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Speaker Details

Kyle Poyar

Growth Partner
OpenView Ventures

Session Transcription

Well, welcome to this session of SaaS Metrics Palooza at 23. I've known the next speaker for several years. He was one of the first guests when I first started the Metrics to Measure at podcast. And I'm a huge fan and follower of him on LinkedIn, and his Growth Unhinged newsletter. So with that, without further ado, I'm very proud to introduce Kyle Poyar, the operating partner at Overview. Kyle, welcome to SaaS Metrics Palooza at 23. Yeah, thanks for having me, Ray. Hi, everyone. I work at OpenView, a SaaS-focused VC. And I'm ready to admit I have a problem. Ray has this problem too. I have a SaaS Metrics junkie. I really can't get enough of all things metrics and benchmarks. And I actually started OpenView's SaaS Benchmarks Report back in 2017. We're now on our seventh year of tracking private SaaS Compute Performance. But the more time I spend in this space, the more I'm convinced that our SaaS metrics are fundamentally broken, given the way that we build, distribute, and monetize software products today. And I think it's time for a next-era metrics playbook. So let's explore how we got here and what might come next. So SaaS metrics aren't some fundamental free-or-danger. It's helpful to think about, how did we even have them? How did they get developed? And so in the early days of software, software was on-premise. It had a really fantastic economic model. We sold software as a capital expense, generally big seven-figure deal, maybe six-figure deals, collected cash up front. You could use that cash to go fuel even more customer acquisition. Then cloud-based software and software as a service started to show up. And really, this had a business model. It's unproven whether this would be as valuable as a classic on-prem perpetual license model. So a new customer would like paying on an OpEx basis or paying on a subscription basis. But would this actually be a better business model or worse for software vendors? And so the fear was really that we'd spend all of this money on sales, on marketing, on implementing customers, only to acquire folks and to cancel at any time. But we never recouped that money. And so SaaS metrics helped us understand the power of SaaS business models and whether they were effective. And we started looking at metrics like CAC payback period and that dollar retention. And in many cases, saw that SaaS companies could acquire customers relatively efficiently and that those customers did stick around and all they stuck around and actually spent more and more money over time. And so these business models are not really effective. And we started getting confidence saying, hey, look, we know this business is $10 million in revenue right now. But based on their SaaS metrics, we can predict the future and get comfortable investing relatively early on in a company's revenue generation. It's kind of seen the movie played out over time. This was critical in terms of how we think about SaaS being the powerhouse that it is today. I'd argue that it might have contributed to a bubble in SaaS valuations as folks got too comfortable predicting SaaS businesses. There's actually a lot around the macro economy and other factors that influence SaaS businesses. The SaaS Metrics Playbook was fantastic. It kind of boiled down to believing every SaaS business looked more or less like Salesforce. It had this view of the world that was a kind of a classic sales funnel type of view of the world where there were prospects. Those prospects would become leads. Those leads would turn into opportunities. And that may be a proof of concept and that it closed one deal. And we have metrics to kind of measure the performance of sales and marketing action. We sort of looked at things like MQLs or SDR productivity and then how many of those converted into SQLs and VDA. How that became an accurate pipeline. We have enough brand reps to work that pipeline. And it was our win rate or our ACV at days to close. All of this focused on sales efficiency type of metrics and were focused on really our view as a vendor of what was happening inside of our accounts. But what you might see here is that this ignored a lot of things, right? It assumed that the way that we grow is from sales and marketing activities when today more and more that product usage is setting the tone. And product usage is a really important part of the buy journey both in terms of bringing people in at the top of funnel and then showing their level of intent in making the purchase. The other thing is that this really assumed that buyers are the only important stakeholder in buying software. We know though that end users are often the ones who are discovering products, bringing them into their organizations and advocating to the bottom up, right? In this view, end users are an afterthought but today end users cannot be seen as an afterthought. We also just know that a lot more happens in the software buying process outside of just activity but the sales rep. That's actually a relatively small part of the buying journey for the average customer. And so we also with this view of the world miss a lot of visibility into what's truly happening inside of a retargeted account. So this model, and this sort of sales and marketing view of the world made for some pretty compelling software businesses, right? And so