The 5 Metrics You Should Track to Maximize Your Company’s Valuation with Tomasz Tunguz

Great. So welcome to the first session of SaaSTR. My name is Tomáš Tengus. I am a managing director at Redpoint, and today I want to talk to you about revenue design. And the goal of revenue design is to, to help founders understand the way that the markets value startups and how to improve that value. Just a quick background on us. I work at a firm called Redpoint Ventures. We invest anywhere from about $1 to $40 million across rounds. 75% of the companies we invest in are as-a-service companies, and we're based in San Francisco with offices in Woodside. And the most important thing here is if you're starting a company, please do come see us. We'd love to talk to you. We've been fortunate to partner with lots of different successful companies in the last 5 years. We've worked with 28 unicorns and generated more than $110 billion in IPOs and M&A. Those companies include incredible businesses like Snowflake, Stripe, Twilio, HashiCorp, Looker, Zendesk, and many others. So let's jump right to it. What I'd love to cover to you— to share with you today is how investors look at your business and how to increase the value of your business. So the way that the— the first place to start actually is how should you value a software company? And this is something I've spent the last 10 or 12 years trying to understand at a very deep level, and I'd like to share those insights with you. Pop quiz, hotshot: how much is this business worth? Imagine you have a hypothetical company that's at $100 million in annual recurring revenue, growing 70% a year with an 80% gross margin. It has a sales efficiency of 0.8, a net dollar retention of 125%, and a cash flow margin of 5%. If you have an idea, put it in the chat box here. Let me know. We'll get to the answer at the end. The goal of this session is at the end you'll know exactly why this business is worth X, and I will walk you through what goes into it. So please ask questions along the way. I'd love for this session to be interactive, and also know that around 1 PM Pacific we will have 30 minutes of extra sessions for a networking session that we'll be doing later today. So at a high level, the mentality that most investors look at companies— there are two different mentalities that investors will look at companies. The first are a value-based mentality, where I look at a company like, and I determine its value based on profits. The second mentality is I'm going to look at a company and value it based on its growth. The vast majority of companies in the world today are value companies. If you look at most publicly traded businesses, they're valued on profits or EBITDA. But the truth is all startups are valued as growth companies, and that's because they're some of the fastest growing companies in the world. So the question is, when you're looking at a growth company, it's not generating— most of the time it's not generating any profits. So how do you value it? Well, imagine we've got another hypothetical business and we look it up on Google Finance and we realize— and we see that it's got a $4 billion enterprise value. And it has $200 million in revenue. What we can say is it's valued on a 20x EV-to-revenue multiple. And that's the way that most businesses are valued, most growth companies are valued. Let's break that down. So the $4 billion enterprise value, the enterprise value is the market cap minus the cash plus the debt. And the reason that we look at enterprise value is to make sure that it's sort of a level set. We want to remove the cash from the business because some companies have lots of cash, and some companies have less cash, and so we subtract it out and we add the debt. Then we look at the revenue and we create this multiple. And so every business, every software company of note that's at scale is valued on a multiple basis, on a growth multiple basis. And this is just as much true for the private markets, the areas that we invest in at Redpoint, as much as the public markets, the shares that you can buy on Robinhood. And to give you a sense, as of February 23rd of this year, This is the distribution of the software companies' multiples. The mean is 26 times EV to forward revenue and the median is 23 times EV to forward revenue. So EV is that enterprise value number that I mentioned before, and forward revenue is the projection of the next 12 months of revenue that that company will generate. So in other words, if I've got a company that's going to do $1 billion in revenue next year, if I'm valuing it as an average company, it will be worth $26 billion. Great, so now that we know, have a sense of how the market views software companies, the next and most important question is, if I'm operating a software company, how do I increase that value? Well, that multiple is a single number, but it's underpinned by 5 major components, and these are the 5 largest correlates to that multiple. And over the next couple slides, we're going to be walking through what those 5 multiples are. We'll define them and then walk through examples of how different companies fit into those multiples. So here are the 5 different multiples. This is a— the result of analysis that we've done understanding both the public and the private markets. And we've got databases for private companies as well as public companies, and we run correlation analysis to figure out for that EV-to-NTM multiple, the data that we just talked about, what are the 5 major components that actually go into it? The first is revenue growth. The second is gross margin. The third is cash flow margin, net dollar retention, and the last is sales efficiency. So let's step through each of those 5. To kick off each section, what I'm going to do is I'm going to bracket the numbers. What should you expect? So for a public company, how fast are these businesses growing? And the answer is they spend anywhere from about 14% annual growth to 174% annual