To figure out the number of accounts up for renewals, most businesses typically look back either one month or one year. Then, for those same customers up for renewal, they ask: how many of them have canceled?
Let’s imagine that you are a B2B SaaS company and one year ago you had 5000 subscribers. Fast forward to today and 635 of that original 5000 customer cohort have canceled or not renewed.
Annual customer churn rate = 635 / 5000 = 12.7%
Notice in the calculation that customers added over the past year are not included in the numerator or denominator of your churn calculation. This is because they were not subscribers one year ago. It is important to stick to a single list of customers when running churn calculations. There are two important decisions to make when using this formula:
Do I want to express churn or retention?
Some businesses prefer to track retention rate instead of churn rate. They feel it is a more positive way to frame the metric. Retention is simply defined as 1 − Churn Rate. In this example, a 12.7% churn rate corresponds to an 87.3% retention rate. It makes no dierence if you choose to calculate churn rate or retention rate, though keep in mind that most benchmarks report statistics in terms of churn.
Is it better to look back one month or one year?
Base this decision on your typical customer renewal term. For example, if your customers are typically signing up for annual subscriptions, then an annual churn rate most naturally aligns with your business because it is over the course of the entire year that your business has to provide value to get your customers to renew. Alternatively, if your subscriptions have month-to-month terms, then your retention occurs each month, and so, a monthly churn rate aligns.
Customer churn rate is a useful subscription metric because you can also use it to calculate the average life expectancy of one of your subscribers since your churn rate is inversely related to the age life expectancy of your customers, as indicated by the following formula. In the prior example where the average annual churn rate was 12.7%, the average life expectancy of a customer would be: Life expectancy = 1 / 0.127 Annual churn rate = 7.9 years