some of the metrics that we all love from this era are metrics like hack payback, which refers to how fast to recover the cost of acquiring a customer. Net dollar retention, which thinks about how your book of business with your customers grows or shrinks over time. We love over time 100% dollar retention. A gross margin, which looks at the relative profitability of customer on an ongoing basis. And the magic of SaaS revenue was that we can have fairly efficient customer acquisition, 18, or actually less in terms of love hack payback, paired with 50 customers who spend more and more over time would lead to highly profitable businesses at scale. And in theory, you could stop any sales and marketing and still grow profitably in the future. And that model is kind of breaking down. It's breaking down a number of ways. And so first, let's look at hack payback. Now, hack payback really fundamentally assumes that products grow via sales and marketing, right? We look at hack payback as how fast it takes to pay off the sales and marketing costs of acquiring a customer. In a PLG model, you'd like to spend money on product managers, on growth teams, on product analytics, on a number of other things in order to grow a customer. And so in a PLG business like Atlassian, they spend way less on sales and marketing than their peers, but way more on R&D than their peers. And so how do we think about the right efficiency metrics to understand our customer acquisition efficiency in this PLG model where products are part of this mix? On the net retention side, our view of the world and net retention tended to assume that we're selling annual contracts that generally were relatively high renewal rates and there was modest expansion. But in the world of PLG plus usage-based pricing, we're often seeing much smaller lands. We might land with an individual user or a team or a pay-as-you-go plan, and then much bigger potential expands as a usage-based model, the expansion potential design of account is essentially uncapped. And so at a company like Silflake, for example, the net dollar retention isn't just off the charts, it's way off the charts, right? It's historically been up 150% plus over time. And so what's the right amount of money to spend on acquiring a customer in these cases of essentially limitless expansion opportunity, right? We can't look at things like LTV to cash, those don't really make as much sense in this modern world. So what's the right way to look at it? And now the gross margin side, if this is still important, but we tend to think about gross margins on a SaaS basis. And there's a lot of other revenue streams that are popping up, right? We might look at paybits revenue, which is very big in vertical software companies, or Fidget, or marketplace revenue, or services revenue. These different revenue streams are a bigger and bigger part of the pie for how a SaaS company shape money, but they have different characteristics in how they operate and in terms of their profitability. And we need to understand that rather than treating all software companies with the same. So let's look at a few examples. One is Snowflake. Their net revenue retention actually peaked at 177%, right? If you factor that out, instead of requiring $1,000 worth of spend for a customer, that's turning into tens of thousands of dollars if you have enough time in the future. But with the consumption model that they have, they only recognize revenue as customers actually consume the platform. And so that retention is actually very high, but also relatively less predictable, right? It's not locked in, it's tied to whether customers actually use the product. And so there's actually a double-edged sword here of really loving that limitless expansion potential, but also fearing that that expansion potential could dry up or actually shrink depending on what's happening in the economy. And so the fundamental question for folks like Snowflake is, how much should we spend on customer acquisition when LTV is essentially limitless, but not predictable? You can also look at Atlassian, one of the poster children of PLG. Atlassian actually spent 50% of their revenue on R&D, and only 20% of their revenue on sales and marketing. This is an efficient self-service version where the product sells itself. But how do we think about the efficiency of their R&D staff, right? Do they have too many engineers, are we spending the right amount there? Should they invest more in order to drive more efficiency in their funnel, right? How do we think about that JRE G-span as that revenue generating function? And the final example is Shopify, and I could replace Shopify with a number of other folks here, but Shopify is an example of a company that doesn't just monetize on subscription software. In fact, only less than a quarter of their revenue comes from subscription software. The rest comes from a bucket that they call merchant solutions, which includes other things like FinTech, Hay-Benz, Marketplace Revenue, and so on. And so these types of revenue should often have different profiles of how they work and also in terms of their margins. So how do we benchmark ARR, right? Should we count this as annual recurring revenue? Should we come up with a new term? And should we be valuing this on a multiple basis of ARR, similarly to how we value traditional software revenue? Those questions, a lot of people are asking, we don't have the best answers for today. And