User Churn Teardowns & Best Practices

User Churn - Teardowns & Best Practices

Why reducing User Churn is important

As a SaaS company becomes larger, the size of the subscription base becomes large enough that any kind of user churn against that base becomes a large number. That loss of revenue requires more and more bookings coming from new customers just to replace the churn. As a result growth slows substantially.

It is possible to run a SaaS, or any other kind of recurring revenue, business in such a way as to get what I call Negative Churn. This happens when the expansions/up-sells/cross-sells to your current customer base exceed the revenue that you are losing because of Churn.

If you are presenting your SaaS company to a VC, expect them to pay very close attention to your user churn numbers, even if you are early stage. They will be looking at churn as a great indicator of whether or not you have good product/market fit.

Why I’m doing User Churn Teardowns

I like UserOnboard and the kind of teardowns Samuel is doing. But while he is focussing on the onboarding of new users (basically the top of the funnel), I consider the drop out at the bottom (aka user churn) even more important -, especially for SaaS companies.

This is why I wanted to share my experience from building high scale digital products over the years with you so you can benefit from the user churn prevention best practices and mistakes the top companies out there make.

The goal is to look behind some of the most popular cancellation processes out there and point out obvious improvements and highlight examples worth following. So you can apply those mechanics to your own funnels to further reduce churn.

Available User Churn Teardowns

How audible does Churn Prevention

How Amazon prime does Churn Prevention

How Linkedin Premium does Churn Prevention

Why and When Users Churn at all

  1. Users churn if they don’t complete activation
  2. Users churn when retention efforts fail
  3. Users churn when they become frustrated
  4. Users churn when the product team confuses correlation with causation

Suggest the next User Churn Teardown

Tweet at me suggesting a (paid) service you’d like to see a teardown from.