Churn

Churn (or churn rate) is the percentage of customers or revenue a company loses in a given period, typically measured by month or by year. It is the mirror metric of retention: if you retain 90% of your customers, your churn is 10%. In subscription or recurring revenue businesses (SaaS, telecommunications, financial services), it is one of the indicators that best predicts the health of the business, because every cancellation erodes future revenue.

It is calculated by dividing the number of cancellations in the period by the customer base at the start. There are two complementary readings: customer churn (how many accounts left) and revenue churn (how much recurring billing was lost), which do not always match, because losing one large customer weighs much more than losing several small ones. Measuring it well requires bringing billing, usage and support data together in a single view, which is the kind of work done on the analytics of Metrix.

How it is calculated

The base formula for customer churn is simple: cancellations in the period divided by the starting base for that period, expressed as a percentage. If you start the month with 500 customers and lose 25, your monthly churn is 5%. The subtlety lies in the numerator and the denominator: do you count only explicit cancellations or inactive accounts too? Do you include the month's new customers in the base? Defining these rules up front is what makes the number comparable across periods.

Revenue churn is usually more relevant for the business. It measures what percentage of monthly recurring revenue (MRR) evaporated through cancellations or plan downgrades. When a company manages to make expansions and upsells from the customers who stay outweigh what it loses through cancellations, it reaches negative revenue churn, the holy grail of subscription businesses, where the base grows on its own without adding new customers.

Why it matters so much

Churn determines how long you keep a customer and, therefore, their lifetime value (LTV). A monthly churn of 5% implies an average lifetime of 20 months; bringing it down to 2.5% doubles it. Since acquiring customers costs money (CAC), high churn means you are filling a leaky bucket: you spend to win customers who leave before paying back the investment. That is why, at many companies, cutting churn by one point pays off more than adding new traffic.

A concrete example

An Argentine SaaS company that bills small businesses for a plan of 40,000 Argentine pesos (ARS) a month starts the quarter with 300 accounts. It loses 18 customers, but at the same time 12 existing customers move up to a higher plan. Customer churn is 6%, but when the team cross-checks billing in its dashboard, it finds that revenue churn is only 1.5%, because the expansions offset almost all the cancellations. Without that cross-check, they would have overestimated the problem and gone after the wrong cause.

Voluntary vs involuntary churn

Not every cancellation comes from dissatisfaction. Voluntary churn happens when the customer decides to leave (they found a competitor, they stopped seeing value). Involuntary churn is caused by payment failures: expired cards, bank declines, insufficient funds. In Latin America, where card replacements and spending caps are common, involuntary churn can account for a significant share of cancellations, and you recover it with payment retries and reminders, without touching the product.

Common mistakes when measuring it

• Mixing customer churn with revenue churn and drawing crossed conclusions.
• Changing the definition of "cancellation" between periods, which breaks comparability.
• Measuring only the average without segmenting: churn among new customers is usually much higher than among mature ones.
• Ignoring involuntary churn and treating every cancellation as a product problem.
• Calculating it on a base that is too small, where a single cancellation distorts the percentage.

Churn vs retention: two sides of the same coin

For customer churn the two add up to 100%, so measuring one is equivalent to measuring the other. The choice is usually cultural: teams that want to act on leakage look at churn; teams focused on loyalty look at retention and net revenue retention.