in my view, we need to start with a new playbook. And so before we even get into metrics, we have to actually think in terms of what is the playbook for how we grow as a business? And ultimately we think about the user journey rather than just the B2B SaaS flow. And so in this user journey, users discover a product, but usually to solve a problem in their workflow. They land on the website and decide to try it out. They usually sign up for a free product or trial, can look at interactive products on our website. They expect to see value quickly and on their own terms. And they do what we call a debate, which shows that they've actually seen value. They tend to invest money in the product, often at a small initial price point, perhaps via credit card purchase. So we think about that as an initial conversion, and then they scale their usage and the spend over time as they go from individual user to team to do a company-wide adoption. Though in this playbook, growth isn't necessarily limited based on sales, I can't write, or marketing style. It's limited based on your ability to attract users, and then how efficiently you can turn those users into how fast you can make this flywheel spin. And so you're looking for as many efficiencies as possible, and ways to replace things that maybe historically were done manually or by people-intensive means with automated and product-based solutions that are both more efficient, but also can unlock faster and faster scale. And so with this new playbook, we also actually need metrics for different stages of the user journey. And so metrics that I think about, on the discovery side, you're looking at with visitors to your website, and how much of that user acquisition comes from different sources or different channels, right? With an emphasis on lower-cost, scalable, organic channels, things like Word of Mouth, direct-to-your-website, SEO, organic social, and so on. And when folks discover the product, you want them to start and sign up for it. And so there we look at a conversion from website visitor to some sort of lead, right? That lead could be a free sign-up or a requested demo. And in my view, that conversion is only so important. You actually wanna go further and look at how many new activations you were able to capture. And so a sign-up is kind of meaningless if they sign up for the product and that abandoned all-you-do-nothing account. And it trades out about 40% to 60% of new sign-ups and to actually be those folks who are immediately ghosting you. And so a much healthier metric is to look at how many new activations you break, and that'll also help you optimize the marketing campaigns to spend money on things that will drive more activation than not just more sign-ups into your funnel. And then from an efficiency standpoint, you should be looking at cost per activation as well, rather than just cost per sign-up or cost per click. So then as you move some folks through, these folks have seen value there in your product, you wanna look at the conversion rate. And for me, I think about conversion rate on a homework basis, right? So some people will just look at conversion as how many people converted that month and how many people signed up that month. But that's not really the right frame of mind because you could have people sign up one month and convert the same month. You could have folks that you actually acquire about a year ago, and if it's been free users for a while and they decided to buy a month later or a year later, you really wanna understand for a given audience, how does conversion rate for that specific audience look over time? So you really have a true sense of your sort of ceiling for conversion rate and how that plays out in the future, right? How your business will grow over time. The other thing I look at is a metric called product influence revenue. And so this is an indicator of how much PLG is actually driving revenue growth at your business. The product influence revenue, this is essentially how much of your revenue started with a meaningful product interaction before sales or people really ever got involved. And this is a way to say, you're not just investing in PLG on a service level, but that PLG is actually driving real business outcomes for you. And it's a way to be honest about if the PLG motion is actually working or is a distraction for the business. The other thing to think about is sticky usage, right? And so for many folks, activation isn't the only usage indicator that matters. Once they were activated, you actually wanna think about, hey, have they done things that are showing that they're forming a habit in your product? They're setting up integrations, they're sharing that product with their team, they're deepening their usage, which leads to better outcomes in the future. And then finally, in terms of scale, one scale metric I focus on is having a North Star usage metric that looks at the product success of your customers. Now, if you have a usage-based pricing model, this is really natural for you because usage is tied to revenue, but even in most PLG businesses, even if you don't monetize it on a usage basis, your North Star usage metric tends to be highly correlated with your revenue metrics. And so it's a way to understand what's actually happening with your user base that will translate into revenue opportunities that you can capture from there. You should also be looking at growth and net