can really unlock the returns later on. And so everyone has an opinion, right? A single idea, it's not necessarily good or bad. The key is you need to test and learn because that's the only way to know. So ideate, define a hypothesis, set up your A/B test, measure, and learn. I mean, at Secret Escapes, we used to run 150 creative ad optimizations a week on performance channels only. So building that muscle from really early on, I think that can help you to scale later on.

Lena's point on experimentation is crucial, so it's worth echoing that the experimentation should never stop. In a sales context, a conventional wisdom is write a sales playbook, then hire a bunch of salespeople. But in reality, the playbook is never hard-coded. You should always be experimenting. In fact, if you are assigning accounts to a sales rep, make your first 100 accounts accounts, your playbook, but then make the next 50 this experimental piece. A new vertical, a new geo, a new use case, sell to a new persona. And now as a board member, the very first question I ask in a board meeting to the sales leader is, "What did you learn this quarter?" I can see the results, and revenue is a lagging indicator, but the leading indicator of where you're going is how much you're experimenting and figuring out which new revenue streams you'll get into. A quick note on Boomerangs, if you lose a candidate to another job, don't disconnect from them. Keep that connective tissue. Sync up with everyone who was on the hiring panel. Revisit them every 3, 6, 9 months, and that way you can talk about your growth, how you're de-risked, how— and maybe that candidate's job hasn't worked out. For the very best candidates, you should— it will be a very long sales cycle because they have plenty of options. So don't just give up on them if you lose them. It may take a long time to get them in.

And talking about sevens, I mean, this is probably the biggest mistake I've made. When you grow, there is this immense pressure to grow the headcount at all costs and scale. And so don't optimize for the speed of hiring over the quality of the talent. Just don't do it. Sarah Tattletail Jason M. Lemkin puts it really nicely. 7s slowly kill companies. And if you rank your team members on a scale from 1 to 10, 4s, it's an easy decision. And so are the 10s. But the 7s, 7s pose a dilemma. Because while they do add value, they also take away a seat of someone who's a 9 or a 10. So don't compromise on the quality of your talent. That's the key thing that you have in your organization.

And if you end up hiring over your early joiners, you want to make sure they don't become flight risks. So one graceful way to frame it to them is that, hey, we're going to bring on someone who you can learn from. So I want you to be a part of the hiring panel. And when they join, I want— it's dependent upon you to set them up for success. And early hires often become flight risks because they feel like they're losing access. Maybe they sat next to the founders or they were part of meetings that now they're not a part of anymore. And so you want to make sure you continuously hear the voice of those early joiners. So either include them in on meetings or create sidebars for them, because the worst thing that can happen is you grow this fat layer of middle management, and as an executive team, you get diluted what's actually happening in the trenches. So make sure you— the early winners still have a voice in your organization?

The deadly curse of silos. I mean, my entire role at Secret Escapes was connecting the dots between the marketing, the product, and the data teams. And so when you're a small business, you can physically all fit in the same room. And so comms, silos, I mean, it all happens organically. It's by osmosis. You, it's always on. As the company grows, grows, inevitably functional specializations start to emerge, and that's totally fine. But codifying and operationalizing that early DNA that got you to where you are, that real cross-functional collaboration, I think that is key to sustainable long-term growth. And so whether you use the Spotify, the famous squads, tribes, guild structure, or the GitLab and their DevOps DevSecOps, pick whatever works for you, but make sure it's in place because it's really gonna pay, pay further down the line.

Um, yeah, so culture is inherently democratic. If you hire more new people than old people, the new people set the new culture. So I like the rule of thumb that doubling headcount every year should be the absolute max. Otherwise you can lose what you successful in the early days. And I like the idea of undercapacity over overcapacity. If you get over your skis, you have too many people in the room and there's not enough work to do, that's when the drama starts. And instead, you ask people to do a little bit more than the capacity model suggests. You say, hey, everyone has a day job, but you also got a night shift. And if you really stretch this and have tension, on the hiring model, you avoid the risk of hiring too quickly and losing your culture.