growth. That's a pretty big range. Within the private markets, especially this year, we've seen some companies growing at 5, 6, 700%, particularly driven by COVID. Most of the time, the companies at the Series A are typically growing somewhere between 300% to 500%. So let's take a look at two radically different approaches to revenue growth. The first is Snowflake and the second is Atlassian. Snowflake is a cloud data warehouse company that was founded in 2013, recently went public, and is growing incredibly quickly. And Atlassian is a business that's based in Australia, has moved to the US, was started in 2000, raised literally no venture capital, and is also an incredible business. But they couldn't have taken two different— two more different approaches to market than they have. Let me show you why. So both of these companies enjoy a top decile multiple. In other words, their EV-to-NTM multiple is in the top 10%, but they look very, very different. So on the left-hand side, on the left column, we've got Snowflake. The revenue growth at the time of IPO was 121%. Its sales efficiency was 0.82. The net dollar retention was 160%, but its profitability, net income margin, was -132%. Cash flow margin, -67%, and gross margin, 62%. So if you look at these numbers, the takeaway is Snowflake raised a huge amount of capital, many hundreds of millions of dollars. They spent that capital in unprofitable growth, but have achieved one of the most incredible revenue growth metrics at the time of IPO of any software company. So a big burny SaaS company. Atlassian, on the other hand, At the time of IPO was growing 48%. Sales efficiency was 2.6, and we'll get into what that number is, but it's a really important difference here. You can see that the sales efficiency of Atlassian is almost 3 times what Snowflake's is. The net dollar retention, this is a 132% number, which is— comes from the last 10-K because they didn't publish it at the time of IPO. The net income margin at 2% means the business was profitable compared to Snowflake's very unprofitable year. And the gross margin is slightly higher. So on the left-hand side with Snowflake, you've got a software company that raises lots of venture capital, spends lots of it to grow still efficiently, but is running a very unprofitable business today. And on the right-hand side, you've got a company that's super capital efficient, growing at a little bit, at slightly slower rate, but still both of these companies are valued within the top decile. And so the net of this slide is that you can build a company into— these are two extremes, right, of big, burny SaaS company and then a super capital-efficient SaaS business. And so the question is, for your business, which one should it be? If you double-click on these, the competitive dynamics here, there are a couple of different attributes that might guide you in different directions. Snowflake, when they launched, they were competing with some very large behemoths. They were competing with Google and Microsoft. And so in order to become relevant, they really need to grow very quickly. Atlassian, on the other hand, started right around the dot-com era, based in Australia. Maybe the venture capital environment wasn't as supportive as it is today, and so pursued this more capital-efficient market. When you think about your business, keep these two contrasts in mind. And if you want to learn more about how Snowflake built that business, there's a session tomorrow led by Denise Pearson. Who actually ran— is running as the CMO at Snowflake, and she can tell you exactly how she did that. She's absolutely incredible. So moving on to the second component of this multiple, it's the gross margin. And just to bracket it again, gross margin spans anywhere from 52% to 91% for publicly traded companies. What is the gross margin? Let's define it for a second. Gross margin is the revenue of the company minus the cost of goods sold. And what goes into cost of goods sold? Well, for most software companies, it's on the top left, it's cloud computing costs. What do I pay GCP? What do I pay AWS? What's my Azure bill? The second big component that you find within software as a service companies is customer success. A lot of companies will just use this rule of thumb that half of their customer success costs go into COGS. Less common, you might see professional services, So this is, hey, can I customize the software for you, my customer, or can I train people? And then the last is licensing software. If I'm taking a piece of software and embedding it within mine, then I have to pay that person who's offering me the software, and that gets embedded into my COGS. So here again, two different models. Let's contrast Tableau and Twilio. Tableau is a publicly traded business intelligence company that was acquired by Salesforce for around $16 billion, been around for 20 years, was founded out of Stanford. And then the second business, a company called Twilio, which offers very simple telephony via API. And you'll see that the gross margins of these businesses cannot be more different. So Twilio's gross margin is 51%, and Tableau's gross margin is almost twice as much. I picked two different examples to show the extreme difference that you can see. And the reason for such a big difference is that Tableau isn't really an as-a-service company. In other words, at the time I collected this data point, most of the software was actually running on somebody's computer, and so they're not paying for any hosting, and so there's very little that's actually going into COGS. And so the metal that they're running on is somebody's computer as opposed to an AWS instance. Twilio has two different major components of their COGS. The first component is They're an infrastructure as a service vendor, and so there's a big chunk of their workloads that are run on cloud data centers. And then the second part is they actually resell telephone carrier minutes. So if you're sending text messages, they're