retention, again, on a cohorted basis, and not a blended basis. And the final thing to call out on this list is product-qualified leads, or product-qualified accounts. And what this is looking at is a signal of the expansion potential within your customer base, right? So in a PLG motion, we talked about people will indicate their buying intent based on product interactions and not just their sales interactions. But looking at product-qualified accounts, you're understanding folks where you have a real revenue opportunity with these accounts, and that you can take certain actions, whether it's through marketing or through sales or through customer success and account management, to convert those opportunities. So those are the key metrics to look at. Here are some benchmarks to diagnose how you're doing relative to your peers across those metrics. And these come from OpenView Product Benchmarks Report, which we run every year. The most recent report had about 1,000 products. And so in discovery, you want to make sure that you're attracting new signups from organic and product-driven sources, so at least half of your new signups ideally are from these non-paid sources, which should be a much higher rate than it would work to traditional sales-led business. In terms of start, so this is signup rate for a percent of folks who land on your website who actually sign up for the product. We tend to see it's about 6% for free game companies, and then 3% to 4% for free trial instances. When it comes to activation, this metric would be a little bit of a blip, so there's not necessarily a good and a great metric, because it's good or great really depends a lot on your product experience and how high of a bar you define for what activation looks like. If you have an individual single-player mode activation, you're going to be able to see a much higher activation rate than if you have a team-based activation. And so generally, 20% to 40% is healthy. If you have less than 40% activation, you're either doing something really great, and I love to hear what you're doing, or you've defined activation in a way that's a little bit too narrow, and you probably think about a deeper activation record. From a convergence standpoint, these are free-to-play convergence rates on a cohorted basis. And so of the folks who sign up for the product, we typically find about 5% is normal for free game businesses and 15% is normal for cultural trial businesses, or 10% to 15%. There's a lot of nuance here based on how much sales interaction is involved with your free account signups, but we have a lot more data on here if you want to visit that Product Longevity Report. And then in terms of scaling, everyone wants to be north of 100% of that dollar retention, especially in this current economic environment. But for PLG usage-based businesses, the bar for great actually goes up because many of these businesses are land-based counter businesses with relatively small lands, and so have higher expectations for how those scale over time. And how do you increase these or how do you improve this? It's all about reducing friction through that user journey. And so for discovery, you want to focus on finding high-end type users who are going to get the WordPress aware to the jury. You want to reach people in the neighborhood of me or when they're feeling the pain that your product solves. And often, product referrals or product buy-reliefs are a great ocean there that PLG companies have accessible that many other companies don't have. But SEO also, despite talks about the death of SEO, SEO is still effective for PLG businesses because you're able to reach this end user who's often turning to Google when they're facing a challenge in their work. And they can discover your product when they might not even realize their software to do what they want to do. In terms of getting people to actually sign up and start, you have a really narrow window, right? People, you're getting people relatively early in their journey before they even know that software helps them. So you want to nail first impressions on a website, the .com page, your messaging, your imagery, how much social proof you add is really critical for driving this rate up. And also increase the motivation for people to continue along the journey. In terms of activation, this is about delivering value, more often than people to pull up their credit card. So really having a clear understanding of what it needs for folks to see value and then having a relatively innate path for getting to that initial stage of value, while having also some ability to personalize that experience for different use cases or levels of intent of those folks coming to get your products. From a convergent standpoint, we found a reverse trial motion has been fairly effective for increasing converting rates. And this is where you should get the best of both worlds with freemium and free trial, where you land someone in a free trial experience, and then they can either buy at the end of the trial or continue with a basic free version of the product. Reverse trial businesses see the best of both worlds in terms of a very high side up rate and also a high free to pay conversion rate. And then there's also an important role for sale growth, right? Product with growth is in anti-sales or doesn't mean only self-service. There's a really great opportunity to target the right folks who are signing up and work with those short