Finally, we know what investors— we know what investors are telling you. Optimize for growth. Grow at all costs. The truth is, as ex-operators ourselves, it's not the revenue that you should be optimizing for. Revenue is an output. What you need to be focusing on is the input metrics. And so Whether it's the monthly active users, the conversion from free to paid, day 90 retention, pick the right North Star metric, give it to your team so that can they design experiments specifically targeted against that KPI. You know what? The revenue, it will come. With that, thank you. We want to thank you for your attention and best of luck.

Please welcome Octopus Ventures investment principal Edward Keelan.

Thank you very much. So, uh, looking around the room, this is where all the hungover people are from last night, just wandered in off the street. Straight in here, get the coffee. How many, how many sort of founders have we got? Founders, operators? How many VCs? How many founders with their VCs on a presentation about how not to blow themselves up? Nobody so far. Thank you so much for having me. It's amazing to be here, really appreciate it. Very quickly, a little bit about me. My name is Edward Keelan. I'm a partner founder with Octopus Ventures. We're one of the most active and recommended VCs in Europe. I work in the B2B software team. It's about 25% of our $2 billion portfolio. Billion-dollar portfolio. We have around about 50 SaaS companies at the moment. And I'm one of those rare VCs at the moment which is still investing. So if you are a company looking for investment, you're looking for between $2 and $10 million, please do come and see me or connect me on LinkedIn. And that is all I'm going to say about me. So why is this topic so important? Anybody know what 92% signifies? Tough crowd. Startups that fail. Good man in the pink at the front. Yeah, this is the number of startups who fail. Apparently, this is a McKinsey report. Like most of these reports, it's kind of based on nonsense. Most of the data is pretty rubbish, and if you really get into it, it's not really SaaS companies. So I looked at a different report, which was the Kit Room report. So this is a software development company. What Kit Room do is they develop software for other companies, and they've worked on over 150 SaaS businesses. And what they found is that actually the number of SaaS companies that they've worked with failed is actually 20%. So much, much lower number. However, however, there is a twist to the story. 75% of all of the companies they work with lost money. Oh, sorry, lost their investors' money. That's why I care. And 30% lost all of their investors' money, which is why I really care. And I think what this shows and what this talks about is that how robust the SaaS business model can be and how much we can survive with a SaaS business model. But however, you can still lose my money, so I still care. So why do SaaS companies fail? They went on Kit Room to look at why SaaS companies actually fail, and this is what they came up with. What I think is interesting about this is that less than 20% of the companies failed due to financial problems. And so what I took from that is it's really not my fault, it's kind of your fault. Uh, a joke, obviously. But anyway, because AI is basically going to replace all of our jobs anyway, I decided to let ChatGPT GPT write the agenda for this, and I asked that— why— I asked ChatGPT why companies failed, and this is what it came up with. It's a pretty good list, but ultimately what this comes down to is understanding when you've got product-market fit, understand when the right time is to scale, and understanding the environment that you're currently in. So this is going to be kind of the framework of today's presentation. So finding product-market is the case— first case study I wanted to talk about. Now, finding product-market fit is a bit like trying to describe a hippopotamus. You know, we kind of all know what a hippo is, it's quite hard to describe. I think we probably all know what product-market fit is, but it's quite hard to put your finger on. But I think Adam at Bessemer has done a pretty good job with this matrix. I should also admit I have done an MBA, and therefore every presentation must contain a 2x2 matrix, and this is the one from this one. And what this matrix is actually doing is it's saying you take on one axis the sort of vision of the product, like the vision of what you're trying to build. On the other axis, how much engagement you have, and then you build the quadrant. So let's, let's have a look at this. And really what this is doing is saying, when are you mistaken that you think you've got product-market fit but you actually don't have product-market fit. So if you take the first one, the sexy story, hopefully you already know— you all know a company like this. I think Google Glasses was probably like this. I've invested in plenty of companies like this, or a few of them at least, whereby the founders are in the top tech 100, the company is the fastest tech company in something or other, they're on every single list you can imagine, and the vision and what they're trying to do is so bold and it sounds like they've got product-market fit, but when you get into the actual number of customers engaged with the product, it's actually quite small and it doesn't quite make sense. The story kind of outweighs it, and that's usually when they've got a very good marketing department. On the flip side of this, on the other side, is the revenue-centric. Now, SaaS companies in particular fall foul of this problem, and that is because what happens is when you first start your SaaS company, you get some proof of concepts, usually with banks. I don't know what it is about banks. Banks love a proof of concept, but they never actually buy anything and engage with it. But you get your initial customers and you start to build things. You might even get to something that looks like $3 million ARR, and then you all of a sudden look at your tech and what you've got is a bit of a Frankenstein, because what you've been doing is the sales team have been selling to all sorts of different customers doing all sorts of different things, and before you know it, actually what you are is a service a services company. You're no longer a SaaS company. So don't let yourself get fooled to having product-market fit because you've got early revenue or you've got early stories. And then the final one is the self-deception, which is just where tech people build something because they can and because it's a little bit cool. But even if you should manage to get into that top right-hand quarter and get yourself product-market fit, the problem you've got then is how do you stay there? And that's actually more difficult than you think. Things are going well, VCs are now backing you, but the problem that you've got now is that the opportunities are massive. The opportunities are everywhere, and you have to stay disciplined and focused. So hopefully you've all read Crossing the Chasm. If not, it's kind of like Management Books 101. So Crossing the Chasm, and the way they say you cross the chasm from the early adopters to the early majority is by focusing focusing down and understanding your product-market fit and staying there and not being distracted by all the other things. So, I thought we'd start with case study number 1. This company is called Ansaray. I actually don't know if this company is pronounced Ansaray, but it doesn't exist anymore, so they can't tell me off for it anyway. But yeah, we'll start off with the company Ansaray, and they had a cool kind of product. So what their product was is that they were looking at how hiring was done, and they thought it was just kind of really ad hoc. They were saying, we're not really using data to hire, it's really about the personality of the recruiter, and why don't we as data scientists create something that both the interview process and how we actually go about recruiting people is much more based in data? I think that's a pretty cool story. I think that's— that should be a product that should work. Anyone disagree? No?

