Battery Ventures’ VP Brandon Gleklen on The Latest in SaaS Metrics (Workshop Wednesday)

people are joining. Welcome. All right, welcome everyone. Feel free to turn on your cameras as you're joining. We'll just give it a minute while people continue to enter. Excited to see you all today, and thank you for joining us. All right. Welcome everyone, and hello, SASR community. Thank you for joining us. We are thrilled to have you back at Workshop Wednesday. Reminder, this is every Wednesday at 10:00 AM Pacific. We will be here week after week to share detailed, interactive, and hands-on workshops. We'll bring along a SAS expert to walk us through some content that they are an expert in and kick off the interactive discussion. You will have the opportunity to interact with the speaker directly. So feel free to turn your cameras on, get your questions ready, because we are excited to see you all today. As well as connecting with the speaker, you are welcome to connect with your fellow community members. We want this to be as interactive as possible. This week we will hear from Brandon Glecklin, Principal at Battery Ventures. We will be discussing the fall of the metric monolith. Exciting stuff. Again, these sessions are as interactive as possible. Please have your questions ready. Feel free to come off mute to ask them, or if you want me to ask them while they're in the chat, that's totally cool. Whatever you're comfortable with. So to kick things off, let's ask Brandon a few questions to get to know him better. All right, Brandon, so what is one of your favorite investments you or the firm has made in 2022?

Well, first off, Caitlin, Amelia, whole SaaS team, thanks so much for having me. This is a presentation I gave at the SaaS Annual, and it's really cool to be invited back to give it to this group. And thanks everybody for giving some time in their Wednesday to do this. In terms of investments we've made so far this year, obviously, I love all of them, but I'll talk about the one where I actually, I just had the board meeting last week, or last week, yesterday, which is a company called Compt. The website is compt.io. The CEO is Amy Sperling, and she's like really, really phenomenal. We've done a lot of investments, I would say, over the last few years that are related to like what I think of as being kind of the easiest macro shift for us all to think about, which is kind of the shifting nature of work, you know, people working remotely. I can talk about so many investments Battery has made where that's been sort of at the core of, you know, why that exact investment was interesting. But This one specifically looks at benefits. So for example, you know, for the folks on the call, you probably do things like in-office lunches or like a local gym discount. These are a lot less relevant for a kind of a global, fully distributed workforce. And so what Compt helps companies do is set up flexible stipends. Say you want health and wellness stipend, or you want people to be able to eat meals, you know, local to them, even though they can't come into an office to eat lunch. They just make it really easy and tax compliant and very user-friendly for people to be able to set up these stipends. So really cool company being used from everybody from, large accounting firms to exciting startups and unicorns and all that. And Amy is just like a force of nature as a person. So comps.io, and would highly encourage everybody here to check it out.

Awesome. Who doesn't love benefits? Great answer. What has most surprised you about venture capital this year?

I would say the biggest surprise, and in some ways it's not a surprise, but it's just been really awesome to see, is just I think the resiliency of the founders that we work with. People give the metaphor of going from peacetime to wartime. And I think for a lot of the founders that we work with, maybe for some of the younger ones, even their whole professional career, they don't know, they've never been through an exact environment like this. And the way that people have been able to shift strategy, shift focus, and kind of reorient on, we're talking about metrics in this presentation. Just operate their companies in new ways. I think the speed in which people are, have been able to move and adjust has just been really awesome to see. I think it's been a really big year of growth for a lot of people in this ecosystem. Like, you know, building new muscle, learning to do new things. And so I think the speed with which that's happened has been really, really awesome for me to see.

Wow, agility, growth, and resilience. What a great way to kick things off. Our last question before I hand it over to your presentation. Who is one of your favorite co-investors?

