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 venture scape, the obvious elephant in the room. But having had a lot of conversation over the past couple of days, I think is actually a more helpful 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 going to try to. It sounds pretty abstract so I'm going to try to be really concrete about it. I think ideally at the end of the next 10, 15 or so minutes you'll have a understanding and framework what VCs look at these days basically when they're looking at revenue beyond obviously the top line, a actionable way to look at your own revenue ahead of a fundraise or 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 and A. Yeah, that's a 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 Speed Invest. 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 six teams as sort of like verticalized teams and one of those teams is SaaS and infra, I'm a partner on that team and that's why I'm here. And then you know, the 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 of the modern software building blocks of companies. Right. So we start at the very top of the like application stack, so 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 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 two days ago or so from Carter, but if you're googling, there's all sorts of numbers out there. I think the, the, the fundamental headline here is that VC dollars have not quite dried up, but especially at the later stages, it's have really come down. Right. And I think everyone knows 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 why you're here, I'd imagine. And yeah, just as an additional data point and I just realized that that's 2, 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 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, our job is to give advice to our portfolio companies and help them navigate 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 in our network with our founders, portfolio founders, friendly founders and all the sort of downstream fund relationships that we have. And we asked around what actually are the most common pass reasons from series B and like somewhat astonishingly, they're not that changed. Like people will tell you quite similar things. They'll tell you, well, you know, 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 like other reasons, cap table, team, market size, you name it, all the stuff that's, 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're 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 Suite 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 talk 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, 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 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 appeal to, you 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 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 and 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 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 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 HR software to you know, scale ups or tech companies and there's a hiring freeze that might be, it might be harder to take that to market. So again like this is just a, like a way to look at sort of what your, what sectors you're selling to and sort of how that's, 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're 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, long term incompatible interests with that corporate and they're kind of using you know, the 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 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 weird. A lot, 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. But, 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 and 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 like that might be a problem. Right. And so if you were to take away one thing from sort of all of this, the first part, the qualitative, it's really that like, you know, not all revenue is created equal and the dollar will be judged to like assess your amount of like the amount of product market you have, the late demand that is in your, in your, that your product has in your industry and sort of what the expectations of future revenue based on this. R. That's sort of the first bit. So 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. You know, software gross margins, probably one of the most commonly talked about topics here. And then I, 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 like, there's no good or bad necessarily. But if like 80% of your revenue is from two 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 and 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 9am to check it, because that should be the workflow. And, 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 the 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 to 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 want to 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 it's currently solving someone's like, hair on fire problem. Right. So this is sort of the, the second part. The. Yeah, the, the, the, the, the liminal space between the, 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. Yeah. Like how high quality your revenue is and how people will judge it. 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 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's said and done. I'm going to go through them and then, I mean we can have a Q and A at the end, right? So let's, let's jump in. Good morning, Mr. Sachs. So there are five and I don't know why the slide shifted. There are five fundamental, like I'd say there's four and then there's one that I thought was funny. There are four, 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 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 Cetera's paribus like 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 this 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. 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, you know, 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 upsell. Those are the two ones. The next 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 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, like, salesperson to phone call, right? There's, like this, like. And there's. There's people that are much more qualified than me to talk about that in detail. But especially with, you know, 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, like, basic measure of, you know, 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. 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, 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 the. 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 on your journey, and I know this is like 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, you know, to invest into R and D to build products to then be successful. So the whole point is that you're probably not going to be particularly efficient, right? Because obviously R and 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. 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 in American venture capitalist. And it's really about the capital raised divided by ARR. So it's just how much does this firm raise and where are they at? And it just sometimes makes for a very fun crunch based 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 like 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 like more around the series a stage. So some of them are more serious, 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. And I believe there's also if you want a competing benchmark, I believe iconic 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. Well not competition at all. Much later stage than us plugging in other firm's 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 excess. Excess 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 fundraiser. It's good practice to basically get in the habit of like understanding these things, knowing how you're going to be, you know, 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 like have this like spectrum and we try to split it a little bit into qualitative, quantitative and this like liminal in between space. And the idea really is to like, you know, 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 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's like 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. 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, so 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 how 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, as a broad, 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 historic figures that people use. Once again, use them with a grain of salt. Right. But like on average, if you enter out, should be, should obviously be over 100. So that's sort of. Does that answer the question? To some extent. Any takers for any questions? Oh, someone's getting up.