not the ones actually providing the text messages. They're partnering with the carriers in order to resell those messages. And so every time a message is sold, they have to go and pay that carrier. And so that's why the gross margin is at 51%. So when you think about gross margin— oops— when you think about gross margin, the most important thing to look at is whose metal are you running on and how do you optimize that metal. And for most, most software companies today, figuring out how to, how to maximize the cost on the cloud computing service is critical. And tomorrow, again, Jeff Lawson is actually speaking with Jason M. Lemkin, and he will walk you through exactly how he built that business. And so if you'd like to learn more That's a terrific session to follow. The third of the five metrics is the sales efficiency. And what we observe in the public market today is sales efficiency spans anywhere from 0.14 to 1.15 for public companies. There are lots of— well, this is my preferred definition for calculating sales efficiency. Different people actually have different takes. This is one of those metrics that isn't a GAAP metric. There's no standard for it yet. But this is the way that we measure it when we look at companies. So what you really want to look at is this third line, which is the sales efficiency is the gross profit in period 2 minus the gross profit in period 1 divided by the sales and marketing in period 1. And what does this tell you? This tells you if I put in $1 in sales and marketing spend, how much gross profit am I going to generate? And I can do that on an annual basis. I can do it on a quarterly basis. I can do it on a monthly basis. The greater that number, the more efficient my business is. So if you recall the first slide, Aladdin was a 2. So for every dollar of sales and marketing spend, they generated $2 of gross profit. That's a pretty incredible machine. And the way that most businesses use this is they actually invert it. So they, They take 1 divided by the sales efficiency multiplied by 12, which will give you the payback period in months. In other words, if I pay to acquire a customer, how many months of that customer paying me will offset the cost of that customer acquisition? And for most publicly traded companies, that span is between 14 to 18 months. It tends to be higher for higher contract companies, higher contract value companies, and less for sort of SMB. And in the consumer world, it's like 3 to 9 months. Within the SMB world, it's something like 9 to 14 months. And then with the enterprise, it's not uncommon to see 18 to 36 months sometimes. So if you look at ServiceNow, they're up on the higher end. This is the most— so I've done a lot of analysis of different software companies. This is the most beautiful sales efficiency chart I've ever seen. It's called a smile chart because when you look at it, it looks like it's a smile. This was an analysis of Shopify in 2016. And what's going on here is you can see that the sales efficiency for Shopify was around 150%. It dipped to around 100%, then it increased in 2015 and to 2016 and is now, at that time, was close again to 150%. Why is this so amazing? Because as this business grew, it actually became more efficient. It's very rare to see that. What's been happening is that Shopify has been amalgamating all these different stores and the reason that the sales efficiency has actually increased is because of the cross-sell of different products. But it's an incredible money-making machine. And there's another incredible money-making machine, and this business has not gotten enough praise, which is Duo Security. We were fortunate enough to be investors in this company. They have sales efficiency metrics that are really off the charts. And the man who deserves a lot of the credit is a guy named Jeff Wyss, who actually ran the go-to-market engine there, and he's speaking later on at this event. So please do take the time to go and ask him. He was at Zendesk before, which is another also a Redpoint company, built an incredibly capital-efficient go-to-market strategy with sales efficiencies north of 1 for both of those businesses. So he's a terrific expert to talk about that. But if you think about what's going on within the sales efficiency game plan, if you're an operator and you're trying to figure out, hey, what are all the different things that I need to balance to get that efficiency, there's actually quite a bit going on. So the first is, how fast do I want to grow? And the second part of it is what's the sales motion? Am I PLG versus SLG? If I'm product-led growth, it's gonna be very different than sales-led growth. The third thing that's gonna go into this sales cycle, if I've got a really long sales cycle, it's actually much harder to get to a larger sales efficiency just because of the field sales that I need to deploy. The fourth is the net dollar retention, which is probably the most single powerful metric in SaaS just because it's like a, interest rate for your bank account, payback period and gross margin. The one that I do wanna double-click on, which is definitely super important is PLG versus SLG. PLG is kind of the new hotness within SaaS and it's something that's been around for a very long time, but I think given the monotonically increasing cost of customer acquisition in SaaS, because a lot of the channels that people are using to acquire customers have been saturated, PLG is now starting to become more and more important. In fact, I was talking to one of our entrepreneurs in residence yesterday, and he and his partner did an analysis and found that something like 50% of the current unicorns are PLG. And the important part there is actually the combination of the PLG motion or the product qualifying motion with a sales force. And those businesses actually tend to be far more efficient. And if you want to hear more about that, there's no one better to talk to you about it than Ivan Zhao, who is the founder of Notion. I