Yeah, so this is a hard question too. Like, I really like, love and respect so many of the folks that I work with. But when you gave me a hint that this could be a question, the first person that came to mind is Sarah. Sarah was a GP at Greylock most recently. We work together on an investment company called Shortcut. Shortcut's kind of a Jira killer is basically how I would describe it for software project management. But the reason I picked Sarah is we have a very small board. It's 3 folks, me and my colleague, Niraj, and Sarah, all working with Kurt, the CEO. And so it's a very small room. It's, you know, you can't get lost, right? You know, I have some other boards that feel a little bit more like, you know, there's like, you know, 8 investors that get invited and everybody maybe says they're one thing. In that small of a setting, you know, everybody's kind of constantly contributing and you have to show how flexible you are across, you know, from whether it's R&D or sales or kind of all the different functional units. And she's just one of the people that whenever she speaks, I listen very carefully and I learn new things every time I get to chat with her. And she's got a new fund called Conviction. So she's really phenomenal and I feel lucky to get to work with her.

Wow, what a great compliment. Well, thank you for indulging some of our quick questions to start things off, but I will hand it over to you because I know you have a lot to share with us.

Yeah, for sure. Well, again, thanks to everyone, and definitely encourage folks to keep this collaborative, you know, chime in with questions or put questions in the chat. I'm gonna try to go through this pretty quickly so we can get to more kind of Q&A style. But Think of this as generally being like, in the year 2022, what metrics should we actually be solving for? And so maybe a little bit of just historical stuff, the classic disclaimer. Actually, you should start with maybe who Battery is, maybe to get kicked off. So for folks that aren't familiar, we've been around as a firm since 1983. We're currently investing out of our 14th group of funds, combined capitalization of of $3.8 billion, working with over 450 companies. So we've got offices all over the place. I'm based in New York City. We have offices in Boston, two in Silicon Valley, Israel, and London. So very much a global firm doing a lot of work in software. And then who am I? Also useful. So I got started at Battery in 2015. I spent 6 years in Boston, came down to New York. To, you know, help grow our presence here. So we were maybe 2 or 3 people before the pandemic. We're now up to 12. So if any folks are in New York, please swing by and say hi. And here's just a sense of some of the companies I work with on the right here. So Niantic is the lone consumer company I work with. The rest are all B2B software. And in terms of when we got involved, it ranges from, you know, the earliest stages where, you know, founders, you know, signed a term sheet and quit Google the next day, all the way through doing large pre-IPO. I think $4 billion was the highest valuation in terms of us getting involved with a company for the first time. So I'd say I spend most of my time in kind of like the 20 to 200 person bucket in terms of new investments. But quite a few of the companies on here actually have like now north of 1,000 employees. So yeah. So yeah, so let's take a step back as we think about SaaS. So if we go back to— sort of the dawnings of this industry, maybe let's just even go back 10 years or so, there was a shift in our language from talking about GAAP to basically SaaS metrics. And as this model has matured, we've gotten a lot better at saying, actually, these GAAP metrics, right, revenue, gross profit, EBITDA, that we use to measure businesses across sectors, we need to have some consistent language. There's actually a new language that is better for describing SaaS, software as a service businesses. You know, I think for all of us, you know, it's very nice that, you know, when we talk about ARR these days, people know what that is, right? People don't get ARR and revenue and like all these different concepts confused. We actually know, like what all these metrics are at the bottom. And so as this industry has kind of grown up, there's this now this, you know, common language to describe businesses. But this common language has also led to like a common understanding of what, what a great SaaS business looks like. And so Folks can probably recognize some of these thresholds. I like to joke that when I was getting started in 2015, I would make flashcards for these. What is great net retention? What is the right ARR add-to-burn number or gross retention? And it's become kind of what we think of as being the metric model. Basically, you need to have all of these things. And if you don't, are you building a valuable cloud business, or is there something wrong? Wrong with what you're doing. But we actually see this model falling apart. And that's falling apart primarily due to what we view as two of the biggest drivers for value creation today, namely machine learning and product-led growth. So I don't need to spend too much time going through all the different things, kind of like side comments here. But basically, one way to think about it is SaaS used to mean two things. Model for delivering software, right? It's, you're not, you're not getting your software on a CD and, and, you know, you're getting software delivered over the cloud. But also, it was both kind of the, the infrastructure, it was a way that software was being delivered, but it was also a business model, right? Software as a service, subscription software, you know, typically sold by an AE, typically a certain deal size, typically start targeting a certain kind of customer. Um, you know, that first part, for the most part, is right, is still true. Like, cloud software is is a way of delivering software. But the business models are changing quite significantly, right? And things like product-like growth are changing basically how the economics can work for a software business, right, when it's not a sales rep-led model. And things like machine learning, like there are more data-intensive SaaS apps now than there has been in the past. And those companies can look very different than other businesses. Um, the