Hi, Heather, founder of a Street Group, SAS Co. 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 yeah.

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, 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 I'll be tied in for six 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 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 with the idea that they will potentially value that service more As a customer make better use of that and 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. Did 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. All of it. 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 like look, actually this is a separate business line that we're building out and we think we can like you know, increase this business line because we're not providing value added services and you know, it somehow makes sense in your reporting structure and in your hiring structure then sure. But like I think if someone looked at it and like previously it was $10 a month and now it's 7 and 3 but they have different names like 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. Cool. 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.

Yeah, yeah. Not an expert. I've have a few companies going into sort of into usage base 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 over complicated on the optimizing for VC side. Right. Like 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, you know, conversion early on. It can help actually increase baskets as 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 three months, right? So I would say if it makes sense, then go for it. We operate in a relative niche which makes a 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.

That'S 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 you know, it's sort of downside protected, then there's no, there's no issue with that necessarily. So it's a little bit as a question of like 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 you know, a lot of it is, you know, time expansion that happens over time by virtue of the fact that this business growth is actually category creation happening. So it's a little bit of question of like what kind of business do you want to build? Do you think there's a credible way for you to, you know, 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, multimillion 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, I don't know, close to or have visibility on profitability, then like 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. So it's a bit of a tangent, but the best way to understand 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, 3xing 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. Thanks.

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.

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 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 want to 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. 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 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 how you where you where your your customer success. Sits and where your AE 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? Like that's your story. So you've got to figure out why the new acquisition isn't as efficient or you got to make a story that like, right, we're going to 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 cap to LTV. If you're a company, we're SaaS companies say we're three, four, five years in. You have customers, they haven't really turned.

Your NRR is above 100.

How would you look at modeling your LTV?

Most funds will just take a like a cut off. They'll just won't believe you. Anything above like two years really like, I mean you should have an internal analysis of it. So even if you have companies that.

Are around for three, four years, it.

Just discounted people will eventually like maybe they'll take a three 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 model. So like a lot of later stage funds will sort of take a cut off where they're like. Because realistically you should have recouped your CAC at that point anyway, right?

Well, yeah, I hope so.

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

Sure. Thanks.

All right, Mike, 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 thanks so much for your time. Have a great day at Sastra. It. Baby. It. Sa. Sa. Baby. You. It.

Please welcome Verdain's partner, Helena Svankar and.

Onomondo's VP of growth, Jennifer Montague.

All right. 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 Verdain, 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, onedo.

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 move beyond that growth at all cost, SaaS is still thriving. But we cannot deny that the markets have changed. 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 three 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 one? So it's actually a bit different. Sorry, I'm a bit confused here with. With the clicking. So bear with me.

No worries. Thank you very much. So, yes, as Elena mentioned, there's capital. We're here, so. Yes. So what I mentioned earlier, one of the things that we do on a Mundo. 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 assigned 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 ANO 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 cst. 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 and 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, Jan. 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 one buys products of you for some 30k. In year two, 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 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 power of earned growth. So the fact that customers advocate for your product 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 key to sustain your revenues. But for growth, customers advocacy is really what you should go for. Okay, to create that earned growth, we suggest you ask yourself three questions. Number one, what does customer value look like? Number two, 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 a successful growth to market strategy. And that's pricing. Let's see if we manage this in two minutes, but let's give it a go.

So.

Oh, now there is something wrong with the slides. 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 many cases today compared to 12 to 18 months ago. And this obviously has an impact on pricing dynamics. A customer that has 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 really important. What do you say, Jennifer? Does that resonate with what you see at one do?

Yes, absolutely. So one of the things that we've approached obviously at ANO 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 of 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 mvts, minimal viable tests that let us get something quick and dirty out the door that is going to 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 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 three 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 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.

Ram. Sa. It. Baby, Baby. It. Sa. Sam. It. Good baby, Good baby. Good baby, Good baby. It. Sa.

Please welcome psg equities managing director, head.