remember walking with Ivan through the streets of San Francisco. We talked about Art Deco architecture. He's an incredibly creative guy and just has built an incredible business through community. And so if you want to hear about that, he's speaking tomorrow. So moving on to net dollar retention, as I mentioned, I think this is the most important metric for a business, just because imagine you have a bank account with a 58% per year interest. Within 2 years, you have doubled your money. And so it's just— if you look at net dollar retention across publicly traded companies, they span anywhere from about 100% to 160%. Again, this is a metric that's not a GAAP metric. They— but the way that conceptually you should look at it is what is the value of a cohort today versus what they paid me last year? There's actually a really interesting statistical phenomenon called Simpson's paradox that exists here because what I can do in order to calculate NDR is I can say, I can take a look at the cohort today in January versus last year in January and figure out what the change is. Or I can take a look at the changes over the last 12 months and then average that. And you end up with this thing called Simpson's paradox. That's a real fun aside. I put the link there if people are curious. But at a high level, the whole idea of NDR is, How quickly is my bank account growing? How quickly are my customers going to pay me? And the levers that we see in market to improve NDR are— they fall into two different buckets. The first is products and pricing. So one important aspect of this is the customer segment. Are you selling to SMB, mid-market, or enterprise? And I'll show you on the next slide that there's actually one segment you have far better NDR than in others. The second, as we talked about with Shopify, is can you cross-sell adjacent products? The third is, do you have a pricing model that lends itself to upsell? Do you have a flat fee? Do you have an infrastructure as a service fee where you pay by the unit, like a Snowflake where you pay for credits? It's really important to get that pricing structure right. The, the second category is within customer success. So the people that have the best NDRs do very proactive account planning, have an upsell motion, and then are very good at cross-departmental sales. Okay. So as I mentioned, so we ran a survey across 600 companies, including very small startups all the way to publicly traded companies, and we looked at the NDR based on the ACV, the average contract value. And what you find is within the SMB, the SMB companies actually have smaller rates of net dollar retention. And so the way to read this chart is If you look at the SMB column, the bright red, 38% of the SMB respondents within this survey said that their NDR was between 80 to 100%. And the reason that it's low, one is they tend to have higher gross churn, so the number of customers coming onto the platform and leaving tends to be in the 15 to 25%. But the second is there's less headroom to grow. And if you look at sort of the heat map of the chart, you can see that about a third of the enterprise respondents actually had NDRs of 100 to 120%, and a quarter of them had 120 to 140%. To put it into perspective, the top decile of companies will have something like 125% plus NDR, and the very, very top have about 160%. Okay, we got a couple questions coming in. This is going back to cost of goods sold. So when we define cost of goods sold, the question is, if 50% of customer success is in COGS, where is the allocation to the other? 50%. That's a very good accounting question. It's in sales and marketing. Most companies will put it in sales and marketing. And then another question says, let's see. Actually, we're going to go back to these at the end because they're a little bit out of order. I do want to tell the story here now, which is a tale of one market segment with three different NDRs. So there's a category of software that's called the application performance monitoring space. And it's software that allows engineers to figure out what's going on within their own software. Is it working well or is it not? There were 3 companies that filed S-1s and 2 that actually went public. So the first was New Relic, founded by Lucerne. The second was AppDynamics, which is founded by Jyoti Bansal. And then the third is Datadog. And they went public in, in actually this order, or what they filed their S-1s in this order. New Relic is still public. AppDynamics was acquired by Cisco on the eve of their IPO. And then there's Datadog, is still a publicly traded company. And what you find is New Relic's net dollar retention at the time of IPO was 115%, AppDynamics was 123%, and Datadog's is 151%. Now, Datadog's net dollar retention is 22% better than its peers, but what does that mean? Well, it turns out that 20 percentage points of net dollar retention means that in 5 years, the business will be twice as big. So without doing anything else, assuming everything else is exactly the same, Datadog's business will be at least twice as big within 5 years just because of their NDR. And so that, that NDR advantage is absolutely massive and it's hard to overstate. And if you wanna hear more about it, Jyoti is coming in to speak as well. Cool, moving on to the last and final metric, this is cash flow margin. And cash flow margin is— it's a metric that's— we'll define it in a second, but the span is -94% to 41%. The way that you define it, here's the formula, is the cash flow from operations. In other words, what is the bank account? You can imagine a company's bank account at the beginning of the year and the end of the year. What does that bank account change look like? Did it have more money in the bank account? Does it not? Excluding financing. And you divide it by revenue. The more cash the business generates, the more the business can invest in growth. Less cash means in order to finance the operations of the business, you have to raise venture capital or