way that we think about it is that, you know, the, the cloud is expanding. We like to joke that like the cloud's like now becoming three-dimensional. Um, there's like sort of this metric model with their approach to building a software business. And, and to be fair, like these companies aren't going out of, uh, out of fashion, right? Top-down sales, right? You know, recurring revenue will never be, uh, out, you know, out of fashion, uh, right? If you can land these big large enterprise deals, right? If any of you guys sell to governments and have 10-year sticky massive deals, that'll never be a bad way to build a great business that can produce a lot of cash one day. But there's now an expansion of models that people can take that still create value, that still— where the potential markets are significant, where the potential to build a large profitable business exists. So SaaS isn't a business model anymore. SaaS is— cloud is now a collection of business models. Thinking about, you know, a metric model, if you need to stick to every single one of these points or your business falls apart, it doesn't make as much sense anymore, we think. And so, you know, where does that leave us, right? We all need goalposts to kind of look at our business, kind of analyze our success, you know, try to figure out if we're on the right path. You know, I don't think that SaaS metrics are going to go away, right? I think measuring, you know, your net add, measuring your retention, measuring your lifetime value, you know, that's never going to go out of fashion. Same way that, you know, good old-fashioned GAAP metrics, right? Right? Revenue, gross profit, EBITDA, you know, one day, everybody on this call will be, you know, public business, and all this is gonna have to translate that back to that one day. But we do think that our language for how we analyze businesses can and should shift. And we should use sort of different terminology to talk about, you know, what, what a great business in the cloud can look like. And so we call that new language, going from SaaS metrics to now being called cohort economics. So basically, the key insight, I think, is just this shifting of thinking of your business as a set of averages to thinking about it as a collection of cohorts or a collection of segments. Said simply, it does not really make a lot of sense to talk about ARR per customer or to talk about retention as an average across your customer base, where your customer base can look very differently, right? Simplest example is people who are swiping a credit card and never have talked to a rep in their life. Versus somebody who's, you know, going through an RFP and who you're invoicing. Those are two very different customers that have very different economics in terms of acquiring them and servicing them. So averaging that out and looking at that, that average point, and, you know, saying this is what a business will be like, it doesn't really make a lot of sense. And so what we're encouraging all the companies that we work with to do, and when we're evaluating new investments, like what we're doing on the back end is like break out your customer base by the different segments that you find to be relevant to your business. So right, pricing plan, industry, geography, go-to-market channel, customer headcount, and analyze your business like through those lenses rather than just looking at, you know, purely just the averages. And then once you define these segments and you're tracking them, you can figure out, well, which ones are working for us and which one should we invest into? And so, you know, here's kind of an example of that. The market's moved, I would say, in the last probably 5 years or so from an understanding of retention from being like a point-in-time metric, like my annualized gross retention is 79%, to think about retention through cohorts. If you look at this, I think you guys can see my mouse, it's much more instructive to say, well, how's retention transforming over time? Are our newer customer cohorts or customers that sign up more recent months, are they performing differently than customers in the past, right? So there's a shift from going up here to over here. But we think, you know, taking it a step forward, right? Thinking about your business as a collection of segments, you know, you can look at it, you know, through these segments, right? You should be running analysis of cohorts across these different segments, right? Understanding your cohorts by geography or by customer industry, for example, to understand, you know, which of your segments are retaining well and growing over time. Once you have these segments broken out and you've done that cohort analysis, you can actually do this analysis of what we call cohorted LTV or realized LTV. You'll notice there's a downloadable Google Sheet down here. We will be sharing this presentation certainly through Battery channels, likely through, I guess, you know, probably SaaS channels as well. So encourage folks to, you know, download this and you can see, you know, exactly how all the sausage is made here. But the basic idea is, right, you know, take your starting MRR in a segment, you know, gross profit, weight that, you've got the retention from the slide before, right? You can actually see, all right, well, what is the LTV, you know, per, you know, per cohort, and, you know, kind of per month and track that going out. And so once you've got that realized LTV, you can look at your, you know, CAC payback on this kind of through this measure, right? So take your sales and marketing expense as you're starting, understand, you know, you know, and basically wait that on through. So right, in this particular example, you know, let's take February 2020 here, right. So in the first month, 19% of it is paid back. And it looks like you're breaking even, you know, starting in month 5, where all of a sudden your realized LTV is now, you know, exceeding basically what you spent to acquire that customer. This is kind of like an interesting example graph. You can see, you know, something apparently happened in April 2020 in this business where all of a sudden their payback ended up getting pushed out. This could be for reasons that, you know, make a lot of sense. Maybe you hired a bunch of sales reps that aren't productive yet, and you know, that, that's