MRR Churn

As with all SaaS metrics, there is neither a firm nor well-established method for calculation of MRR Churn. This can be an absolute number, such as $3500 of MRR churned, or a relative number, for example a MRR Churn rate of 4%.

Typically, this measurement is not performed using true GAAP reportable revenue, rather a number representative of the recurring revenue attributed to a subscription, MRR. While different methods can be used to calculate MRR, those in of themselves will not usually lead to significant variance in the core MRR numbers.

However, there can be significant variance in the MRR Churn number due to the inclusion or exclusion of upgrades/up-sells (we call “Expansion” in Maxio) and downgrades/down-sizing (we call “Contraction” in Maxio). This is especially true for business with the “land and expand” model, where up-selling is a critical component of the overall business growth strategy.

Few would argue that MRR lost due to customer cancellation should be excepted out of the calculation of MRR Churn. Many would argue that contraction should be included in the calculation. Some would argue that if you are going to include contraction, then it is only fair to also include expansion. Others would argue neither expansion nor contraction should be included.

Since there are no rules, it is important for you to define and communicate how you measure MRR Churn. First, this ensures your C-level and board constituents understand the formulae and rules well enough to have an informed opinion for you can gain concurrence for consistent reporting. More importantly, the process of defining the rules helps you also define the underlying strategic uses for MRR Churn.

For example, MRR Churn might be an essential component of your forecasting equations for your fiscal year revenue performance planning, but it is not used in the calculation of Customer Lifetime Value. By defining and documenting all the SaaS metrics you use to manage and measure company performance, you avoid confusion that often comes from personal biases and interpretations stemming from lack of industry standards.