Demystifying Churn: Measuring and Benchmarking this Metric

As every SaaS entrepreneur knows, churn is one of the single most important metrics in determining the day to day health of the business. Acquiring new customers is time and capital intensive, and this growth is meaningless if those customers do not stay.

Despite the importance of this metric, measuring, tracking and benchmarking churn often generates a great deal of confusion. A simple search for “SaaS churn” yields over 175K search results with different opinions on the right calculation and benchmarks to use. Two of the most common questions we receive tend to be around 1) calculating these metrics on your actual user data 2) benchmarks for each of these rates. I’ll aim to address both these questions in this post and have also included a google spreadsheet with an illustrative customer data set that goes through each calculation.

Businesses will typically track and measure three churn rates on an ongoing basis: customer churn, gross dollar churn and net dollar churn. Since each metric helps highlight a different trend that may be happening with your users, it makes sense to track all three. To keep it simple, our dummy data set only includes 30 customers. Thus, likely similar to any early stage business, there will be a great deal of fluctuation in the churn numbers that will smooth out as a business grows.

Customer Churn (Logo Churn)

Definition: This metric measures the number of customers you lose over a period of time. I’ve calculated this number on a monthly basis in the “Churn Calculations” tab. The formula behind the calculation is:

churn 1

Tracking the reasons customers are leaving can be even more important than tracking this number itself. Particularly, when selling to early-stage startups, you may experience involuntary churn (e.g., a customer goes out of business or gets acquired), which you may not be able to control. This churn is different from voluntary churn (e.g., customer dislikes the product and chooses to cancel or picks a competitor), which is important to mitigate.

Benchmarks: These numbers tend to significantly vary based on the type of customers you are acquiring (e.g., the numbers for a prosumer subscription business would be very different than those of a SaaS business selling to the Fortune 1000). We typically spend less time looking at customer churn benchmarks internally.

Gross Dollar Churn

Definition: This metric looks at your total lost revenue both from customers churning and from downselling (e.g., your customer on the $1000/mo plan downgrades to the $100/mo plan). I’ve calculated this number on a monthly basis in the “Churn Calculations” tab. The formula here is:

churn 2

The difference between the customer and gross dollar churn numbers also highlights the importance of tracking both metrics. As you can see from the raw numbers, my example business is good at retaining its $100 customers but loses many of its larger $1000 and $2000 businesses, a trend you might miss if you were only tracking customer churn.

Benchmarks: Best-in-class gross dollar churn is typically less than 1% on a monthly basis. It is important to note that at early stages of a company when customer numbers are small, there will be a good amount of variation on a month-to-month basis (as my spreadsheet highlights). However, over time, it should be easier to get a feel for a longer-term churn rate for the business.

Net Dollar Churn

Definition: This metric looks at the revenue you are losing from customers churning or down-selling less the gains from upsell (effectively, the change in your monthly recurring revenue excluding new bookings). I’ve calculated this number on a monthly basis in the “Churn Calculations” tab. The formula here is:

churn 3

As you can see, in months where there is more upsell than downsell and churn, you get a negative net dollar churn rate.

Benchmarks: The best-in-class benchmark for this metric is negative net dollar churn — these companies will still grow even if they did not acquire a single new customer. We saw this behavior with Zendesk, one of our portfolio companies. Once a business purchases Zendesk, it typically increases its spend with the product as it brings more agents onto the platform. At the Series A, however, there are many successful businesses that may have not yet experimented with pricing and packaging and may not see a negative net churn rate until they are further along.

 I hope this post was helpful to you as you think about measuring and tracking your own churn rates. If you have any feedback (or if you catch any errors!), feel free to drop me a line @ or reach out on Twitter @anoushkavaswani and @MatrixPartners.

For more discussion on churn, you may find the following articles to be of interest:

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Anoushka Vaswani

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  • Ari

    This is a well articulated primer on churn calculations. Thanks Anoushka! There’s another type of revenue that may be worth explicitly mentioning: reactivations. We include reactivated/revived customers in our Net Dollar Churn metric because we don’t exactly consider them new bookings. (But they’re not really “expansion” either.)

    So our Net Dollar Churn equation is: (Churn & Contraction Revenue – Expansion & Reactivation Revenue) / Start of period’s Revenue

    Is that how you would incorporate reactivations?

  • Anoushka Vaswani

    Hi Ari, sorry for the delay here! Reactivations can be a tricky one and is definitely worth calling out. If the business typically has a lot of reactivations, it may make sense to have a separate line for reactiavtions (e.g., under row 46) and break this number out. We have also seen business track the total customer base, the total active monthly customers and then look at the % active ratio over time. For the net churn equation specifically though, we have seen many software companies treat reactivations as new bookings. The one other thing that may be worth doing is looking at churn / retention metrics over a longer period of time (should help smooth out the population churning and reactivating). Hope this is helpful!

  • Kevin Meakings

    Hi Anoushika
    Thank you for writing this article on churn. I have a couple of questions
    1 How would you calculate annual churn based on the data in your sheet?
    2 We’re based in Canada and so we invoice in CAN$ locally but in USD$ to anywhere else in the world. If I calculate $churn it becomes skewed by exchange rate fluctuations which can mask what is really happening in the business. Do you have any suggestions on dealing with this type of problem please?

  • Anoushka Vaswani

    Hi Kevin, great to hear from you. On your two questions:

    1. You would apply the exact same formulas above but the time period would be a bit different. For customer churn for example. it would be the total customers that left over the course of the year / the customers at the start of the year. If you tried calculating these annual churn rates on my spreadsheet, they look very high because I am starting with only three customers (tried to keep the dataset very simple) which may have thrown you off. If you are looking at annual churn rates, I assume you have a larger customer base and these numbers should make sense.

    2. Most of the businesses we look at our US based so I have not seen a company normalize for this issue in a particular way. I would use your final financials to calculate your churn (not sure if you look at everything in USD or CAN at the end of the month) and then footnote this issue. As your customer base grows (and thus your denominator increases), I assume the impact from fluctuations in exchange rates will normalize.

  • Kevin Meakings

    Thanks for the prompt reply Anoushika. Re 1 – the only problem I see here is where customers start and leave within the 12 month period. They will show as a leaver but obviously won’t be in the customer count at the start of the year. I guess excluding these completely from the calculation is probably the best thing to do
    Re 2 – we report in CDN but prob 80%of our sales are in USD. Our costs are in CDN and so it does make sense for us to report in CDN.
    A small change in exchange rates in the year can easily distort churn data based on revenue and I see how it will normalize as our denominator increases. There must be others with this problem! I have resorted to looking at subscriber churn as an alternative but of course this ignores revenues gained from existing subscribers but it is more accurate for us than looking at pure revenue.

  • Anoushka Vaswani

    On 1, customers that start and leave within the year should still be counted as leavers (wouldn’t exclude them)