Tough crowd.

Everyone Everyone thinks that it should agree. Excellent. Now luckily, thanks to Failory, it's like my favorite website, Failory. It's all about companies that fail. Far too much positivity. Much better to look at the lessons from things that go wrong. But fortunately, Sam, the co-founder of Ansaro, he actually gives us some ideas over why his company failed, or why he thought his company failed. Number 1, conflated buyers and users. So the buyers he saw as the sort of HR people that like the idea of unbiased and etc., but the users were the recruiters. And actually the recruiters didn't really care what the outcome was. What they wanted was an efficient recruitment process. But the problem with that, and that came into number 2 for him, was it took a long time to prove out the ROI. So although the HR people loved it, it was very hard to get kind of wider management buy-in because he couldn't actually prove out about the value of it. And he gives his third problem as being a slow pivot. So he decided to pivot when things weren't working to like a transcription service, and his feeling was that he was a bit slow to do that. I'm not so sure I agree. Now let's look using my matrix again— or not my matrix, Adam's matrix, can't claim credit. We can see sort of what happens. First of all, with product-market fit, They solve the recruitment bias story. It's a sexy story. It works really well. They get early traction. They get some early investment. It's all going good. But then what happens is, to win proof of concepts, what he finds is there are no kind of one HR system. There's no APIs for HR systems. And even worse, the companies don't even trust their own data they've got in their HR and recruitment systems. And so they have to go away and build build bespoke products each time. And before long, what they ended up with is 4 or 5 completely random products that didn't talk to each other and wouldn't scale. They might have thought they had product-market fit at this point, but they didn't. And finally, he goes into the sort of self-deception mode. Why don't we just create anything? We've got some money. Let's just do anything. Let's build some tech. And he created the transcription. But I think by that stage, he'd actually lost his kind of way. I think he'd lost his vision completely. For me, I think actually what he should have done— just, I don't know, I don't know the company— but what I think he should have done was probably actually stuck with his vision. So we've got a company called Sova that's doing a lot of this sort of stuff, and it's flying at the moment because actually that's the way the mood and the culture has gone. So he just needed to buy himself a bit more time. So some quick lessons from Ansari. First of all, do not mix up the fact that everybody loves you you with the idea that you've got product-market fit. They are two different things. Don't mistake the fact that you've got early proof of concepts with the idea you've got product-market fit. You know, make sure that you've got something that is scalable and repeatable. And finally, when you do have product-market fit— and this is probably the hardest one of all of them— when you do start to feel like you've got product-market fit, double down on the customers and the sectors that are working. Do not get blind blindsided by the fact there's all these other amazing opportunities out there. And finally, and the one that nobody will say in a presentation like this, if the idea is rubbish, just stop. It might just be your idea isn't very good. You know, you might have thought it was, but perhaps it wasn't. Oh, so moving on, fixing product and churn. So case study number 2. Anybody heard of this company, Scalefax? ScaleFactor? Nobody? They raised $100 million under the radar. It's pretty crazy, isn't it? And the idea of ScaleFactor— it's probably good because if anybody was here from ScaleFactor, then this would be really awkward. But yeah, the idea between ScaleFactor was that, like, bookkeeping is really boring, it's really hard for small businesses, but don't worry, we've got technology, so we're going to let our AI algorithms on your bookkeeping, everything's going to be automated, everything's going to be live, just give us all your stuff and we'll make it happen all through our whizzy apps and things and it'll all be good. And lots of people bought into that, they got sort of £14 million. However, unfortunately, according to Scale Factor, what they said was that due to the difficult period that we had, a lot of small businesses shut down and their product just then wasn't viable not viable. That's what they said. They also tried to pivot. They tried to pivot as well into a marketplace for accountants. Again, a