Of talent corianne van dremelin and psg.

Equities managing director, product and technology europe, antony edwards.

You tricked me. Oh wow. Nice.

Sorry.

We'll talk. We'll talk 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 Anthony.

Good morning.

And I'm Koriyamo and we're from PSG, a growth equity firm that it's invested in over 150 scale up. 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 six of every scale up. This is a picture we see over and over again. You get a great startup, it grows really quickly, does really well and then it hits 10 million, 12 million ARR and the growth just stops. It goes really flat. And the reason for, for that is because during that initial growth period people weren't scaling up their management team. It's the same three to four 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 nine 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 three 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 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? 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 a success, successful, here you have some people in the team that you will recognize. We're pointing out the two that we come across 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 two, 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 one 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 the key thing from Kolyana there is what got you here won't get you there. So when you're thinking about your management, 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 roll by roll. 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 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, look, it's similar. It's when they start having to manage multiple priorities at once. It's when it's 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 multiple priorities. 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 people beside them as well. Ctos pick up a lot of additional responsibilities in startups. They usually run a lot of opera. All the operational stuff ends up with them. Support, professional services, random things. The ones who can bring in people besides 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 era, 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 going to 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 and A, I do just really want to highlight that because that's the thing that brings most startup scale ups undone if they haven't built up that management team. And it's simple. I mean firstly, integration's 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 big M and a big integration until you've built that scale up management team. And that's really it. If there's three takeaways we wanted you to have from this presentation. Number one, when you hit 7 million of ARR, stop 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 two, 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 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 two 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 to want, want to control everything and become, 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. That's excellent. So thank you very much.

Thank you very much. Are we doing questions?

Good baby. Good baby. Good baby. Good baby. Good baby. Sa. Sa. Good baby. Radio. Ram. It. Sam Please welcome Notion Capital's general partner.

Joss White and Notion Capital's principal, Stephanie Opdam.

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 hundred 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 four changes to business models that used to be ingrained in the SAS playbook but are now changing in the light of the current difficult environment we find ourselves in. But also a maturing software market. Now we before we dive into some of these business models changes, I'll briefly call for 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 the COVID has been a massive tailwind for the software adoption worldwide helped by the abundance of capital available with kind of really send 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, hovering around that level. But we do think it will remain like this for the next year or so. 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 fast to counter the decline in multiple 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 that, 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 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 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 strong metrics in terms of your efficiency, then it's more important than ever that you push hard towards profitability. That means that you're actually able to, to buy time, that you have optionality 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 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 profitability to give themselves more time and space to regroup and figure out what the best options are moving forwards. So I think the framework that I talked about helps to inform the four business model changes or the four emerging strategies that we're talking about today. So the first one is the way that 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 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 grow, you have to actually hire more people. So the cost of growth is very, you know, 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 can be that more kind of efficient model. And we've seen in terms of the data we've seen out of in the last three 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 cloud challenger report that Steph mentioned where we picked the top 100 emerging cloud companies in Europe, 40% of those were PLG companies. So you can see that PLG becoming more and more significant as a growth model for SaaS 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, it was a model that, you know, I think the kind of free and easy money environment led to. But I think that the headcount driven growth model is now being challenged 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 of 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 150, 200k per head. The best performing public SaaS companies are at about 300k or more per head. And so it's to try to try to break that relationship between your cost base and your revenue growth and 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 JOS has been talking a little bit about the cost optimization areas, but, 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 really seen the 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 more optimally align your marginal revenue per customer with that of the marginal cost per customer to create an equal kind of product profit opportunity per customer. And so if you look at kind of Data from the US Open View sees that about 62% of companies have adopted usage based pricing in some form growing to 80% over the next two 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 plus model. And especially in this environment really recommend you looking into the SaaS plus model where you keep your existing revenue base but you start layering on these additional revenue streams. Portfolio company of ours, MU Systems recently saw actually their usage based revenues overtaking that of the SaaS base. Showing the skill 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 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, that is using a broker to adopt a pay as you go model or using cloud optimization spend tools of which many have popped up in the last year or so can really make a meaningful difference. So on the key takeaways, okay, so.