to share an offer, right? Driving more usage adoption and ultimately conversion. From a scale standpoint, your focus should be going from user to team to company adoption. And so many PLC companies land with an individual user and maybe even work with B2C user. Those are great in terms of building champions or in community around your product, but ultimately modernization comes with teams and businesses. And so really need to nurture folks who build that bridge to turn that user into a team or a business in this case. And looking at your product qualified accounts is a great framework for people getting there. So these were all operational oriented APIs, right? Things that you can do to manage your business today to kind of get better and better. But you also need to bring investors along to show that this strategy is working, right? And has the characteristics that a board cares about that will be attractive for the increase in your valuation or getting the next funding. And in terms of investor oriented KPIs, I've tracked six more modern SaaS KPIs here that I personally believe are important. And I've split them into growth oriented KPIs, efficiency oriented KPIs. Both of which are, you know, especially on top of my list are economic and virus. So first is, you know, sounds simple, but it's a little bit more complicated than you think. Annual revenue run rate or ARR in quotes, quotes is purposeful here. And this is a way to think about your revenue that acts recurring, even if it's not officially recurring subscription revenue. And so having an understate for your non-subscription and subscription reoccurring revenue. And what's the overall size of that pie? Knowing that you can then share the breakdown of that ARR in quotes by source or by type of pricing model. And then when you have that ARR definition, ideally that broad based definition, you want to look at the quarter on quarter change in that new ARR. And the reason why this is important is looking at that new ARR helps show the growth, but the quarter on quarter change shows to what extent your growth is getting bigger and bigger in subsequent quarters. And it indicates to an investor, are you growing linearly where the business is, maybe on a healthy path, but not necessarily investable or not showing signals that growth is inflecting or non-linear slash exponentially, which is a really interesting path to put more fuel on the fire. The final one here is cohort based retention by customer type. And so we talked about cohort based, we talked about retention, but customer type to me is the other unlock. So some companies will look at retention by things like by a self-serve customer versus sales channel, right? I think that you should think about it in terms of customer types. So you've got your small customers or SMBs, maybe you include personal users in that mix, your midsize customers, your enterprise customers, that's gonna correlate roughly with the conversion channel that they prefer, but you're gonna find some enterprises you'll land on a self-serve plan, but then you have a lot of expansion opportunity. Some SMBs you might post with the sales team. You wanna understand the retention characteristics of your different customer types in the business. On the efficiency side, like relatively simple KPI that I'm drawn to is the quarterly net new ARR versus the cash burn. And so what's that ratio look like? And that helps to just show, really, are you spending money in a way that actually leads to making more money on the business? Also, what's your natural rate of growth? So natural rate of growth is looking at that product influence revenue, but how much of your growth is contributed by it, right? So another way of thinking about this is your organic rate of growth, like how fast you would grow without needing to add incremental loss of ownership, things like more sales reps, for instance. And the final KPI here is ARR for FTE. And this is, there are a number of gotchas or things to be aware of here, but I like this metric because it's really simple, like no complicated math required. It's very obvious where you are, and it's very easy to compare against other businesses because many of these metrics are available or can be solved. And this is a great indicator of capital efficiency and whether your investments in things like product-led growth or AI or automation are actually driving more efficiency in your business in one day. On this ARR for FTE method, I've included some rough benchmarks here based on our annual SaaS Benchmark Survey of what good and great looks like at different ARR bands. Obviously, there's nuance, right? You are a business that has a lot of international locations, including low-cost deals. You might want to look at businesses like ARR based on an overall compensation dollars or something rather than individual employees. But for most startups, especially startups based in North America or Europe, this is a good rule of thumb in the jar. And you should be looking to see this metric increase over time, right? Copping that pot to ideally 200K plus ARR for FTE as you scale. And the relative possible is very high if you look at public companies, whether it's Salesforce, Zoom, or more PLG companies. Like, aha. That's it for me. Just closing takeaways to leave you with are that SaaS metrics are historically important, but they came about to help us understand the power of SaaS business models. They worked great