pushing things out. But basically, if you can have this view of your business, right, across your different segments, you can actually understand like, when do customers in this exact cohort, like when do they become profitable and how is that transforming over time, right? Don't look at your averages, right? Don't say, you know, our company's CAC payback is X. Look at your, you know, CAC payback across different segments and look at them over time, which is, which, you know, is what this analysis helps you to do. And again, there's the Google Sheet that will, can, you know, help folks work through this. One kind of comparison point, or I guess analogy that we make, is you can kind of think of subscriptions as being an annuity, right? And in a traditional sales model, right, if we look at, you know, the, the, you know, kind of traditional metric model with playbook models, it's a very specific annuity where there's a big trough of cash, right? You've got, you know, your reps who are flying, you know, over the world and wining and dining, and there's a long sales cycle, and there's, you know, there's an RFP and But it's a really stable long-term annuity. Your net retention is great. The deals that you're signing up are long. And so basically, this is actually kind of how— this is why us venture capitalists are around. We're around basically to fund this trough. And a lot of great companies, your Salesforces, your Guidewires, your Workdays, they look like this. But now there's new annuities that are possible today. You can look at bottoms-up sales models where people are swiping credit cards and maybe they don't have 120% net retention. Maybe their net retention's only 100%. Maybe actually it's even slightly below that. But if your payback is fast enough and you're getting profitable on those customers quick enough and your market's big enough, you can still build a large, highly profitable business. You're also saying kind of this viral in-account spread is sort of what we call it. You'll get a company like Zoom and Slack are kind of great examples where they see this large expanding, exploding usage where they're not signing up all that customer value upfront, but they're seeing this, you know, in the short— the payback is shorter because they're spending a little bit less money on acquiring customers than maybe Salesforce would. But they see this viral sort of in-account growth. And so how do you measure that and think about that and think about customer profitability? There's a lot of different ways to build a great business in the cloud. And you don't have to look like this. You can have a model that looks like this where where your annuity sort of has this shape and it can still be okay. So what you can actually do, and again, using this sheet that's in this presentation, you can actually plot your annuities on top of each other, right? So perfect example, right? Our enterprise, right? Big cash trough, but high net retention. In this example, for whatever reason, for this specific made-up company, of course, European customers, there's a slightly lower CAC, but the curve of this line isn't quite as kind of up and to the right. So their retention is probably lower in terms of realizing LTV. Their self-serve segment pays back immediately. By month 2, it's breaking even. But you can see how this line isn't flexing up as much. LTV, they're basically capturing all of it straight up. But you can look— if you can plot your business in this way, plot your different customer segments, understand when CAC is getting paid back, understand your realized LTV, If you can plot your segments on top of each other like this, you can actually, you can have a conversation with your management team, with your board, like which one of these segments should we be investing into right now? Should we, you know, do we have a lot of access to capital? And really, you know, these enterprise segments look the best, like we want to go, you know, really prioritize those. Or actually, you know, we want to just get cash in the door as quickly as possible. And by month 6, you know, we're getting the most amount of cash from self-serve. And so yeah, the LTV is a little bit lower, but you can have these more thoughtful business conversations if you're able to, you know, kind of just measure your business this way and kind of look at your business this way. You know, this has kind of all been sort of focused on, you know, sales and marketing metrics this whole presentation. I do want to give a shout out to another thing that we've been talking about recently, which is Airwalk per employee. Another thing that's changing a lot in just the way that, you know, SaaS companies operate and work is your sales and marketing expense is— you might be a lot smaller for a PLG business, right? Again, you don't have these high-cost sales reps flying all over the place, but you might be needing to invest way more into products or into other areas of your business. And so like, how do you think of your efficiency there? And so one thing that we've been talking about a lot is really using APE, ARR per employee, as being sort of a profitability North Star for your business. And so moving beyond just looking at only your sales and marketing metrics to understanding, you know, what is our ARR per employee and, and what's our breakeven, uh, APE, uh, you know, what, what do we need to get to from a revenue perspective with this employee base, uh, in order for the company to be, to be breakeven. And we find this to be like a really simple, easy to understand metric. Um, so yeah, uh, inclusion, like, still never a better time to build SaaS company. Uh, we're still very excited, we're still actively investing. I gave that example of comps earlier, but Battery's been doing a lot of investments. And one thing that I think is so amazing to see is just how great companies are getting started everywhere, how what was once thought of as niche markets are creating large public software businesses. A lot of opportunity out there. And this is just a slide I love. I think there's still a ton of opportunity out there for companies all over the world to build great businesses in the cloud. I think we can skip by this because you guys will have this, but maybe I'll give like 5 seconds if people do just want to take a picture. I think, cool. That's it.

