I'm really honored to introduce our next session and our next guest. I got to know Lauren Kelly about two and a half years ago when I invited her to join on a podcast with me, and then we started talking about the need to standardize metrics and that really was the foundation for the SaaS Metrics Standards Board. But without further ado, I'm very proud to introduce Lauren Kelly, the founder and CEO of OPEXEngine, now a Bain company. Lauren, the show is yours. Thank you, Ray, and good morning, afternoon, good evening to everyone here at SaaS Metrics Palooza. Ray, I have to say, I am so thrilled that you invited me to participate. You have such great group of experts and practitioners, and I just think you are such a great presence in the industry, bringing so much terrific content. But I'm Lauren Kelly, I'm the CEO and founder of OPEXEngine. OPEXEngine is a SaaS benchmarking platform. We've been collecting data with companies and working with thousands, hundreds of companies, over a thousand now, for about 15 years. We were acquired, as Ray mentioned, two years ago by Bain and Company. We are very lucky to have worked with and continue to work with some of the most amazing companies that are setting standards, they're evolving SaaS models, and we learn so much from them. We're just incredibly excited about the work that we do every day, and as we all know, this is an industry that is constantly evolving. We focus 100% on B2B software in SaaS, primarily on SaaS companies, and we are backed by the insights of Bain and company and bringing those insights together with the data to the mid-market. We have a little different model than some of the other benchmarking companies out there because it is a paid model, but we go into great detail and we have financial consultants who work with the companies who validate the data, and all the data goes into a blinded database and companies can compare themselves against peer groups with great detail in terms of the filters that they apply to create their peer groups. But let's talk about the SaaS industry. The rules have changed in 2023 and going into 2024 for SaaS companies. We all know that there's a lot of money in the SaaS industry, and growth at all costs was really the model in the last couple of years. As more and more money float in, as the world is becoming more digitized and cloud-based, and as the market has grown, at the same time, the market has, or the investment numbers have slowed and companies are looking now at profitable growth. One of the issues, and I'll just speak to this, I think we've all in the industry spoken to this before, in 2020, as we all know, the market kind of stopped for a little bit. And then a lot of our customers found that by June, July, things were opening up. Companies were still buying, everyone had transitioned to remote, and they continued to grow. And then they went into 2021 with more access to capital, more money, and they felt like they were behind in the hiring because they'd missed a large part of 2020 when they were trying to hire. So in 2021, a lot of companies went out and hired way beyond perhaps where they should have been. And then as we went into second half of 22 and companies were moving to slowing down, the feeling was, oh my goodness, we have to manage our growth and we have to dig into our cost structures. So I love this, and I'm using another firm's data. We have the same thing, but just to give an example to another company, America's Growth Capital, great tech investment bank here in the Boston area. And the key thing about this information is if you look at sort of the top blue line, from the top, looking at price per earning multiples, 38X, definitely on the rise as compared to if you look down at the light blue revenue growth multiples of 16%. So we all remember when that was flipped a year or two ago, but it really tells you the story a little bit about the focus now on profitability, cashflow positive for smaller companies and just on efficient growth. So the successful companies out there are building strong fundamentals, and you'll hear a lot about this from some of the other speakers, I think, here, but the focus is on rule of 40, although it's still weighted more towards growth. Unit economics, go-to-market productivity, and R&D ROI. R&D ROI is a metric that OPEXEngine developed, and it's a very simple rule of thumb to look at the productivity, the growth productivity that you're getting from your R&D investments, and we'll talk about that in a minute. So we see companies, and we certainly have a particular perspective in the market, that are using benchmarks as a roadmap to efficient growth. And how do they do that? They identify, you look at the top indicators, rule of 40, growth rate, EBITDA, and then dig into, okay, how can I make those better? And that requires really detailed information of headcounts and expenses and various ratios. And then, in addition, as you go through that process, what a lot of companies find is that the way they're calculating KPIs may not be based on industry-best standards. They may find that, you know, if I want an average cost per company, I need to have one customer number. So many companies have one customer number that comes out of the CRM, a different number that comes out of the billing or the back-end financial system, and you have to have one source of truth for those numbers. And so there's standards and different ways of calculating that. But what we're seeing in the investment world, and being part of Bain now, we work a lot more with investors, as well as with individual companies, that investors are, you know, transactions take a