Three leading indicator SaaS metrics to understand where your business is heading
We all know the flagship metrics by which SaaS businesses are gauged — CAC, LTV, churn, and the like. Understanding these metrics is key to measuring the health and value of a SaaS business, and if you’re the operator of a SaaS company, you should have a deep understanding of what each of these metrics mean, how to measure them for your business, and whether your metrics are healthy or indicate potential issues. Every company is different, but a combination of common knowledge and some business specific reasoning should give you a sense of whether your SaaS metrics jive with where you want your business to head.
Some kinds of SaaS businesses — especially enterprise SaaS companies with medium to high price points around, say, an average ARR of $25k or more per customer — can test the usefulness of the most common SaaS metrics. NS1, for example, is an infrastructure business — IaaS — and we find that while we have a deep understanding of our cost to acquire customers (CAC, the combination of sales and marketing expense that goes into winning a new logo), customers don’t switch managed DNS providers very often once they’ve made a technology choice. This means we have incredibly low churn and as a result, high lifetime value (LTV) compared to more “normal” SaaS businesses. We also have the “problem” of being a relatively young business at right around four years. We haven’t been around long enough to understand the true LTV of our customers, so we need to resort to guessing, setting 5-year horizons or making other approximations to bring LTV into a “reasonable” range so our board and our investors don’t think we’re crazy.
Investors may care most about these traditional SaaS metrics, but we’ve found that in many cases, there are more useful metrics for us to focus on to actively steer the business. There are a number of leading indicator metrics we can observe in something closer to real time that help us understand how we’re likely to grow, how our customers are doing, and how our business is scaling to meet demand. Here are three of the leading indicators we measure at NS1:
How many new qualified opportunities are entering your sales pipeline?
Understanding your opportunity pipeline creation is critical to steering your business. Of course, it’s necessary to also understand your pipeline’s conversion metrics — How many opportunities typically convert? How long is the sales cycle? How large is your average deal? — but once you’ve been in business long enough to develop a basic understanding of the dynamics of the sales pipeline, a key driver is simply how many qualified potential customers you’re engaged with.
This metric — more so than most metrics — demands discipline in the data set, and in how you define qualification of a sales opportunity. Pick well defined criteria for converting leads into qualified opportunities — BANT, for example — and stick to them. And then review opportunity creation often (we do so weekly) and if you’re seeing stagnation over the course of a few weeks, ask why. Dig in deeply and do something about it. And if you see an extended drop-off, or a sustained acceleration, then adjust your plans — your business is going to be slowing down or speeding up when sales cycles start to come due.
How likely are your top customers to walk, or reduce their scope?
We all know that churn — customer turnover — is a key driver of the dynamics of any SaaS company. The trajectory of a company that churns 5% of revenue each month is dramatically different from that of a company churning 0.1%. And if you’re an enterprise SaaS business with relatively few customers and fairly large deals, then early in your business, before you’ve established a solid understanding of long term churn rates, any churn can be painful, even life threatening. So, don’t wait for it to happen: measure it in advance by gauging the risk that your top customers will reduce their spend, or even worse, leave.
How can you do this? It depends on your business, but if you’re big enough to have a customer success focus (which isn’t that big), you can start to guesstimate churn risk. When is the contract coming due? What are the contract’s renewal terms like? What kinds of customer support interactions are you seeing from the customer? Is the customer using the service and getting what they’re paying for? How does the account manager “feel” about the customer’s state of mind about the services they’re buying from you? (This last one sounds wishy washy, but it is a hugely important indicator.) All of these are indicators of churn risk, and should be easy for you to track for your largest customers. Review churn risk regularly (we do so monthly at NS1). If there are a couple risky indicators, then strategize on how to improve the relationship with the customer and do what you can to prevent churn before it becomes a problem. And when a customer leaves or downsizes (it’ll happen eventually), find out why, and feed that input back into your churn risk reviews.
How well-provisioned are you to manage your anticipated growth? What kind of headroom do you have?
There’s no worse feeling than closing a big deal, turning up the customer’s services, and falling flat on your face because you’ve overcommitted your service’s resources. Almost the same, nothing frustrates your revenue team like telling them to slow down, or to hold off on selling that big account, because your platform isn’t ready for the workload. Unless you’re dealing with customers with needs well outside your normal bounds, this should never happen — especially if you’re managing an effective sales pipeline — because you should be anticipating growth in the usage of your services, and scaling in advance to meet that growth, ideally with some headroom for quick expansion.
How you’ll measure capacity utilization depends almost entirely on your business, the service model with which you deliver, and the service delivery pipeline for your products, but one thing is clear: you must have a model, even a simple one, for resource utilization, and you need to drive that model based on anticipated growth in time to procure and deploy capacity in advance of that growth.
You may have a service offering that’s exceedingly simple in its technical infrastructure and architecture — a database backend, with some application servers in front — but it still pays to think about capacity. How many requests per second can you handle with a single server? What overhead is incurred with horizontal scaling? What sort of headroom do you need in place for “burst” events? Are you using a cloud provider that enables you to auto-scale stateless components of your application, or do you have a more serious lead time for provisioning and deploying resources?
Focus first on the capacity model. What are the key resources and interdependencies in your systems, and how do they relate? Then, drive the model based on forecasts. Here, you’re deriving a leading indicator that can help you decide when to procure resources, when it’s time to devote operations or engineering effort toward vertical scaling, or when you’ll hit a “ceiling” requiring architectural changes.
Understanding capacity and utilization is important not just in your technology systems, but in people systems as well. What are the triggers for hiring new sales staff, or customer support reps? How long does it take to onboard new staff and bring them fully up to speed? Building these models, and measuring indicators of utilization, can help you effectively steer the business.
Your SaaS business is probably a little different than ours, but chances are, there are some leading indicators you should be measuring to understand where things are headed. Don’t just look at CAC, LTV, churn, and other typical SaaS metrics: figure out higher frequency metrics for your business that predict where things are heading. Then, develop a guttural understanding of those indicators. The farther in advance you can understand where your business is going, the more time you have to make course corrections — or pour fuel on the fire.