debt and you're gonna be diluted. The reason that this is so important is this is how business works, right? We have this cash conversion cycle, which we spend money to acquire a customer, we acquire that customer, sometimes, you know, 30 to 60 days later, we receive the money. The faster I can get this cash conversion cycle to work, the faster I can take the cash that I've got from the existing customers and use it to acquire new customers. And this is why the Salesforce innovation of the contract prepay is so important. So let's take a look at Zoom. Zoom is best in class when it comes to this. They generated an incredible $160 million in free cash flow, and their free cash flow is actually growing at 102% per year. So it's a massively profitable business, and that's important, But what's more important, particularly for understanding how to value this company, is the amount of cash that they're getting from the customers is growing incredibly quickly, and they can take that cash and use it to acquire new customers without diluting themselves. Great. So let's go back to that original question. That business, what is it worth? So we walked through those 5 different components, and if you put those together, It was revenue growth, gross margin, cash flow margin, net dollar retention, sales efficiency. The number is actually, as of a month ago, was $3.9 billion. Today it'd be a little less just because of what's going on in the public markets. So the question is, if you look at your business through the lens of those 5 metrics, what could it be worth and what can you take from the sessions at SaaS to Build to apply to your business to increase the value? Fantastic. Thank you very much. Let's jump into some questions now. So we've got one question, which is, "At the bottom of the range of a sales efficiency of 0.14, is that an acceptable number?" So let's go back to that slide. Let's see. Here. So a 0.14 sales efficiency is a really tough business to invest in. It probably means you've got a 7 to an 8-year payback period. And so if you had an absolutely massive ACV, I'm thinking $1 million plus, it might be an interesting investment to make, but on the whole, no. The answer's a flat no. 0.6 is probably— When we look at companies, we might invest in a company at 0.6, maybe 0.5, but we're really looking for companies 0.8 to 1.1. Another question, is there a piece of software that calculates all this stuff for you? That is a good question. I think SaaSOptics is probably one of the better platforms. I don't know if they calculate all these metrics, but I have heard of a bunch of portfolio companies using those. Okay, so how do these metrics change for vertical SaaS companies? You've got horizontal SaaS companies like Salesforce that sell software to everybody, and then you've got vertical SaaS companies like Encino or Veeva that sell to one particular industry segment, like in Veeva's case it's pharma, what do you typically find? So I didn't break down these results, this is cross-industry, I didn't break down the results on a per-segment basis, but what you do find is that the vertical SaaS companies and the ones that we've looked at in the private markets tend to be far more capital efficient, their sales efficiencies tend to be off the charts and they tend to be far more profitable. In other words, they've raised— they look more like Atlassian. And the reason that tends to be is they just have far better product-market fit because instead of needing to sell to pharma and manufacturing and healthcare and consumer packaged goods and IT, they're picking one and they're building software just for them. So on the whole, you would expect that most vertical SaaS companies would be far more capital efficient, have greater sales efficiency on the whole. Might be an interesting analysis to do. All right. What is your point of view on the B2D bottoms-up growth for developers? What gross margins should you aim for? So the business-to-developer, the B2D go-to-market motion, so there's 3 different go-to-market motions for as, well, for software companies. There's a B2C motion where you sell directly to like a prosumer, And there's a B2D motion, which is you sell to a developer and then the developer brings it into the company like a Heroku, and then the VP of engineering decides to buy. Sort of this two-pronged pincer movement. And then there's the B2B motion, which can look either way, either like a direct sale or then the pincer motion. We really love the B2D motion. We've invested in 17 open source companies in the last 5 years. For those gross margins, you would expect a pretty typical gross margin for everybody else. It's really gross margin for most software companies is function of how much do I need to spend on cloud computing. Where you do find a split is companies that are deploying machine learning. So like if you're doing speech recognition or image recognition, you'll find those gross margins are kind of in the 50 to 60% range because of the cost of operating those GPUs. But most software companies are going to be in the, in the 65 to 80%, depending on how much cloud compute they use. Okay, Jason M. Lemkin asks, on the power of cash, Zoom is now up to 50% monthly invoices. How hard should you push for edge to get to annual and longer payments? That is a great question. So what we found, you should push hard. A couple of our portfolio companies have sort of pushed against this suggestion. And what we found is with a simple SPIF for the salespeople to get to annual or the elimination of the possibility of quarterly or monthly, you can move pretty quickly, like within a quarter or two. One of our companies put in a SPIF within a for getting to annual PPAY. And then the next quarter, 93% of the bookings were annual PPAY. And the power of— and I'd be curious, Jason, if you've got a different point of view, but the power of that cash prepay is you're basically borrowing money from your customers at 0% interest. So why wouldn't you?