Just quickly to wrap up, I think SAS, 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 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, efficiency through technology and process 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 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 Next 47's partner, Micah Smurthway and Stride VC's principal, Lena Zacharyskaida.

So, stand here.

Right.

Cool. Hi, I'm Micah. I'm from Nex47. 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 a million to over 100 million. Today the company's at 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, Sasters, Leena from Stride VC here we are an early stage fund based in London that invests in B2B and B2C projects at seed. Before going to venture, I was ahead 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. Micah, 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 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, you know, 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 going to 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 offer, 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 mis hire 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 going to 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 to 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 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? And a single idea. It's not necessarily good or bad. The key is you need to test and learn because that's only way to know. And so ideate, define a hypothesis, set up your ab test, measure and learn. I mean at Secret Escapes we used to run 150 creative ad optimizations a week on performance channels only. And 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 hundred accounts your playbook, but then make the next 50. This experimental piece, a new vertical, a new geo, a new um, 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 three, six, nine 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, 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 Tavel puts it really nicely. Seven slowly kill companies. And if you rank your team members on a scale from 1 to 10 fourth, it's an easy decision, and so are the tens. But the sevens, sevens 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 deluded what's actually happening in the trenches. So make sure the early joiners still have a voice in your organization.

The deadly curse of the 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, it's always on. As the company grows, inevitably functional specializations start to emerge. And that, 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 squad strives guild structure or the GitLab and their devsecops, pick whatever works for you but make sure it's in place because it's really going to pay further down the line.

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 made you successful in the early days. And I like the idea of, of under capacity over over capacity. If you get over your skis and 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 be design experiments specifically targeted against that KPI. And you know what, the revenue, it will come. And so with that, thank you. We want to thank you for your attention and best of luck.

It. Good, baby.

Please welcome Octopus Ventures investment principal Edward Keelan.