Great. Okay. Feel free to stop sharing your slides because we are going to transition into our Q&A portion. I know we already have a few questions that have come in through the chat. So Coleman, if you would like to start by unmuting yourself and asking your question, feel free to kick things off.

Thanks, Kaitlyn. And first of all, thanks, Brandon, for walking through the slides of the deck with us. It was really, really helpful. Early in your presentation, you mentioned essentially cohort analysis as the maturation of kind of the traditional SaaS metrics. And I was wondering if you had any tips or tricks or insight to businesses selecting cohorts that are impactful? Naturally, it's going to be specific, you know, either to an industry or into, you know, an individual use case, but, but just kind of generalities on, on, on those of us that might think about places to look or, or just kind of thinking about that in a different way. Yeah, so I think, um, some of the segments that I outlined, I like— I would encourage everybody to track, right? I think geography is a great one. I think customer size is a great one. Industry is a great one. You know, I think this is something that folks are going to need to be nimble with, right? I would start with measuring a certain set, and then, you know, from then on, you know, you might have to change that over time. Like, I like to joke, even at Battery, you know, we do all this analysis on, you know, what sectors are we investing in and which ones are we missing? And when I started my career, I did this whole analysis of like what our peer set of firms were investing in, and there was a category that we were tracking over time called mobile. And right, like, that's so like anachronistic today, right? Like, it's so crazy. Like, you know, mobile is— everything's mobile. What's not mobile today? Every SaaS company has a mobile app. And so you'll find that in the course of your business too, right? Over the 10-year history of your company, you'll start tracking a segment, and it'll be related to some product mix or something, and something will change. So you've got to be nimble and just, you know, hypothesize constantly, roll out different things, like try to keep your data scheme as flexible as possible for the tracking of these things. The most important thing I would say to be is to be consistent. As long as you're consistent about what your segments are and you know like what you're measuring and you can say, I know this will be a discrete set of companies, customers that we're trying to sign going forward, you'll be okay. Where you end up falling into trouble is when you don't have a real consistent definition and you know things can kind of fit into multiple baskets and it can kind of obfuscate, you know, which segments are actually doing well. So Best advice is just set a definition, keep it, and then discard it if it doesn't seem like it's useful and really telling you something about the business. Super helpful. Thank you. Yeah, great.

