Canceling the Noise in Your SaaS Metrics

Disclaimer: the numbers presented in this article serve only as examples, and do not reflect any of WalkMe’s actual data.



Everything comes down to data, in high tech businesses like SaaS and elsewhere. Data can be a fragile thing. One little mistake and rather than gold in your hands, you’ll have something considerably less precious—bad data.


Bad data means that, instead of valuable insights about your company’s performance, efficiency, and overall trajectory, you’ll have distorted numbers that hide far more than they reveal.


It’s very important to make sure that the data metrics capture the subtle nuances of your company’s situation. If they’re painting an overly rosy or bleak picture, the decisions you make will be correspondingly off mark.


Especially if you’re a SaaS startup, your metrics may not be precise enough to truly capture the nuances and characteristics of your company—the places your company is ahead of the competition, the places where you’re lagging behind.


Maybe you’ve been looking through funhouse mirrors and while you may not be as gargantuan and thin as you’d been told, you probably aren’t as stout and spherical as some of your metrics would suggest either. You deserve to know the truth, the whole truth, the cold bright truth that illuminates and cuts through the chaos.


It’s imperative to refine how you calculate SaaS metrics so that you’re removing much of the noise from your data. Here are a few common examples for how to do this.

Problem of Attribution

Now, let’s say that in the following quarter, the number of customers that you’ve added stands at 600 so that your CAC is $1000K/600 = $1,667. How do you know what percent of the customer acquisition increase can be attributed to the expansion of your sales team and what can be attributed to the increased marketing spend? The answer is by separating out your CAC. Marketing CAC can be calculated by multiplying total marketing spend by the percent of total leads in the segment, and sales CAC by multiplying total sales spend by the percent of sales representatives selling into segment.


Marketing CAC = Total Marketing Spend * % of Total Leads in the Segment

Sales CAC = Total Sales Spend * % of Sales Reps selling into Segment


Further divide marketing spending by campaign. Maybe you experimented with a marketing campaign that failed and ended up bringing up your overall CAC drastically. Looking at your Marketing CAC might tell you to cut marketing expenses dramatically. This is misleading. However, if you isolate the failure, you may find that the rest of your marketing was, in fact, cost effective.


Also, we all know that the timing of revenue and expenses are not perfectly aligned. It can take one or two quarters before you see the effect of a new marketing campaign. Lag your expenses accordingly, so that revenue and expenses show up in the same quarter. Every CEO has a sense of how long the lag is for his or her company.


Net New MRR

Say you calculate your MRR by multiplying the total number of your paying customers by the Average Revenue per User (ARPU) per month. So, 600*$167/mo = $100,200. However, this number doesn’t tell you how that number expanded or contracted over previous months. If your MRR grew by $5000, you’re going to want to know from where. Net New MRR tells you from where because it not only takes into account new revenue, but also account upgrades, downgrades and churn. For that reason, Net New MRR is more informative and predictive of future growth than regular MRR.


Expansion Rate

Say you want to focus in only on your expansion rate. You’re counting your upgrades. Keep in mind that your smaller customers may already be receiving the maximum level of service they can afford. In this case, your true expansion rate is one where you’ve cleaned the clients who are already at this point. To arrive at your expansion rate, divide the number of customers who expanded over the number of customers who had the financial ability to expand. That’s to say, keep your client profiles in mind when calculating expansion so that you don’t underestimate your draw amongst customers.


Real Churn

Your churn is probably higher than your realize. Say that you’ve got 2000 customers and 50 of these customers churned in this quarter. Standard churn calculations would tell you that your churn rate is 50/2000 = 2.5%. This calculation is artificially low because it doesn’t remove customers who don’t have the option to leave. “Churnable” customers are those who could have feasibly churned – those with expired contracts, customers up for renewal and those customers with out-clauses in their contact. So, say that, of your 2000 customers, only 1000 were “churnable”. Now, your churn rate calculation has doubled to 50/1000 = 5%.

Churn Rate Calculator

In a given period (month, quarter, year etc.)

? not including customers with an out-clause in their contract or customers whose contract expires in this period

As you can see, the discrepancy between the standard and the refined metrics is fairly significant. A churn rate being twice as much as expected is something you’re better off knowing, even if the truth is a bitter medicine.  And knowing where your CAC expenses are actually coming from is a lot more useful than just knowing the lump sum. In a world where revenue can vary substantially from month to month, a number with predictive power does a lot more for you than static MRR.


It’s time to get out of the fun house and make sure you’re working with good data that really reflects the financial viability of your SaaS.


For information on how to correctly calculate your Net Promoter Score, click here.



An editor of SaaSAddict Blog. The SaaSAddict blog was established to create a source for news and discussion about some of the issues, challenges, news, and ideas relating to SaaS and cloud migratio