Thank you very much. So looking around the room, this is where all the hungover people are from last night. Just wandering off the street. Kind of 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 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. And 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. Yes, 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, there is a twist to the story. SaaS 75% of all of the companies they work with lost money. 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 satisfaction 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, I joke, obviously. But anyway, because AI is basically going to replace all of our jobs anyway, I decided to let ChatGPT write the agenda for this and I asked that one, like 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 fit 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 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 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 is 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 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 back 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 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 the case study number one. This company is called Ansaro. I actually don't know if this company is pronounced Ansaro, 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 Ansario, 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 should be a product that should work. Anyone disagree? No. Tough crowd. 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 one, conflated buyers and users. So the buyers he saw as the sort of HR people, 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 two for him was it took a long time to prove out the roi. So although HR people loved it, it was very hard to get kind of wider management by him because he couldn't actually prove out the value of it. And he could 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 box 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 the own data they've got in their HR and recruitment systems. And so they have to go away and build bespoke products each time, time. And before long what they ended up with is four or five 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 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, I don't know, I don't know the company, but what I think he should have done was probably actually struck 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 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 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 cool. So moving on, fixing product and churn. So case study number two. Anybody heard of this company Scale Factor? Nobody. They raised $100 million under the radar. It's pretty crazy, isn't it? And the idea of scale Factor is probably good because if anybody was here from Scale Factor then this would be really awkward. But yeah, the idea between scale Factor 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 platform 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 wizzy apps and things, and it all will be good. And lots of people bought into that. They got sort of 14 million AR. 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. That's what they said. They also try to pivot. They try 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 Scale Factor, 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 crooks of why Scale Factor failed. Ultimately, it came down. They believe it came down to three things. So there's sort of three things. The reason why Scale Factor failed. Number one, the product didn't work. So the idea was it was always going to be automated. All this bookkeeping was going to be automated. Live time, all this. What it 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. It'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 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 it'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 three years, I've again plagiarized it from 0 to 100. And if we get to that point where we. 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 process has worked. But what actually happened over the last three years is People like me, sorry, it's kind of my fault, not my part. I'm not taking the whole blame, but 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 causing the problem. So how do we kind of know when it's ready to. When we're ready to scale in terms of products and churn? You've probably all seen these statistics. 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. Five times. Anybody know what five times signifies in this, in the sense of ch? Thank you for trying. You're incorrect. Five times is how much cheaper it is to keep an existing customer than win a new one. So it's quite a well publicized number. It's five 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 say, number one, if you take anything away from this, do not try to scale before you have got a product that will scale and chat 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 three, we are getting through them, I promise. Case study number three 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 six years as a SaaS investor. I started off off about six years ago into SAS and everyone said to me that SAS 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, two 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 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 of bunch bubbles are created. 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. Anyway, 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 and the reflection of valuations. So I put my roller coaster on the SAS Capital Index. So the SAS 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 to sort of where we were before. I've talked to a lot of people this. These last couple of days and there's a lot of investors that are still very happy to invest that sort of six, seven times ARR. You know, people are talking. I know, I know. There's sort of a theory that it's more like three to five, but I think there's quite a lot that are more quite happy to sort of do six. What can I do? Are you. Terrible method. So there's a reason why I'm not wearing my favorite shirt today that's on holiday for two weeks and it doesn't fit me anymore. It'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 or last couple of weeks. In SASS world, it's the last couple of years and I sort of feel like that's where we are. There's nothing wrong with a SaaS model. It's just that we ate too much over the last couple of years and expectations like I have for 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 Lucid Era. I will ask again, anyone heard of Lucid Era? Probably people weren't born in the crowd when Lucid Era 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 Lucid Era and this was revolution 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 live data and it looked a bit like this. This, at the time was revolutionary. SAS 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 Jeffrey's tache. I think Jeffrey's moustache is amazing in here, but I also think it gives us an idea just how far SAS has come. Just 15 years ago, people were still questioning whether cloud computing and SAS was even going to be a thing. And Lucid Era was kind of the big first casualty 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 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 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 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, SAS Capital did a really good blog on what happened over the last. 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 very well, 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 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 there is a real human cost to this. There is a real human cost to what happened with 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 two, 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 dead wood is, and they start putting crosses in them. Oh, they're not very good. They're not really. That is the wrong thing to do, what Ben suggests. I say, ben, 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 hard 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 many employees? Ed 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 SAS companies are quite different. So what I built is the. Something called the headcount calculator. And my friend Chloe, my colleague Chloe, built this code. And if you scan, apparently if you scan this code, it will take you to the headcount calculator. How cool is that? No, 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 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 one and a half times, what that means is if you're adding a million pounds worth of ARR, you should be burning no more than one and a half million pounds worth of arrangements. Now, we kind of ignored this stat for the last three 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 one and a half 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 fast to say we were investing companies that had like burn multiples of three. Good is burn multiples of less than one. 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 bare multiple of one and a half. 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 to able, 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'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, you know, and, and make sure we don't get it wrong. The worst thing you can do is have to cut employees not once or twice, but three 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 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 but to get to cash flow break even. Well, either that or there's some 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. So, yeah, those are my key takeaways. My key takeaway was going to be don't spend money on really expensive conferences. But I probably thought I wouldn't get an invite back if I said that. So these are my three takeaways. Any questions? No questions at all. Somebody help me out. Fraser, ask a question. Ah, good man. Oh, sorry. Did it carry on?

So, yeah, you mentioned the burning multiple from 1.5 and I was wondering like.

Is that a constant in all stages?

Because I imagine that like series cd 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 multiple should change. And I think the answer to that is probably yes. As you grow, you know, when you're, when you. 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 about 1 1/2 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 0, but you should certainly be lower than 1. I would agree with that. Any other questions? Yes, Rocket man by Elton John.

Cheers for that. 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 only about saying just because your customers love you.

Does not mean you have product market fit.

And there was another point you raised in your deck.

But the problem is when you're early.

Stage startup, like obviously that's when you're.

Really 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? It's a really good question. I mean the one thing I think that I think defines product market 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? Are you trying to educate them? Because this is where I think banks have a quite often they're the people that always love a proof of of concept. Anyone worked 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 have so I'm quite big on the sort of sales flywheel. I think I don'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 additional and.

Cool.

Finished ahead of time. Thank you very much.

Good baby. Good baby. Good baby. Good baby. Satan. It. It. Sam. Good baby. Good baby. Good baby. Good baby. Good baby.