Yeah, I think it's— I think you're better with the data. I think it's super interesting, the power of the SPIF. That might be the most compelling data there, right, is changing behavior. I think I've had a lot of revelation the last 2 years on SMBs because SMBs are back. That could be a whole topic. SMBs, like when you and I started, we loved SMBs, we loved product-led growth, but some of these markets were just a little bit too small and enterprise seemed early. And I think the fastest growing SMB investments I've made let customers pay the way they want to pay. And as soon as the salesperson adds friction to the process, you can have an illusion. You can have an illusion of progress because you don't see the deals that you lost, right? So I worry that the specificity of those anecdotes in mid-market or larger obscures lost deals with SMBs.

Yeah, it's an important distinction, particularly with that product-led growth motion. What you find is like at Expensify, you know, and Atlassian is kind of the same way, there are no salespeople. People use the product for the free motion and then they contact customer support or customer success. And then upgrade. And so you're not going to spiff the CSM in order to get to that annual prepay. So that's a really good counterpoint. Really, really good.

Maybe I want to add, hi, this is Alex, capchase.com. It's a great company for people that might struggle moving from monthly to annual, who basically enable SaaS companies to move to a cash flow that is more upfront. Obviously you have to pay for it. So there's a margin, but it's a very slick integration into Xero, into everything else. If people want to have a look at it. Capchase.com. I'll post it in.

Cool. Thanks.

Would you invest, Tomas, in— it's a related point. I don't want to monopolize the conversation. Would you invest in an SMB SaaS company where the NRR wasn't close to 100%? Or at least at scale, at least by the next round? Where do you think that cutoff is related to your prior slide in this point?

The NDR is not 100%? Yeah, we— if it's a prosumer— so we have this debate. So there's this division in the world, which is an arbitrage— this is like, is this a prosumer business? Like, am I selling to an individual? And if I'm selling to an individual with a high enough price point, then I'm going to look at it like a consumer business and I'm going to expect the NDR to be less than 1 and I'm going to expect the payback periods to be 6 to 9 months. But if I'm selling to like an SMB, even a VSB, like a very small business, a 1 to 5 person company, then I don't think we would invest with less than 100% NDR.

Got it. It's a different, it'd be fun to get your data sometime because I'm with you, right? And I've found that the folks even selling to VSBs that make it a top 3 goal, they find a way, the best startups, right? But the motions are so different because you're still gonna have organic churn, right?

Totally.

It's a lot of work when no matter, even for that NDR of 100, if you have 3% logo churn per month, it's a lot. It's a lot of work to hit even 100%. It's the exact opposite of your Datadog example, right?

Yeah, yeah. And so that's why logo churn matters a lot. And so within like the VSP, you really want to be below like 15 to 20% a year. Otherwise, like if you're at 3% a year, you're replacing more than 40% of your customer base every year.

Yeah, I think if you sell the individual, like if the low end, if you're selling to single shops, if you're selling to single Shopify stores or restaurants though, I think you're— I mean, maybe that's a bad place for venture, but you can't have 1% logo churn because the businesses just go under, right? It's not mathematical. Like the grocery stores on Shopify are not gonna have 90% logo retention.

