What if we turn an altitude map (a tree of metrics that influence each other) on its head? We get a depth map of negative metrics we try to combat to fight churn.

• Value Loss instead of Value Capture

• Value Destruction instead of Value Creation
  

Looking at your product in this way can be quite interesting.

Let's look at "churn" the same way we look at revenue:

• No single team should directly impact revenue, the metric is not outcome-based and it's usually hard to influence directly.

There are metrics that contribute to revenue, like in our case the number of documents that a user processes. That is influenced by their engagement and so forth.

What if we apply this to churn? Suddenly you get metrics that you never looked at or used. What if we attribute a churn score to our users that starts to go up every time they do something dangerous?

These actions increase their 'score':

• Visit the support page

• Visit the cancellation page

• One of their uploads/transactions failed

• Did they encounter a server error?
  

Their "danger" of churn starts to increase. We can fight this in two ways:

• Reduce the occurrence of these events -> Product / CS Teams,

• Introduce (in the case of B2B) high touch intervention by sales for valuable accounts as soon as they go above a certain score > Sales Teams
  

This shows how we can ideally treat different metrics with different channels. Whatever is the best for these particular groups of customers/users.

This will require that you start to do account-based reporting in some way and think about your users in a different way. (Attributing to individuals scores)

And as shown in the graph excellent KRs to influence teams in the entire organization:

Low churn means high LTV and high retention.

Easy, isn't it? :D

#data #productmanagement #retention