We have a question from Sterling, if you would like to unmute yourself and ask.

Yeah, thanks, Brandon, for the presentation, by the way. It was really helpful. When you were talking about the cohort analysis, one of the things that popped to mind, you were We're talking a lot about kind of like annuities and, you know, subscriptions. If you have a usage-based component to your revenue source in addition to your subscription revenue line item, does that change how you look at that cohort analysis or the insights you can glean from it? Yeah, so you'll notice, so when I— when we're talking about the realized LTV, it was, it was just realized gross profit, which extends across, you know, subscription revenue and any other type of revenue you have. We have a lot of companies in our portfolio that have like an embedded fintech component to them, have payments, or just have, you know, sort of usage-centric models. And so I actually think like this is a better way to think about businesses precisely for that reason, Sterling. If you're looking at a usage-based model and you're only caring about just strictly like the revenue retention cohort, like it's going to bump around every month, it's going to look very odd. If you look at it from more like a cumulized, uh, like realized, like LTV, realized gross profit of a customer, um, I think it's just a much more instructive way to look at a company where, uh, like the, the revenue, I, you know, line item, you know, month to month might fluctuate a bit. So, um, I, I mean, frankly, I would do both, right? I think you do want to understand like what is our like contracted revenue and how is that looking over time, because if that if that base isn't sticky, right, if that, you know, I don't know, 12 months later, you know, you've got 60% net retention on, on just that piece, or 60% gross retention on just that piece, you know, it's probably instructive and helps you think about the business. But when you're thinking about the profitability of, of a customer, profitability of a segment, which for all of us right now, right, we're thinking about cash so much, like, I think you bring all that into this. Great.

We have a few questions from Ray. So if you would like to unmute yourself and ask, feel free to do so.

Yes, Brandon, I guess my first question is usage-based is a very popular new pricing model that's evolving very quickly. The revenue generated from there, which is variable in nature, ARR or not ARR? And specifically then, how does that impact things like CAC payback period and CAC ratio and sales efficiency calculations? You know, I've gone back and forth on this, Ray. You know, I used to be an ARR purist, but I think I'm less so these days. I think ultimately we can, you know, we should determine like what we want to use for language. And, you know, I would encourage, you know, for folks in like fundraising materials, for example, or board materials, like just make it very clear exactly how you're defining everything that you that you use. But ultimately, like, I don't think companies should be penalized for having significant usage-based models or having embedded, again, embedded fintech or payments-based revenue streams. I think these are all things that grow the potential TAM of a business and grow the profitability of a customer. And so I don't like having like something in our language that would like detract from that, right? I think we should be we should be calling like anything that contributes to like LTV, like I think is beautiful. I would just try to, I think when I hear that kind of question, I think about just make sure folks are aware of that. If you're talking about run rate and not recurring revenue, that's fine, but just, you know, call it out as such. Just to follow up to that, I don't want to monopolize, but if there's no standard definition, how do you benchmark yourself against external expectations? If battery has one definition and Bessemer has another, how do you benchmark good, better, best? You know, it's becoming a lot harder. I think it's just becoming a lot more difficult, right? When there was, in the metric monolith era, the single playbook era, it was a lot easier to do that, you know, cross-company benchmarking. And it's become a lot, a lot trickier these days. So we frankly don't do nearly as much of it as I think as we used to. You know what we talk about? We talk about, hey, here's a company that we might invest in. They've got these few segments that are working out really well. Like, they're, you know, this product or this, you know, this industry. Look at how quickly they're paying back their CAC. Look at the retention in this segment. We do a lot of talking about that, and we do a lot less talking about, you know, things that are, I think, more kind of global benchmarking. So, and I think it's really like, it's a back-to-basics way of looking at a business, right? Where is this segment profitable for you? Is this profitable segment in a big potential market, right? I think a lot more about that than I do about good, better, best frameworks personally. Thank you.

