The churn rate is the rate of customers who voluntarily unsubscribe from the push notification subscription.
When this happens, a communication channel is being broken. They may still be customers but they no longer want to receive notifications.
We must take care that the churn rate does not increase since messaging subscription rates are directly related to greater user retention. Push notifications open direct lines of communication with your audience from which you can encourage activity and re-engage inactive users.
Remember! It costs more to acquire new customers than to retain the ones you already have.
How does churn prediction work?
Thanks to Machine Learning technology, we identify users by their probability of abandonment, based on risk profiles.
Our abandonment prediction model is trained to detect the most relevant risk factors for an abandonment outcome and assigns a high, moderate or low abandonment factor. Every week we recalculate these segments based on the historical data of the last 3 months such as geolocation, click on campaigns, age, visit to the web / app, browser, type of device…
Churn prediction filter
With the "Churn Prediction" filter you can create specific campaigns according to the probability of abandonment and select the users who will receive it.
Minimizes the cost of user acquisition by reviving at-risk users.
For example, you can create an aggressive discount campaign for those at high risk of churn while showing a campaign with new products to those at low risk.
As in any data-driven process, we need... data!
To do this type of segmentation we need to know the behavior of users, so if you have not yet sent enough campaigns you will not see this filter working. Keep sending notifications so our Artificial Intelligence can learn and segment.
Updated 4 months ago