longer time, there's much more detail required, and oftentimes investors are definitely going into back-end systems and calculating the numbers themselves. So if you're presenting for M&A, for fundraising, and you're showing numbers that then are not validated when an investor goes into your systems, that definitely either affects the deal overall or affects the numbers in the deal. And then one of the things that we find with benchmarking, which is not usually why people decide to do benchmarking, but one of the things we find which is really surprising is that one of the biggest values is getting everyone on the same page. It's a lot more compelling to have the conversations between the finance organization and the sales organization and the R&D organization when you're comparing their numbers and what they say they need to data-driven, you know, examples from other peer companies that have similar business models. And that's something that just takes a lot of the politics, a lot of the ego, a lot of the, you know, just frankly, sort of confusion about what the numbers should be off the table. I also wanted to talk a little bit about the different kinds of benchmarks because, you know, Ray, you and I both look at a lot of things on LinkedIn, a lot of the content that's out there, and sometimes people confuse one thing for another. So internal benchmarking, and we hear sometimes from investors, one of the things they really don't like is when a company is only showing internal benchmarking, which means I'm showing how I'm doing this quarter against last quarter against last year, and, you know, nice upward trend. Well, that's great, and that's important. That's step one in tracking your KPIs. But that doesn't tell you whether that's good, great, or below average. That increase of 30% in a particular function or a particular performance might be still below average in the market. So the second kind of benchmarking that companies undertake is peer benchmarking, looking at your peers, and there's lots of sources out there for benchmarking. There you're looking, trying to look at your peers. Oftentimes companies look at, you know, other companies' results based on revenue size. Sometimes it's possible to get different business models like PLG, product-led growth, which has very different dynamics than a standard sort of enterprise sales of an application or of a large contract value or different than SMB and transactional sales. So peer benchmarking is really important, but it's also helpful to look at strategic benchmarking, so looking at world-class organizations that are aspirational, if you will, for your company. So, for example, lots of companies this year have been looking at, you know, we want to improve our cost structure, so how can we look at companies with business models like us but better cost structures? And that's an important aspect of it. I also wanted to talk a little bit about how difficult it can be to do benchmarking, or because of some common sort of perspectives out there, as we talk about internal benchmarking or word-of-mouth networking. All of us have our own networks and oftentimes, you know, traditionally, and in fact that's sort of why I started OPEXEngine, because I've been lucky enough to build up some fairly large businesses, and how did I operate? Like everyone else operated, I would call five or ten of my network to see if they could help me with some particular number or target or information that I was looking for, except for that, I don't usually happen to know ten people in businesses that are exactly like mine at the time that I'm calling them. So you're getting general directional information, but it's not, you know, enough to really make sure that you're on track. And then as we talked about cohort, getting the cohort right is incredibly important. I was talking to a payment processing platform company that is about $200 million, and they wanted to compare themselves to Stripe and PayPal in order to do headcount planning. And I said, well, Stripe's like $15 million, and I think, I mean $15 billion, and PayPal is about, I can't remember, $20, $25 billion at this point, and the headcounts are going to be completely different. Yes, it's the same industry, but it's not going to be similar in terms of headcount, and it's going to be a long time before you get actually to that point. So the other thing is validated data, and that's where performance data or large masses of data can be really good for directional information. But when you're looking particularly on cost structures, and you're talking about people's salaries, and you're talking about, you know, laying off a percentage of your team in order to improve your EBITDA and increase your growth performance, it's really important to make sure that the data you're working with is based on, you know, validated financial and expense information. And then, you know, we're all in the tech industry, and vanity and egos and money can sometimes inflate benchmarks, and it's just, it's not helpful. It doesn't really give you any information. It might matter, maybe, I'm not as worried about what people say externally, but in order to run your company and make sure that you are really on top of the right information, you want to use metrics even if they're unflattering, and comparisons even if they're unflattering. You can keep it internal. You know, the companies that we've had the luck to work with over time, like HubSpot and Zendesk and DocuSign and, you know, just loads of other just amazing SaaS companies, they're very data-driven. If I can say anything, I would say that the companies that I see just anecdotally