for the SaaS businesses that we used to have, businesses like Salesforce. But now we have new business model, new company characteristics. And so we need a new set of metrics that represents the businesses. And to develop the metric, start by understanding what's the playbook for how we grow. And that's often based on the user journey and not just a B2B sales process. And then in selecting growth or accelerating that growth becomes a function of delivering value and reducing friction in the customer experience. And even though we'd love to not do this, it helps to bring investors at board along in this process so that they can see how these investments that you're making or these changes that you're bringing the business are actually leading to a healthy overall outcome. And so in this case, look at growth-oriented KPIs like that new AR growth and annual run rate revenue and then also efficiency-oriented KPIs. In terms of next steps if you wanna go deeper in any of this material, you can follow me on LinkedIn. I put out your daily active advice. I also have a weekly newsletter, all growth on page, it's on SubStack. And I love our benchmarks and our metric support as I know Ray does as well. Well, thank you so much. Every time I have the chance to speak with you or read one of your articles or listen to a presentation, I learn something new. And so thank you for that and thank you for what you're doing for the industry. And when it comes to PLG, you're my go-to resource. So I have to ask you a question because to me, this is the elephant in the room about PLG. Two months ago, you did an article on sales and marketing as a percentage of revenue for PLG versus sales-led growth companies. And I think it surprised a lot of people but our private company research showed the same thing. So can you share at a high level what the correlation is of sales market expense, right? For PLG and what surprised you? Yeah, it's a great question. So there's, in theory, right, PLG companies should look more like Atlassian in their business, right? Where they aren't spending as much money on sales and marketing but they probably are spending more on R&D and it's an indicator that growth is coming from R&D investments, better product experiences, self-service experience and so on. When we looked at public PLG companies, especially data from the, you know, heady days of 2021, PLG companies were spending similar amounts or more on sales and marketing and more money on R&D. And so while growth was higher, the efficiency wasn't there for PLG businesses given this elevated level of spend. And I think that, you know, in my idea, part of this is because in the days when people were valuing growth at all costs, there was a lot of, there was a lot less rigor in terms of the bar for incremental investments, right? And so in PLG companies wanting to add sales reps to motion or increase marketing spend, there was a lot of appetite to do that if it could increase growth rates, even if it didn't make the motion more efficient, right? You can have a PLG business that has a pretty effective self-service conversion. Let's say you convert 10% of signups. You can add a sales rep and convert 12% signups, but that might actually be worth all of that spend on the sales rep. And so today there's much more of a focus on how PLG can drive efficiency in a business, not just PLG as another channel to grow. And I think the Klaviyo S1 is an interesting example of that different way of thinking in practice. Great response. And then the last question, because, man, our session's already almost over, but I love your natural rate of growth. So would you mind just spending maybe a minute on the three primary components of that? Of course, people can come and see it online or your growth enhancement, but what are the three components of natural rate of growth? Yeah, it's a great question. And this is a more emerging metric. And so we'll be very curious to get feedback on all the while folks think about it. The idea here is it starts with, are you acquiring users through an organic channel that you're not heading for? Through something like SEO, organic social, direct traffic to your website, viral loops, and so on. And then are folks getting to a meaningful point of value before talking to a sales rep? And so it's a share of how much of your growth comes from these activities as opposed to everything else. And it's an indicator. So for a PLG company, you might actually have a fairly high natural, organic rate of growth based on your viral loop, self-service purchases, self-service expansion. And then you go and add marketing to it. The blended CAC payback might look still fine, but you're actually taking something that had a CAC payback of zero and then blending it so that we have a CAC payback at 60, and then it nets out to something that's a average. When by focusing on natural rate of growth, you get sort of on app. What is this sort of baseline of really efficient growth in your business, maybe not hyper growth? And then what is the incremental effects of these other things that you're doing to try to reflect that? Thank you so much, Kyle. Always thought provoking. I encourage everyone to subscribe to your Growth Unhinged newsletter, follow you on LinkedIn, and thank you for what you're doing to help this industry move forward. Have a great rest of your day, and thank you again. Great.

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