Michael: On this episode, we look at one of the foundations of the fourth industrial revolution: software as a service. SaaS companies on the road to becoming the next hyper scalars need to constantly assess the direction of the company and ultimately its success through the lens of several key metrics.
Carter: What we want to look at is how efficient is that business model that we're going to put money into? And for us, it's way more important than the standard gap financials. And so that may surprise people.
Michael: Hello, I'm Michael Hainsworth. The CIBC Innovation Banking podcast explores the world of startups, growth stage companies and late stage companies that have made a big splash in their industries around the world. We talk to the entrepreneurs who have made their mark thanks to a fearless passion for what they do. And through the lessons they've learned, we learned how to be better at running our own businesses, engaging our own clients and exploring new ways of thinking about the innovation economy. Carter Griffin of Updata has built a framework for exactly that and is using it to determine which SaaS companies to invest in and which to pass up. But the metrics apply not just to the companies he invests in, but must be applied by those companies looking for a cash injection or a takeover offer. He's looking for companies in the five to 50 million dollar range. But as I found out, there's one other key metric he uses: geography. And if you're in the San Francisco Bay Area, he's not interested.
Michael: So question number one, why is five million to 50 million that sweet spot for you?
Carter: We operate in that spot because those are the companies we used to run as operators here at Updata. So we're a firm of former recovering entrepreneurs, you could say, and five to 50 is the range of companies that we used to run. So it's familiar to us and it gives us the repeatability of insights by focusing on that one band that hopefully we can bring to the companies we partner with.
Michael: But you don't partner with companies in the Bay Area. Why not?
Carter: We stay out of the Bay Area because it's a very well developed ecosystem. And we believe if you're not living in that ecosystem, you're going to be hard pressed to find the best deals. We don't feel like we can fly in from out of town and find the best companies. In addition, our limited partners, our investors at Updata want exposure beyond the Bay Area and we help give them that exposure because they often have heavy concentration of tech in the Bay Area. And then lastly, it gets very pricey and very frothy in the Bay Area and we feel like there are better values to be had in other geographies.
Michael: What are those geographies outside Silicon Valley where you're finding those gems?
Carter: They include Canada, Australia, England, the Netherlands. We've done three deals in the Netherlands, but most of them are in the continental US. Everywhere from northern geographies in the in the Upper Northwest, Pacific Northwest, Seattle, Portland, down to Southern California and across the U.S. in those types of geographies though where where we will go, there's often not a lot of venture capital. There are entrepreneurs who grew up by building a product and selling it to customers, not going to coffee shops to raise money before they even had a company. And so we we like that discipline of those bootstrapped entrepreneurs who can grow a business without continual injections of capital.
Michael: So you can't invest in, in an SaaS company without having some sort of protocol, some sort of system. You introduced a framework for analyzing these companies. And after you built that, it's a process of refinement in revitalization of what that framework looks like. After you talk to CEOs, CFOs, the others, what evolved in your thinking in that framework?
Carter: Well, the framework started when I was an entrepreneur, back when I was running a company called Brivo Systems. We were spending money and trying to grow a SaaS business. And I had questions as the CEO, what's the ROI on certain expenditures? I remember a specific time when the head of marketing came and told me we absolutely had to go to this trade show. And it sounded compelling because all of our competitors were going to the trade show. But I really want to know now what's the ROI on that trip, because it's not cheap. And that led me to develop the framework to figure out what is the return on investment for this, for the spending that goes on to acquire customers. And so we've refined that framework here at Updata, but it really is the core of our underwriting model when we work with companies. And so what we want to look at is how efficient is that business model that we're going to put money into? And for us, it's way more important than the standard gap financials. And so that may surprise people. But to the unit economic framework, it really is the core of our underwriting model, because what we want to know is if we're going to put money into this company, what's the efficiency of that customer acquisition model? Our money really goes for two things, R&D to build new products and sales and marketing to grow the customer base. And it's that sales and marketing expenditure where we spend a lot of time with the unit economics framework. And for us, we're looking at if you put a dollar in to go acquire a customer, how long until that dollar is repaid, and how many dollars are you going to make over the life of holding onto that customer? That's far more important to us than looking at the income statement, the balance sheet and the statement of cash flows.
Michael: So then when it comes to SaaS, you want to know the cost of acquiring a customer. What's the best way to determine that?