We have a question from Jessica, if you want to unmute yourself.

Hey, Brandon, thank you so much. This is really, really awesome. Appreciate it. Question for you, and you may not be able to answer, so I appreciate that. But given the volume of data that will drive all these insights in this cloud world, do you have a point of view on which tools are better suited for this type of analysis in a cloud world? I know there's so many out there— Tableau, Alteryx, ThoughtSpot, Sigma. Do you have a point of view on any that are more suited to handle this type of analytics in the long term? Yeah, well, so I would politely give a shout out to our portfolio company Maxio. This is actually one of the largest investments we had ever made at the time of this investment. It was the combination of two businesses, SaaS Optics and Chargefy. They do a great job of helping people just like understand like their, the SaaS metrics in their business and how their company is operating. So I'd encourage you to check them out. I also think, you know, I would actually encourage folks, you know, it's very hard to do this late in the game, right? If you are a $50 million ARR company and you're just starting to think about sort of instrumenting all of this, it's really tricky. I mean, this is kind of what I do for a living, right? I work with like growth stage companies and I look at their data, I'm like, oh shoot, I'm not going to be able to make sense of this. And so I kind of just go in and have to do it. Um, I think it is a smart thing to build, bring on somebody who's like a BizOps type person. Maybe this is somebody who has a year or two in venture or a year or two consulting, um, kind of a hybrid, you know, athlete, you know, doing some FP&A work, maybe some special projects work, some chief of staff type work. Um, I think you actually bring this person in pretty early and give that the person the task of like, just get all of our data lined up and so that we can kind of understand our business. And, and that person will have tons of stuff to do, uh, kind of just like a general business athlete that's working with you. Um, so that's what I'd encourage. I'd say there's, there's a lot of software solutions out there that will help you sort of organize all the data that Intuit or whatever is spitting out at you. But then I would also say, there's good rationale for a hire here. Thank you.

If you have more questions, keep them coming. I know we're at time, but we have the ability to go a little bit over if you do have more questions. One question that came in, companies are having to make hard decisions regarding layoffs currently. What metrics do you turn to to make these hard decisions?

So I think ARR per employee is a pretty good guiding light for businesses. Um, I, I would say it's a lot less useful and a lot less helpful below, say, like $20 million ARR. Um, your ARR per employee when, you know, you're just getting started is gonna look really bad, right? Like you don't have a lot of revenue and you just need a certain amount of employees to build a product, right? So I wouldn't, I wouldn't like be comping yourself to like public companies for ARR per employee. But I do think it's the right guiding light, right? Like ultimately, I mean, it's actually kind of rational to think through, right? What's the total landed cost of an employee? And then you need your revenue to exceed that, right? With some buffer for, you know, whatever cloud expenses, any SaaS apps that you're paying for. And that's like, that's the basic, that's the basic math. And so I think using that as a guideline of, well, clearly we need to get into some area where we've got eyesight to being able to break even. I think that's the right framework to think about. Beyond that, what I would say is my advice on right-sizing a company or how to think about layoffs, it's very company-specific. The primary thing that we think about is actually just runway and the next inflection point in a business. For some people, that inflection point can just be, can be a number, right? It's a million ARR or it's $10 million ARR. And like, we just need to be able to get to that number. For some of your businesses, maybe it's some kind of technical hurdle or milestone. But for all businesses, we all have some milestone where in your head you're like, oh, if I just, if I hit this, like my business will be worth a lot more. But until that point, like it's, we're kind of in this little bit of a no man's zone, kind of a no-fly zone. And so my advice for you is think about when that next milestone is and make sure you've got cash to get to that point and some buffer beyond, right? I think like 18 months is probably a good rule of thumb for people right now. And so I would say that that's what sort of shapes the conversation for me. It's both, you know, think about ARR per employee if you're at a stage of business for which, you know, that would be a relevant metric for you. And then I think about like, well, how much runway do I need to get to, to get to that inflection point where reasonable minds, our team, our investors agree, like, actually a lot of value is being created if we can just get to this and make sure you can get to that with some buffer.

