Are your SaaS Metrics Inaccurate? Don't include these customers...
Who do you consider a user to be? Is a user someone who uses your product? Is it someone who signs up, or is it somebody who signs up? Or is it someone who is actively engaged with your product? Or someone who made a few visits or logged in briefly?
Perhaps describing a user is difficult.
Let's try to define who a customer is.
You have a customer when they purchase your product or service. Are they within the legal timeframe to request a refund? Or a "cooling down" period stipulated in the contract? Alternatively, what if they're still around after the 60-day "stick point" has passed? Or… So defining a customer is a challenge as well?
You'll have to deal with even more challenges if you're in an industry where customers are more transient, if you're providing free or freemium products, if you've just started and there's a lot of interest from early adopters, etc.
Users and customers are often referred to as the same thing. If you find yourself using these two terms interchangeably, you are not the only one. To be honest, the distinction between a user and a customer has perplexed many individuals, especially in the SaaS market. You need to change how you define a customer (or user), which is the key contributor into how you determine the basic metrics of your SaaS business. Let's dig a little deeper into this...
Definition of a Standard User
For your estimates, you might simply use the primary definitions of users and customers. Use roll-up metrics if your board or investors wish to see them. However, most boards and investors will want more granular.
However, like with other elevated roll-up metrics, the true inner-workings of your firm can be disguised (obfuscated — often purposefully... not always though), constraining the actionability of those metrics.
Identifying Users in a Realistic Manner
Finally, to identify "users," you should definitely start with those who are "engaged" with your service or product.
This entails moving away from low-value measures such as "sign-ups," "visits," "logins," or even basic "activity" and toward particular metrics such as "contextual interaction," or interaction that shows whether the user does something worthwhile.
This will very likely lower the number of "users" you have, which may hurt your ego, but it will provide you with a clearer, more realistic picture of what's really happening in your business.
Same thing applies to customers as well...
Not all customers are capable of churning (At least not right now).
The most basic churn estimates compare the amount of users at the beginning and end of a timeframe (say, a month).
This metric, however, assumes that all customers are capable of churning. That will not be the case with the majority of SaaS models. A segment of your customer base will be unable to churn due to contractual obligations.
Incorporating these clients into your churn rate, will skew your calculations and make it appear as though your churn rate is less than it is; for example:
By including non-churnable clients, you discovered that your churn rate is actually 10% greater than you had estimated. Underestimating churn by ten percent will quickly become a serious issue for a developing SaaS business.
Fortunately, you may follow this to avoid it:
The Typical Churn Estimation (Simplified)
This is how many customers we had when we first started: 300
This number of customers churned: 30
Left with this number of Customers: 270
Customer churn rate is 10%.
Customer Retention Rate (CRR): 90%
Including Only "Churnable" Customers
Initially, we had the following number of Customers: 100
This many clients fall into the category of "unable to churn": 13
Begun with this number of churnable customers: 87
This number of customers churned: 10
Now that you've got this many Authentic Customers: 77
Customer churn rate is 11%.
89 percent of customers are retained.
While this example may not appear to be significant – it only represents a 1 percent difference – when seen in terms of the number of customers who potentially churn, it represents a 10 percent increase in churn rate. It's safe to say that a modest percent will quickly add up to a considerable amount.
While it seems sense that some customers are not eligible for churn, in order to obtain a more accurate number, we must admit that other customers should not be considered customers... yet.
Not All Customers can be called Customers (Atleast not right now).
All of your SaaS metric calculations should only include customers who are genuine customers, just as you would when calculating churn.
Many SaaS businesses will have a cluster of customers (Measuring churn independently across each of these clusters will provide far more understanding into the variables that contribute to customer churn – and make it a lot easier to manage them. Create SaaS Buyer Personas to assist with this) that – right after the transaction or immediately after their transition from trial version to paid version – should not be regarded a customer at this time.
Maybe it's a group of customers acquired through Product Hunt, a package with other SaaS services, or a discount campaign, that you're unsure will stick around.
Or, as indicated earlier, it could be a Cluster that is still within the legal period for a refund or hasn't hit the "stick point" for your product – in which case you don't want to factor them into long-term revenue estimates just yet.
You also don't want to factor them into "actual" churn numbers just yet because the churn rate for this "quite-early" cluster may be higher. Aside from that, they'll have different churn reasons (such being oversold, not receiving onboarding information, or exercising an opt-out option) than more tenured clients. As with the rest of your customers, you will seek to reduce churn in this cluster, but not in the overall churn estimates.
It's actually not that difficult to produce some pretty substantial results.
Sure, you can use any metric you want externally to demonstrate how amazing you are, but internally – if you seek to know exactly how things REALLY are – you should be transparent about how you evaluate metrics by starting with precise customer and user definitions.