Carter: That's pretty easy. What we do is we simply take the sum of all the expenditures and sales and marketing and we divide them by the number of customers acquired in the given period. One mistake that we see entrepreneurs make sometimes or CFOs is they don't fully burden those sales and marketing costs. They may not take some of the office expense and burden the department. They may only look at the marketing expenditures and not include all the headcount costs. So we want to look at the total cost of sales and marketing and then we can take that and look at how many customers were acquired with that expenditure. There's often a lag in sales cycles, so sometimes you'll spend the money two quarters ahead of actually landing the customer. So you need to account for that lag in the analysis. But it's pretty straightforward overall.
Michael: And for a CFO, I can imagine once you break it down into unit economics, this is a way to allocate dollars across the most efficient channels.
Carter: That's exactly right. So the whole point, and going back to my story about my management at Brivo and the marketing person coming to me, what I wanted to know was, is going to the trade show a better use of money than sending out an email campaign or hiring another salesperson? It's those trade offs that are incredibly important as an entrepreneur. And so what the unit economics analysis allows you to do is to look at cohorts and determine which activities are yielding the best results. Maybe it is going to the trade show. Maybe it's actually investing in customer success to allow you to hang on to the customers that you've acquired for longer rather than just adding new customers that may turn off. And so the point of the framework is to help companies make those operational decisions with the outputs.
Michael: And since you're not a leveraged buyout style company, you're not looking to extract things from this company and take it apart. You use these types of metrics as well to help you determine who to invest in.
Carter: That's right. So the private equity or buyout playbook is generally to buy a company, add leverage, add debt, large amounts of it often, and to cut costs through that financial engineering technique. That's how they produce returns and it's obviously successful. It's not at all what we do at Updata as a growth equity investor. What we're trying to do, and the way that we make money for our investors is helping companies grow, helping a 10 million dollar SaaS company become a 50 million or 100 million dollar company. And so we are very interested in understanding what are the levers that we can pull to help them grow more quickly, to invest in the activities that are working. And we say feed those activities. We also want to starve the activities that are not working. The framework helps us get a lens into what those activities are on both sides of the ledger.
Michael: SaaS companies are different from traditional brick and mortar firms, their cost of doing business is all in the cloud.. And that makes the cost of acquiring a customer a key metric. Since every new customer adds to the overhead of running the business, keeping those costs down is critical. But calculating customer acquisition cost isn't as simple as it sounds.
Michael: So once you've got the cost of customer acquisition figured out, how do you figure out what constitutes a reasonable figure?
Carter: So what we wind up looking at is the return on that customer acquisition cost. We call it, there are two key numbers that fall out of our analysis, GMPP and ROCAC. So GMPP is the gross margin, payback period. So you spend that dollar to go and get a customer, acquire a customer. How long until you're fully paid back and back to the water line and then churn starts coming into the picture to figure out how long do you expect to keep that customer? And therefore, how many dollars are you going to yield on that on that customer over their lifetime? And that's ROCAC, return on customer acquisition cost. It's simply the ROI on the dollar to spend and acquire a customer. And those are the two key outputs. But I would say more importantly, and that's a pretty basic concept, those two metrics, where we see companies fall short of their analysis is they're not doing cohort level analysis and I talked about cohorts of customer acquisition, but the analysis also needs to look at how are we doing with different vintages over time? Maybe your churn is is the same as it was a few years ago, but without breaking it down and looking at cohorts over time, you can't tell if the old customers that were on gen one of your product are turning off or if the new customers that you've pressed really hard to get on board are turning off more quickly. You need to look at sales channels as we've talked about. You also need to look at sales person. So are Charlie's customers that he landed, are they sticking with us longer or does Suzie have a better track record of landing customers that stay with us. You have to look at the products that they bought. Oftentimes we find that customers who buy more than one product stick around for longer periods. Is that really true? If so, how much do you want to promote and cross-sell a suite of products? So the cohorts ultimately guide the operational decisions and allow us to figure out again where we want to reinvest and where we want to trim back.
Michael: It seems like it's a pitfall that a lot of entrepreneurs would would fall into you. You need to put churn under the microscope because there could be a multitude of behaviors that are responsible for it.