kind of random pivot once they'd lost their vision. However, that might not have been true. So the people that actually worked at ScaleFactor, and this is an amazing article, if you get the chance, read this Forbes article. It's a fantastic piece of journalism which really got to the crux of why ScaleFactor failed. Ultimately, it came down— they believe it came down to 3 things. So there's sort of 3 things, the reason why Scale Factor failed. Number 1, the product didn't work. So the idea was that it was always going to be automated, all this bookkeeping was going to be automated, live time, all this. What transpired is that they just had outsourced people in the Philippines, and so all the accounts got sent to them. They would start crunching the numbers and trying to provide it. To make matters worse, they called those accountants customer service reps and had it below cost of sales. That's a bit naughty. But even better than that, they were churning customers. Because the product wasn't great, they started churning customers really, really quickly. And the way— and the sort of third thing that went wrong, the way they tried to solve that problem of churn and the product not being right, what do you do? Flood it with salespeople. So if there's like One lesson I can probably take away: you cannot solve churn by sales. You cannot sell your way out of trouble. We go deeper into this and sort of think about actually what might have happened. I like this chart because it kind of gives you an idea of what might have happened over the last 3 years. I've again plagiarized it from Zero to 100, and if we get to that point where We've got that product-market fit we talked about earlier. What we should then do is create a repeatable product. So we should make sure the product is ready to scale, yeah? And then what we should do is make sure our customers love us and make sure that we're adding in before doing anything else. And then what we should do is build a sales flywheel and make sure the sales processes worked. But what actually happened over the last 3 years is people like me— sorry, it's kind of my fault. Not my part. I'm not taking the whole blame. Partly my fault, is people like me saw companies with product-market fit, they threw money at them and said, please, can you grow? And grow by adding salespeople. And we missed out that middle stage. We missed out the repeatable processes. And that's why we're causing the— that, you know, that's what's causing the problem. So how do we kind of know when it's ready to— when we're ready to scale in terms of product and churn? You've probably all seen these statistics. This isn't, this isn't a session about KPIs, but I'll throw them up anyway. If your gross margin is less than 75% in a SaaS world, your product is probably not ready to scale. I work with companies at the moment where, quite honestly, their gross margin is less than 70%, and as they're trying to kind of restructure and as they're trying to reorganize themselves, it is really difficult because cost of sales within a SaaS company is people. So if you can't reduce your cost of sales because they're people, then you're in a real, real problem. So you should definitely not scale unless your gross margin is sort of above 75%. I'll try again with audience participation. It's worked really well so far. 5 times. Anybody know what 5 times signifies in this, in the sense of churn? —Thank you for trying, you're incorrect. 5 times is how much cheaper it is to keep an existing customer than win a new one. This is quite a well-publicized number. It's 5 times more cost-effective to keep an existing customer than it is to win a new one, which is why it is impossible to grow yourself out of churn. Now there's lots and lots of studies and KPIs around revenue retention But I don't care really what your ACV is. Ultimately, if your gross revenue retention is not higher than 90% and your net revenue retention is not above 100%, you have a customer problem and it is not time to scale. So very quickly, lessons. So number one, if you take anything away from this, do not try to scale before you have got a product that will scale and churn churn under control. Masking churn by trying to sell your way out will just not work. And finally, this is probably less relevant now actually because it's kind of flipped the other way around. I was going to say, like, be honest with your investors and tell your investors where you are and that it's not time to spend money on salespeople because you still have to get the product. And it's actually flipped the other way around with all investors now turning around to all the companies and saying, hey, don't scale until you've got these things sorted. But I do think, and