Yeah, no chance. Okay, cool. Eugene asks, if my startup has zero revenue, how do I calculate the price? So the only way to calculate a price is to run an auction and go through a fundraising process, and then the market will set a price. Otherwise, Since you have no metrics, it's impossible to come up with a price. Okay, Jason asked another question. Are more SaaS companies getting funded or is it more concentration within the winners? The data is confusing there. So the answer is the number of SaaS companies that were financed last year declined by about 15% year over year. There are fewer companies getting financed, but the ones that do get financed are getting more and more money. And I saw a data point from SVB that last year, something like 50% of all the venture dollars went into unicorns. So there's a huge concentration of capital, and that's also true within SaaS companies. And the net result of that is the multiples have gone up. The most expensive multiples that we're starting to see in the Series A, B are 50x, 100x, sometimes 150x, which is— 5 years ago would have been absurd, but here we are. Cool. Okay, more questions. Anshuman asks, can you expand more on how B2D motions working in AI and ML work towards these metrics? Yeah, the one that's the most for B2D companies working with AI and ML, if you're, if you're running models and managing GPUs, the biggest thing that we've seen our portfolio companies do is bring GPU into their own data center. Because it turns out that at scale, the cloud GPUs are super expensive, like 50x more expensive than buying your own NVIDIAS and running them. And so you could do that. There's also pre-purchasing of GPUs and sort of cloud spend management. Those would be the two things that I would really look towards. The other note that I will make on B2D companies is, as Jason M. Lemkin, we were just talking about before, the way that we view B2D companies is more like a consumer business where if you're going to sell to developers, you're really going to want to think about it like, I just want as much— I want to think about it as a social network. I want as much usage as possible, and we're willing to bet on the monetization coming later. The same thing with Facebook. You want to have as many different people using the network, and then at some point you'll switch on monetization. But if you've got the distribution, most investors are willing to give you credit for it. Okay. Inbound question. Do you look at growth-adjusted multiples as a metric for making investment decisions? So if you were a public market investor, I think you definitely would. And there's like the PEG ratio is something that a growth investor might look at, a public market investor, but in the soft, in the early, in the pro, like at the Series A, no, because we just want to be in the fastest growing companies. And so it's absolute growth that matters rather than relative growth. Is the valuation of Hopin justified based on these parameters? Good question. I don't want to comment on specific companies. Let's see, we will link to the presentation. Oh, I can stop sharing. Okay, so people can see my face. Let me do that. I'm just ripping through these questions here. Do you have a formula to convert the 5 parameters into evaluation multiple? Yes, publishing a blog post this afternoon or tomorrow morning that will have that multiple so you can plug it in. You should know that those correlations and those numbers actually change. And so what I'll do in that blog post is actually show how that formula has actually changed over the last month or two, just given what's going on with interest rates. In the financial services world, enterprise clients often ask for on-prem and private cloud implementation. Does that model work in your experience? Yes. So this is like a big debate. This is a big debate within the startup world. Because of sort of where we are in the development of cloud or the adoption of cloud. So it used to be like if you were selling to those big financial services companies, you would need to be on-prem and they would require it and it was for security. And now those sort of big banks are starting to move, but very slowly to cloud. And so a lot of the companies selling It's sort of like enterprise solutions have to go to market with both the on-prem product and the cloud product at the same time, but they only want to have one because it's sort of having two different products, two different go-to-markets really complicates things. So I think if you're selling to them, you absolutely need to, or, you know, what you might want to do is sort of wait like a year or two because we're starting to see, we're starting to see sort of even the laggards within the financial services industry move to cloud, but The answer is probably yes. Cool. Let's see, how can we get the slides? We will get them to you. I don't know the precise way, but we will get them to you. Barry asks, what advice would you give to a CEO with a company that has great metrics but has bootstrapped and hasn't stepped on the gas? The company is making a tidy profit but is now considering just enjoying the profit or really going for it. So my sense is this is really a personal decision, how you want to spend your time. The second you take money from investors, like the conversation that we have with founders when we invest is, hey, every time there's a decision to go small or go big, we're always going to want to go big. And so if you take money from VCs, you have to be comfortable with that. And there's a lifestyle that's associated with it, and there's going to be a bunch of risks that's associated with it. And so It's basically just a call on how you want to live. It's not really a broad answer, I'd say. Yeah. Cool. I think those are all the questions. We actually do have a few more in