Carter: That's right. The trap, if you like, that we see companies fall into and we see this every day in companies that pitche us, is that they refer to what what we call the snowball. So you think of a recurring revenue book of business and you can think about that as a snowball and you're trying to pack more and more snow onto it and make it larger. When you look at churn against the snowball, what you're really talking about is, is averages. And what we want to look at are the cohorts or the composition. And what you really want to see is that you know oh that was not such a good cohort. And that's obviously a vintage based concept when you're thinking about tree growth rings, but you can see good growth years and bad growth years. And that's really looking inside of the snowball that we want to take to allow greater fidelity and ultimately better decision making. Retention comes in a lot of flavors. There's logo retention. How are my customers, how's my customer count performing over time? There's gross dollar retention and there's net dollar retention. The one that people refer to most often around this is snowball retention of net dollar. They'll say we have one hundred and five percent net dollar retention. That may be true. And that's, but digging in, you may learn that you're turning a lot of customers, adding a lot of new customers, and it's netting out to one hundred and five percent. But there may be some systemic issues in the business that are worth looking at.
Michael: Right. So there's a reason to look at churn positively. Churn helps you decide what needs fixing. But if you don't know why the churn figure is the way it is, you don't know what to fix.
Carter: It can come from a number of different places. It can come from overselling customers. It can come from faulty products. It can, it often comes from faulty onboarding of customers where customers see the fit. They liked the product. They want to buy it. They do buy it. But then there's a failure to launch. It's given rise to this department called customer success, which didn't exist five years ago. And the whole point of customer success is to help customers be successful with your products. And there are even software companies that do nothing but customer success software. And I think it's a recognition by the market that acquiring a customer is one thing, but making them successful over time with your product is really where you can build enterprise value because churn truly is cancer in these recurring revenue businesses, it eats away at the core and is very destructive. And so, again, where I think companies often fall down and say, look at the net dollar retention, and they say, oh, well, it's healthy, but there can be a lot of unhealthy activity underneath the surface.
Michael: We think of churn as the past, but when we think of forecasting, how do we link churn metrics into operational metrics that drive the business and the goals that you hope to achieve?
Carter: Well, we're big believers in regression analysis. And I guess Shakespeare said past is prologue. And so when you look at the activity of the past, we believe that that activity is likely to project the future. And so if you can see the trends over time with customer behavior, we think that's the best indicator for what the future is going to hold. And so that's why we look at those health metrics on the dashboard and try to figure out, OK, if we invest a dollar here, here's the likely outcome and here's the future. But again, breaking it down by cohort and by activity, you can figure out where to where to invest and reinvest and where to pull back and in which which, for instance, sales channels to start. We think that the analysis is really only useful for helping make informed decisions about how to operate the company going forward. Taking it as a static snapshot in time is a nice view, but it doesn't tell you how to operate the business, how to plan ahead, how to budget.
Michael: We tend to focus, as you point out, on the entire company not breaking things down. How do we determine once we've made a decision based upon those churn figures to implement a program, how do we know that program's working?
Carter: Ultimately, it comes back to those summary numbers on how you're doing. For instance, I was just this morning looking at a compensation plan for one of the executives in our portfolio, and he is compensated on partner health score, which is tracked by the customer success department at this company. And we think that customer health score is a leading indicator for churn. And so we want those customer health scores to be as high as possible because we think that that helps sustain the base of customers and allows any new customers that are brought onto the platform to be incremental, not replacement for a customer that may churn. So that's a good example of how these customer success programs get implemented, measured and in this case, compensated against.
Michael: Company level monthly, recurring revenue per customer at a company level can be used to figure out what's going on across the entire customer base, if I understand this correctly, but explain the critical dimensions when analyzing the effectiveness of SaaS.
Carter: So the SaaS model is interesting in that you have to build the plant first before you sell to customers. In the old world, when I got started in software, you would build software and ship it to customers physically. You would install it on their, their infrastructure. And in the SaaS world, you're putting it in the cloud, you're hosting that infrastructure and then you're trying to cover that fixed monthly cost you have to run that infrastructure. And so the metrics come into play from day one where you're trying to determine how much am I paying back on a gross margin basis to cover my fixed infrastructure costs and what we like to look at are the long term trends of investing in building that book of business over time. And ultimately, that's why we care much more about the metrics of the unit economics as opposed to the gap financials, because the gap financials don't tell you anything about how you're doing, how the profitability on a per customer basis is adding up over time to cover that fixed cost and to hopefully be profitable, which is the ultimate goal and how every company is valued in the long run, which is a discounted value in the future cash flows. And so these SaaS models and software models are incredibly profitable at scale. They're often not profitable subscale, sub a hundred million dollars, you don't usually find much profitability in software businesses. Especially in SaaS, and that's because you're running the infrastructure, not the customer, but at scale? Boy, with the recurring revenue model, they can throw off a lot of cash, which is why they trade on revenue multiples, because people believe in the downstream model effects of recurring revenues and of subscription businesses in general.