if you look at the case studies on Scale Factor, there were certain amounts where the investor-company relationship had broken down, and maybe the investors didn't quite understand what was going on. So do be honest with your investors, although I would say that. So case study number 3, we are getting through them, I promise. Case study number 3 is about adapting to your environment. Now, I have a prophecy. I think many, many companies over the next 12 months will die that don't need to die. I think companies, SaaS companies I'm talking about, a lot of SaaS companies will go bust that don't need to. And so we need to try and adapt to our environment. This isn't therapy, but I thought I'd give you a little bit of an insight into my life over the last sort of 6 years as a SaaS investor. I started off about 6 years ago into SaaS, and everyone said to me that SaaS was interesting, and I was like, yeah, it is interesting, business models, that's why we love it. And then the difficult summer happened where I had to try and homeschool my children, desperate to get back to work. That lasted about, what, 2 months? And then the world woke up and went, hey, if anything's going to win in this environment, it's probably software. And software went nuts, absolutely crazy, and valuations went absolutely crazy. We'll come on to that. But there was a real big problem with that, because what was really happening was that as SaaS became the kind of in thing, and the thing that people wanted to talk about, was you got a lot of short-term investors into the market. Now, I'm not going to name the various US hedge funds that kind of came into the SaaS market and pumped companies full of money to only try and flip them into the IPO market. That's what happened. If you want to know how Bubbles are created not when people get excited about something, but when short-term investors come into a long-term market, and that is what happened. You had very short-term investors pumping companies full of money at ridiculous valuations in the hope that they could flip them into IPO in the kind of greater fool theory. But that's not what this is about, that's just me getting on my soapbox, so I'll shut up about that. Anyone wants to get me earlier over a drink, that's probably a better time for that one. Anyway, then on the roller coaster, things change again, and we're now in that session where we all think we're doomed. But I'm not convinced about that. I'm still pretty excited about SaaS companies. I still think the fundamentals behind SaaS companies remain, and actually the business models that we all got so excited about are still there. Nothing's changed. And we can see that in the reflection of valuations. So I put my roller coaster on the SaaS Capital Index. So the SaaS Capital Index is my favorite of all indexes. It's the one that kind of really looks at what's going on in the market. And you can see the kind of the same sort of path where things were sort of tottering around, growing slowly at sort of a median of around about 6 times ARR, 7 times ARR. Then we have this craziness, and now we're back back to sort of where we were before. I've talked to a lot of people these last couple of days, and there's a lot of investors that are still very happy to invest at sort of 6 to 7 times ARR. You know, people are talking— I know, I know there's sort of a theory that it's more like 3 to 5, but I think there's quite a lot that are more quite happy to sort of do 6. What can I do? Terrible metaphor. So there's a reason why I'm not wearing my favorite shirt today. That's because I've been been on holiday for 2 weeks and it doesn't fit me anymore. That's honest. That doesn't mean to say there's anything wrong with the shirt, just meant I ate too much over the last couple of years. And I— or last couple of weeks. In SaaS world, it's the last couple of years. And I sort of feel like that's where we are. There's nothing wrong with the SaaS model, it's just that we ate too much over the last couple of years and expectations, like I have from my shirt sizes, was a bit out of sync. Anyway, let's get on to the final case study, and this is a company called Lucidera. I will ask again, anyone heard of Lucidera? Probably people weren't born in the crowd when Lucidera was actually created, because it was actually created in the last big recession when SaaS was a mere twinkle in everybody's eyes. And the idea between Lucidera— and this was revolutionary at the time, was that it was going to be a business intelligence platform that sat on top of Salesforce and on your ERP system, and it gave you real-life data, and it looked a bit like this. This at the time was revolutionary. SaaS 1.0. No one had come up with this. We were still