the queue if you want to take them. We've got a few more minutes if you're open for it. Oh yeah, for sure. Okay, let's see. Some of these metrics seem inapplicable to enterprise sales with very few Very few high-value contracts. How do you view this? Okay, so the bigger you are as a business, the more these metrics are applicable. And that's because the number of customers that you're selling to increases. If you're like, if your ACVs are like a million bucks and you're at $15 million in ARR, you have 15 customers, looking at a lot of these metrics is going to be tough. One, because the volatility in bookings on a quarterly basis with ACVs that big is going to be huge. And so, you know, I look more like sales cycle and payback period at the beginning of like really large ACV deals as opposed to sort of more of these. And then once you get to like the $20 to $50 million in ARR, maybe start paying attention to these, particularly for those super large ACV businesses. How well do you usually know the potential exit for an investment target market before investing? I think we do occasionally talk about— The way I frame it is most of the time when we invest in software companies, the buyers are obvious. Every once in a while, and then IPO if the company's big enough, every once in a while we will come across a company where the buyers are not clear and then we will do analysis on, is this a business that private equity would buy or Are there sort of like vertical-specific companies that would buy this? It tends to be much more— we'll focus on that more in vertical SaaS than we will in horizontal SaaS, just because the universe of buyers in horizontal SaaS is so much bigger. Okay, what's your feeling of investing in SaaS B2G? I'd love to— I don't know, does anyone know what B2G means? I've never seen that acronym before. Okay, let's keep going. Feel free to clarify. We'll try to answer the question. Business to government is B2G. Oh, selling to the Fed. Okay. Yeah. So within the last 5 years, the US government has become much more receptive to selling, to buying from startups, particularly the Air Force. And so we're starting to see many of our companies have significant deals there. The sales cycles are really long and the market is quite different. The motion is quite different because you're typically having to go through a consultant in order to sell, somebody who's got an established relationship with the government that you can sell on their paper. But a couple of our companies are having many, many multimillion-dollar deals there, and you've got the whole next-generation defense contractor space that's also growing really fast. So I'm a long-term bull on that space, selling B2G. Startups originally got their start in the Second World War selling to the government. I think it's going to come back, so definitely positive. Are the 5 measures that we talked about in B2B SaaS the same for B2B marketplaces? No, they are not. B2B marketplaces, let me see if I can just off top of my head, the revenue growth metric, the analog is going to be GMV. So a lot of marketplaces are valued on GMV instead of net revenue. The, so the next, the next most important metric is the Rake or the fraction that you, of the GMV that you take, and you typically see, which is the gross margin, those are the same number, you typically see 5 to 60%, and that's a huge span, but most people are kind of concentrated between the 10 to 15% range. We have seen marketplaces, particularly labor marketplaces that are in the 60% range. That's super important. The other twist on the B2B market place model is that you have, since you're in a market, you're the central market maker and you have a buyer and a seller, you have customer acquisition costs on both sides. And so you got to calculate that and put into your sales efficiency. But I would caution anybody to use, I would not use SaaS metrics to look at B2B SaaS marketplace. It's going to steer you in the wrong direction. And that's probably a good post, but a pretty deep sort of well to go down to. So let's keep going. But on the whole, I would not use SaaS metrics for B2B marketplaces. Let's see, would you invest in a clear number 2 or number 3 given the vast growth of cloud? The answer is yes, particularly in certain spaces. So if you look at, you know, I mean, who would have thought that Salesforce would be like a quarter of a billion dollar company, right? Would you invest in the number 2 or number 3 CRM? Yes. Would you invest in number 2 Zoom? Yes. 'Cause they can be massive. And you know, like we went through that example of AppDynamics, Datadog, New Relic. Datadog with the last entrant is gonna be the biggest, right? So for sure. Okay, I think we got 2 more minutes, right, Lindsey? That's correct. Okay, for B2D motion, how many developers do you look for a Series A and a Series B? It's not a number of developers, it's a sense of momentum. Sometimes that's quantified by GitHub stars, sometimes that's quantified by the number of pilots that people have with different customers or reference accounts. You can, you know, we will get excited, as excited about a company with like 10,000 GitHub stars in like a week, like Coder.com did, as we will like an open source company that has like 3 really amazing reference customers. So. It can be either one of the two. Okay, Tyler asks, of the 5 components of the multiple, which ones are more important? Stay tuned for the blog post. I will put it out later today. And then Jordy asks, is there a formula? Yes, that will be in the blog post later today. So I think we should end it there. Jason, Lindsay, thank you so much for welcoming me here. Really enjoyed it. It's such a privilege to kick things off. And thank you to everybody for answering your questions. Look forward to seeing you at 1 PM for some more conversation.