as being successful, they don't hide from difficult information, and they tend to be very data-driven. And then getting the data but not knowing how to apply it, how to drive change in your company. So, Ben Horowitz, if you haven't read his book, you know, The Hard Thing About Hard Things, I think is what it's called, is just, you know, be honest with yourself, look for the right metrics. It doesn't end well either for yourself or, you know, in terms of your reputation. So the two things that we see companies looking at the most going into 2024 is, how do I improve my margins? How do I get to cash flow positive? How do I improve my, you know, rule of 40 and EBITDA? And how efficient is my growth? You know, how do I make sure that there's not sort of blockages in my go-to-market and that I'm actually realizing the value that my company brings to the market? So I just wanted to show, this is just a quick example on margin improvement, some things that we've noticed recently. I just took two quick metrics and, you know, very simple for 25 to $50 million companies, one set are faster growth, another set are slower growth. And one of the things I think is really interesting, which a lot of companies don't do, is to look at your comp, your headcount expense, as a percentage of your total expense for that department. And what we've noticed is that really fast growth companies, it's not as, you know, higher percentage as you would think. And that it's always a lower percentage of the total than slower growth companies. And typically, you know, you think 20 years ago, comp, when I ran sales organizations, comp would be maybe 95% of my expense and the rest would be travel and entertainment. Now we even see some companies that are, you know, depending on the model at like 65% comp. And this is a number that I think in 2024 is going to be definitely a moving target as companies learn how to incorporate AI tools and productivity and capabilities into their systems and make the people that they have smarter and faster and more capable. So on the go-to-market efficiency side, you know, at an indicator level, we'd recommend, you know, look at your magic number. Magic number for anyone who hasn't, you know, thought about it before is your change in recurring revenue over your sales and marketing expense. It used to be for a previous period, now we're seeing most people using the same period. And generally, you want the number to be somewhere between 0.5 and 1.5. But then because the SaaS model is based on innovation and sort of constant innovation and support to the customer, we look at R&D ROI as well, which is taking last year's R&D expense against, you know, for every dollar you spent last year, how many dollars do you get this year? And we find that that, you know, if you think about it, go-to-market and R&D and product, that's about 80, 90% of the value of, I mean, the expense and the spend in your company. So this is just showing it's interesting. We're seeing things tighten up and even this, the R-squared is even tighter than it was at the beginning of the year, where if we took the top quartile of most highly valued Bessemer Cloud Index companies, so just the top 25% in terms of revenue multiple, and we looked at their growth rate against sales and marketing expense. So it's not so much about what percentage of revenue you're spending on sales and marketing, it's about what kind of growth rate. If you're getting the growth rate, then your value is there and the market's recognizing that the value is there. So you can spend crazy amounts within limits, but you have to be getting the growth rate. If you're not, that's when you are in trouble. So here I took, I just wanted to also dig into the other aspect of this, which is getting the cohort right, and this is where it gets a little tricky. So here's two cohorts, 50 million to 100 million, 50 million to 100 million, both selling larger contracts or enterprise-type contracts, 100K, one's slow growth, one's high growth. If I look at sales productivity, an average comp, so it's still roughly rule of thumb OTE to productivity or quota target, but here is actual productivity, roughly four to five X, but very different models where the cost of customer acquisition is lower for the fast growth company, but they are supporting their AEs, their salespeople with more lower cost salespeople and their magic number is higher and they're only needing, their marketing spend is very efficient because it's, you know, a little more than three times between, you know, top of the funnel marketing qualified leads to closes, whereas the other company, it's closer to, you know, five X from the top of the funnel to closing a deal. And they're not only less efficient, but they're spending more for their marketing people. And contrary, the comp for the CS employees is a little higher for the high growth company, but they've got faster growth and they have higher net dollar retention. So very different numbers in a way, but almost exactly at some level, if you were to try and figure out what the right cohort is, very close, but big differences. And that's where it really matters who you compare yourself against. So back to R&D here, we're looking at what's interesting. And I think this is a super interesting trend is that the really bigger SaaS companies, 500 and a billion dollar companies are actually spending more on R&D right now. And there's been a lot of talk in the industry about platform versus application strategies and that kind of thing. But you can see, and that it's a longer conversation, but there's some reasons why these numbers are high, but that's something