Michael: You've pointed out at the beginning of this conversation, your heritage as operators informs how you partner with companies. Help those companies understand the time at which it's appropriate to be tight lipped and the time it is, which it is not. You- many are always tight lipped at the beginning of a journey. Is that a good thing or a bad thing?
Carter: Yeah, it's a good point. We see a spectrum of transparency when we're talking with companies. Some are very guarded and some even publish them on their website to show how they're doing. The middle ground is giving out reports to friends and family and investors in the business so they can see the progress. And you can start to see what what's happening is the momentum builds. I don't think there's the right answer. But in all honesty, we find that the companies that are coy about their numbers are coy because they're not so good. And so we often find that the companies that have the data and can produce it are the good ones because they're tracking the right things and the ones that are forward about it are usually the ones that are performing quite well.
Michael: So when it comes to reporting cadence, what works? You know, we scramble for the board meeting, but to really see the difference when you're looking at a company and analyzing it for investment or even as the CFO analyzing your own company, you know, do you sit down monthly, quarterly? How do you help make decisions about pivoting for change?
Carter: Most of these B2B software companies operate on a quarterly cadence. And so we hold our board meetings typically quarterly, sometimes monthly. That's just to track what's happening more quickly and help them course adjust or give them feedback along the way. But the typical cadence is quarterly. But importantly, what you want to do at a minimum is to look back if you're doing it monthly, thirteen months, or if you're doing a quarterly, five quarters so that you not only see the sequential performance over the past year, but you're picking up that year period prior and comparing, OK, how are we doing against what we did in this period a year ago? And I think graphing this information is the best way to see it. Sometimes you'll report on a number and it sounds good, but when you graph it, you can see we're actually declining in our growth rate.
Michael: What does B2B SaaS look like as we come out on the other side of COVID-19? It seems like for the first time we're starting to talk about light at the end of the tunnel, what does that light look like to you?
Carter: I think it's already here in the B2B software world, everything that we do with our companies and our companies do with their customers, just about everything is digital. And so there's been very little slowdown in the software world through COVID. I think this part of the economy has been less affected than than perhaps any other.
Michael: It's been said that for companies outside of the world in which we're talking, if you can survive a pandemic, you will thrive post pandemic. Since B2B has largely been able to keep the machine running because of that digital nature and the infrastructure is in the cloud. Post COVID do they get the same big bump as a traditional company might that has managed to weather the storm? Or is it going to just be continuous business as usual?
Carter: I think it will be business as usual, but keep in mind that that trajectory was pretty attractive, pre COVID. So I think that the whole notion of software eating the world is a real thing. I wouldn't bet against software going forward. I think it's the dominant sector of our lifetime. And so I think that will continue unabated post COVID. But no, I don't think there will be a boost in B2B software as we return to normal.
Michael: Well, I'll tell you, I am with you. I am definitely looking forward to meeting people in person. And I appreciate your time, though, here virtually.
Carter: You bet. It was my pleasure. Thank you so much.
Michael: Carter Griffin is the general partner at Updata. By using key metrics like customer acquisition, cost, return on customer acquisition cost and gross margin payback period, innovation, economy entrepreneurs have an opportunity to understand in granular detail how their startup is performing and what it takes to attract capital. Customer acquisition cost needs to be more in depth than adding together marketing and cloud. Return on customer acquisition cost is where the churn starts coming into play and gross margin payback period helps us understand how long before that invested dollar is paid back.
Michael: This has been the CIBC Innovation Banking podcast where we learn the secrets to innovation, economy success from the entrepreneurs who are paving the way for the future. If you haven't already subscribe on Apple Podcasts, rate the show and tell us what you think with a review. I'm Michael Hainsworth. Thanks for listening.