carrying around CD-ROMs and putting them into disk drives to upload our software. But it had something that was quite unique Unfortunately, lucid era did not last. I like this quote for a number of reasons. I don't know how big it is on the screen, but I like it because of Geoffrey's 'tache. I think Geoffrey's moustache is amazing in here. But I also think it gives us an idea just how far SaaS has come. Just 15 years ago, people were still questioning whether cloud computing and SaaS was even going to be a thing, and lucid era was kind of the big first casualty of of the last recession. But I'm not sure it needed to be. Lucid Era's problem was it raised money in 2007. I mean, talk about timing. Anyone that, you know, raised money in 2002 probably feels this way as well. But certainly in 2007, people raised probably a very high valuation with very high expectations for something which was quite new. And actually, after a couple of years, what happened is they couldn't raise any more capital. Now, that is a problem for a lot of companies in the crowd right now, will be that you're just in that era where it's really hard to raise capital, because if you've raised capital at a really, really high valuation, to raise any more capital means that you've got to find investors that are probably going to do a down round. Now, your existing investors aren't going to want to do a down round, but even if they do want to do a down round, they want to go for a lower valuation and valuations have halved, remember. Well, that's all fine, but now you've got a capital stack that has your existing investors and you've got your new investors, and it probably means that all of management are under the water. So that also means that your existing investors probably also take— have to take a haircut on their preference and have to somehow recut in management. And they may well be looking at your technology and thinking, the scrap value to me of that technology is worth more than than me allowing another investor to come in. So I'm afraid to say you ultimately don't have a choice. There is no choice. Your only method of survival is time. Time is your only method of survival, is making cash work, because people just cannot invest. Did it have to be that way? Fortunately, SaaS Capital did a really good blog on what happened over the the last recession. There wasn't so many SaaS companies then. There was only about 16. That included Salesforce, which was like 90% of the entire SaaS market. And so taking away Salesforce, they did some analysis and they had a look at it. And what they found was all the SaaS companies during the great big recession actually survived. None of them died. And the reason why they didn't die, and you can see it from this chart, was what they did is although growth plummeted, expanded very rapidly, they controlled cost. And I think they were prepared to do that. And I think because it was such a macro thing and everybody in the environment was so with that, that was probably easier to do. We're in a sort of different world today because for the last few years all founders have been told it's grow, grow, grow, and etc., etc. And now the mindset shift is, I think, probably harder. But it is happening. So if we look at this graph, So I'm kind of the bringer of doom. I mean, there's, yes, far too much positivity at this session. So, but even more bringers of doom is layoff.fi, or whatever that website's called, who are kind of charting the number of layoffs at the moment in tech. I find this graph fascinating. You know, during '21 and '22, I just told my portfolio companies like how hard it was to hire people and how much you'd have to, you know, find agencies and why you have to pay your developers more than you're paying your CEO. So, you know, I may have told a few friends to quit their secure jobs and join a startup because they'd get paid more. So sorry about that, Mark. But, you know, there is a real human cost to this. There is a real human cost to what happened with sort of pumping companies with money and paying developers and selling them the dream that no longer exists, which is that we're now seeing huge amounts of layoffs. And I think this is probably only just starting. It's a bit of a detour. Anyone read The Hard Thing About Hard Things? If not, that's your learning number 2. Read Cross the Chasm. Now read The Hard Thing About Hard Things by Ben Horowitz. There's one little thing that I really like in this, one kind of little tip, and that's if you're restructuring your organization, what most people do is they get their org chart and they decide who the deadwood is and they start putting crosses in them. Oh, they're not very good. That is the wrong thing to do. What Ben suggests— I