to think about for smaller SaaS companies about where the big companies are heading. So when you think about R&D ROI, these companies are getting more than a dollar for every R&D of new revenue, not just the existing revenue and supporting the existing revenue, but an additional dollar of new revenue. And then the very large companies are getting almost a dollar and a half. So these companies are in good shape and I would challenge anyone to calculate this. It's a super easy calculation for your own company and see what new revenue you're getting from your R&D spend last year. So just wrapping up a little quickly, we talked about how important it is to get the metrics calculated correctly. Make sure that you're getting the right cohort pulled together to compare yourself. And then, you know, obviously I'm a little biased, but I think it's important to get the right benchmarks and make sure if you are doing a deep dive to diagnose and improve your and build out your budgeting and your planning, I think it's important to make sure that you have detailed and validated benchmarks. So I'm just going to make a quick plug for Eric Mersch, who has written a great book. If you need background on SaaS metrics and looking at it from a CFO's perspective, I think it's really helpful even if you're not a CFO, because CFOs are typically responsible for calculating the metrics for your company, and it's important to understand their perspective because you need to work with them and understand it. So Eric does a great job of explaining that for the non-CFO types. And then just, I know this is sort of tooting our own horn, but I just want to make the point that benchmarking, whether you work with us or you work with anybody else, it doesn't matter, but you can see real improvements and real results. These are improvements that companies that work with us regularly, three years or more, these are average results. But I'm just, I'm presenting that because I think it's really important for people to see the kind of results they can get. So with that, we've had lots of customers who've done, said all sorts of nice things about us, but that's it. Thanks very much. Oren, thank you so much. It was one of the better, deeper presentations I've ever seen on how to do benchmarking right. And as a fellow benchmarking aficionado, I really appreciate that. I have a couple of questions for you. One is public company data. So we can go to Edgar, we can pull their 10 Ks and 10 Qs, but you don't really know how they're calculating their performance metrics because they're not regulated by FASB or ASC606. So if you're trying to compare yourself to public companies, you have the same issues with like survey-based data where you don't really know how they're calculating their NRR. And is that something that you've solved? But it's more importantly, just for the general audience, well, I looked at Snowflake and their NRR is 166, but I don't know how they calculate it really. Yeah, no, it's a great point. And so public companies for income statement balance sheet, you know, gap metrics, I mean, even within gap metrics, there are variations like what goes into GNA. And for example, one of the big issues right now is any company of scale has big investments in cybersecurity. And is that part of GNA? Is that part of product? Is it somewhere else? Because you have business security, like your employees making sure their email's not getting hacked or they're not clicking on the wrong things. Your product security, your customer security, your system security is like, where does that all fall? How does that get allocated? And so, but generally, income statement balance sheet items, you know, are at least as consistent as they can be. NRR, you're exactly right. It's a Wild West to some extent. I think that's part of the work that you and I have been doing, Ray, and the rest of the team at the SaaS Metrics Board, trying to establish standards out there. But when you're a public company, there's a lot more riding on it than when you're a private company, if I can put it that way. So you have to be very careful about how you describe these things and how you present them. There are some movements in the sort of accounting industry to create, you know, to bring some of these metrics that are actually driving investment dollars and metrics that are actually forward-looking metrics into the fold of gap metrics, but that's going to be a little bit of time coming. I don't know if that helps you. I would say for companies internally and privately, the work that we do, you know, don't, I don't, you know, it's not going to help you diagnose anything if you're not honest with yourself, like Ben Horowitz says. Not to name names, but I still remember a public company that said their NRR was, I'm just going to make up a number so I don't disclose it, 140%. And then about 20 minutes later in their call, they actually said that their growth was going to be 35%. And an analyst was like, how could you have an NRR of 140, but you already grow in 35%. Does that mean you're losing 5% on new customers somehow? It just didn't make sense. So when you'd calculate these metrics and you present them to your investors, private or public, that consistency about how you calculate them, then how you compare it to the right cohort. Sage advice, Lauren. Thank you so much. I could talk to you for another hour, as you know, but we got to move on to the next session. Thank you so much. And thank you to OPEXEngine and Bain for also being a Platinum Sponsor of SaaS Metrics Palooza this year. Absolutely. That's great. Thank you so much, Ray. This is awesome. Bye bye now