What is churn, and why it caps your growth

In this episode of Datadrivet, Joni Lindgren and Jasmin Yaya dig into churn, the rate at which customers leave, and why growth depends as much on keeping customers as on winning new ones.

Their starting point is simple. There are two reasons to measure and lower churn. The first is to save money, by spending acquisition budget only on the customers who can actually become loyal. The second is to earn money, because keeping an existing customer is cheaper than landing a new one.

The episode gets concrete with three everyday examples:

• Hello Fresh: a referral brought a new customer in, but a weak onboarding meant they never got going, and they cancelled.
• Netflix: a viewer finished a series in a rush, drifted off, and cancelled three to four months after they had already stopped watching.
• Headspace: a user kept paying for a meditation app for a year and a half, unused for the last six months, holding on to the identity of someone who meditates.

Each story points at a different cause: broken onboarding, a value gap after the first burst of use, and a subscription people forget to cancel. Different problems with different fixes, which is the whole reason to measure churn rather than guess at it. (The hosts also have fun with how hard some companies make cancelling, noting the oldest YouTube clip for “how to delete your Amazon account” goes back to 2016.)

The takeaway: treat churn as a set of distinct leaks, find which one is yours, and fix that one.

Listen to the full episode of Datadrivet for the examples in detail. If you want to know whether your own churn is normal for your model, that is what the benchmark tool is for: https://benchmark.scilla.studio