say Ben, he's not a friend. He's not a friend, I don't know him. So what Ben Horowitz says is start with a blank sheet of paper, map out the organizational chart that you think is necessary to deliver, and then find your best people in your existing org chart and put them in the new one. It's quite a different mentality, and it sounds really simple and common sense, but it will save you a lot of time and heartache. And what you'll find is your best people will be flexible and will move. Now one of the questions I get asked quite a lot is, okay, well, how, how many employees— that is, the right number of employees that I should have in my company? And often you get this kind of metric which is employees to ARR, and I wasn't convinced that was enough for me. I thought we could be a bit more educated because SaaS companies are quite different. So what I built is is something called the Headcount Calculator. And my friend Chloe, my colleague Chloe, built this code. And apparently if you scan this code, it will take you to the Headcount Calculator. How cool is that? No, I say, I'm impressed by anything. It will take you to a blog, and at the bottom of the blog is the Headcount Calculator. It's an Excel chart. You can fiddle around with it. But the idea is that you can put in your growth rate, you can put in your ARR, you can put in your margin, you can put in the the average salary of your employees, and it starts to build kind of what your headcount should be. And it bases it off the burn multiple. Now, for those that don't know, the burn multiple is basically how much cash you should be burning versus the ARR you should be adding. So if you've got a burn multiple of 1.5 times, what that means is if you're adding £1 million worth of ARR, you should be burning no more than £1.5 million worth of ARR. Now we kind of ignored this stat for the last 3 years. It wasn't that important to us. It is really, really important now, and it's probably the one— for me, it's one of the few efficiency metrics that can't be somehow manipulated. And I take, you know, we take it really seriously. If your burn multiple is more than 1.5 times right now, you're not efficient. And that's why that's kind of the thing that I'm using to back solve the employee headcount calculator. It's fair to say we were investing in companies that had like burn multiples of 3. You know, good is burn multiples of less than 1. So yeah, Company A, just as an example, Company A, because it's got 40% growth, because of the positive working capital benefit you get from SaaS businesses, they could actually have 70 employees with those statistics, with a good gross margin. So 60 employees with a good gross margin, good growth, solving for a burn multiple of 1.5, Compare that to Company B, where growth is half that amount, gross margin is down, they're looking at something like 40 employees. So quite, quite different. So lessons from Lucid Area. Time. I can't say that enough. The beauty of SaaS, the reason why we all love the SaaS business models, is if you've got the kind of product and you've got the churn right, you should be be able to match enough of your cost, enough of your revenue, and buy yourself time. And it will be that time that allows you to succeed. I think it's fair to say that it's probably— and I wouldn't put the blame at founders, I'd put the blame at investors— that we've been reckless with hiring over the last few years. There's a real human cost to that. I think when you restructure now, just try and learn those lessons from that. You know, cut deep. And make sure we don't get it wrong. You know, the worst thing you can do is have to cut employees not once or twice, but 3 times. It just builds terrible culture. It makes people feel uneasy. Just be really honest and do it once. And then the final one, it comes back to that point I was making earlier. If you have exploded your cap table— I call it like the exploding cap table— if you are in a position where you raised tons of money at really, really high valuations, you literally have no choice. Choice but to get to cash flow breakeven. Well, either that or there's some, you know, decent venture debt providers out there that might stretch you a little bit. But ultimately what you need to do is try and get to a point where you're in your own destiny, and there's not really a lot of choice about that. Um, so yeah, those are my key— my key takeaway was going to be don't spend money on really expensive conferences, uh, but I probably thought I wouldn't get an invite back if I said that. So these are my 3 takeaways. Any questions? No questions at all? Somebody help me out. Fraser, ask a question. Ah, good man. Oh, sorry. How do you want to work that? Do it karaoke style.

