How to reduce churn by identifying your “red flag metrics”

Edited excerpt from How One SaaS Startup Reduced Churn 71% Using “Red Flag” Metrics by Alex Turnbull:

We decided that, if we were to systematically reduce churn, we’d need to systematically study it and find its source. What I found was illuminating. There were very strong differences in the behavior of users who had abandoned Groove and the behavior of those who stayed. These are our “Red Flag Metrics”, and we use them to identify churn before it happens.

When we looked at the numbers, there were two metrics that seemed to be the most significant in the first 30 days after a user signs up – length of first session and frequency of logins. (There was a difference in total number of logins as well, but it wasn’t as disparate as the other two.) The average user who did not quit after 30 days spent three minutes and 18 seconds using Groove in their first session, and logged in an average of 4.4 times a day. The average user who quit spent 35 seconds using Groove in their first session, and logged in an average of 0.3 times per day.

So we began to send targeted emails to users who spent less than 2 minutes on their first session, as well as to those who (regardless of first session time) logged in fewer than 2 times a day in their first 10 days. We reduced our churn from about 4.5% to 1.6%.

Notes:
(1) The full article includes the text of the emails sent to “at risk” users. They’re excellent.
(2) Re. “length of first session” — see The first ten minutes of a customer’s experience are crucial.
(3) Cf. How to reduce churn and How to reduce churn — a process.

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