Great. We have a question from, or a few questions from Tova. If you would like to unmute yourself and ask, feel free. Hi, Brandon.

Thanks so much.

This is super helpful.

And I'll keep it brief. They both sort of fit into the bucket of, as an early stage company, with a usage-based component. This is like really aligned with what we've been working on building internally.

But we're like small and we're nimble and we are tiny.

And so really just looking for any insight, advice, lessons learned you can share about where to focus time and energy in order to set up the foundation for success with this, this sort of style of cohort-based reporting and analytics and decision-making. That's sort of the primary thing. The secondary is any way to align that with some of the traditional SaaS metrics that some of the investors who we're talking to are looking for? Because it's tricky on a tight team to be managing both things, and some folks really are looking for that more old-school SaaS metrics. For sure. So I think the first thing is actually like if you're very, really early stage, right, some of the folks on the line are like sub-10 people, right? It's actually, it's a little bit of a blessing for something like this because you can actually like just start building this in today, um, right? It's, it's way, way easier to start with this than it is, you know, if you're a $50 million, $100 million ARR company and you actually now want to start doing, you know, cohort economics. Like, that's like a big— it's like, it's kind of a big, a big push, uh. So good news is like you, you can get started with it and get going on it, um, in terms of like aligning it with investor expectations. Um, so what I would say is Investors are individuals. Everybody's going to look at a business in their own way, and they're going to want to analyze data in a certain way. And so it kind of just is the way of the world. I mean, I like thinking in this way. I will analyze all the companies that we see. I try to analyze them in this way. But if you talk to other people, they might not get this. And so you kind of have to form the way that you're always presenting data in a a data room or in a pitch deck, like to those expectations. But for your own internal way of thinking about the business, like I think this way of doing it is just, is superior and just gives you more telemetry into what's actually going on with your company. In terms of the other aspect of your question is like, well, what should I be focusing on, right? I'm sub-10 people, I don't have cohorts to look at, I've got, you know, 6 customers or something like that. The biggest piece of advice I would give is Growth in many ways is like a function of capital, right? If everybody on this call had $100 million in the bank right now, you will grow faster next year. I guarantee it, right? But that doesn't necessarily mean you're a better business, right? It just means you have more capital to spend. The things that you can control that aren't capital related are like the experience of your customers. So if you have 5 or 6 customers, like make them love your company, make them love your product. When we do seed stage investing, like the biggest thing is, you will, we will talk to those customers at a certain point, you know, far along in the process. And if they're pounding the table and saying, hey, you know, Brandon, you're an idiot if you don't invest, like if I had a dollar, I would invest, you know, like when you get that feeling from customers, that's what gets me excited. And so that's not a metric thing, that's qualitative thing, but solve for that, right? If you just have big, you know, raging fans in your current customer base, we're super excited about you, right? Do things that don't scale, right? Give them a white glove service. I would solve for that above, you know, anything else. Thanks.

Super helpful. All right. This is our last call for questions. You know, we're already 10 minutes over, so thank you all for hanging on. All right. Well, thank you, Brandon, for your insights, and thank you everyone for joining us. This has been super helpful. We really appreciate it so much. We hope you enjoyed Azure reminder, we will see you next week also at 10 AM Pacific and every week after. Next week we will look into the importance of OS communities, and this will be led by GitLab. So look forward to seeing you next week.

Bye, thanks.