So yeah, you mentioned the burn multiple from 1.5, and I was wondering, like, is that a constant in all stages? Because I imagine that, like, Series C, D, you are supposed to be much more efficient, but if you are in seed or Series A, maybe that looks a bit different.

Yeah, that's a great question. The question was around whether the burn multiple should change, whether your target burn learn multiple should change. And I think the answer to that is probably yes. As you grow, you know, when you're at— when you're— I've used an example of $3 million ARR business there, and I sort of think that's about right. That's sort of $3 million ARR business, you're looking at about 1.5 times burn. But yeah, once you get into a company that's doing, you know, $20, $30 million ARR, then your burn multiple— well, you probably shouldn't have one at that point. You should— burn multiple should probably be zero, but you should certainly be lower than 1. I would agree with that. Any other questions? Yes, Rocket Man by Elton John.

This is Nick from Cartier. This is going to get quite abstract because everyone— like, the question of the meaning of life is the same for product-market fit. There is no kind of fine definition. But I liked your thing earlier about saying just because your customers love you doesn't doesn't mean you have product-market fit.

And there were—

there was a— there was another point you raised in your deck, but the problem is when you're an early-stage startup, like, obviously that's when you're probably going to get most feedback and that sort of thing.

So in your view, like, particularly in the early stage, what do you define as like product-market fit? In the— that's, uh, it's a really good question. I mean, the one thing I think that I think defines product-market fit fit. And really product-market fit means do you have a good idea that's going to work and scale? That's really what it means. And the one thing that I think really does signify that is whether people are calling you because you're solving a problem for them, or are you calling them because they're your mates or because you know them? Are you trying to convince them of a problem that they might have? You trying to educate them? Because this is where I think banks have a, you know, quite often they're the people that always love a proof proof of concept. Anyone work with banks here? They love a proof of concept, and they spend loads of money on it. And then you say, right, do you want to like embed this in your organization? And they're like, no, I can't get sign-off, and etc., etc. And so to me, it's like if somebody is calling you and asking, I want your product to fix my problem, that's when you've got product-market fit. You know, if you're in a situation whereby you keep having to build stuff or you keep having to convince people, then you probably haven't. So I'm quite big on the sort of sales flywheel. I think I didn't have time to include it in this presentation, the sales flywheel, but I think the kind of marketing is often— MQLs are often the kind of lost piece of product-market fit. But that is what I'd be looking for. Cheers, thanks. Any other questions? Any requests? Any Ed Sheeran [Speaker:JASON M. LEMKIN] Cool. Finished ahead of time. Thank you very much, guys.