Indigitall: Boost Your Campaigns with Geolocation and Geofencing

What is the Churn Rate in notifications and why is it important?

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.

What are the causes and how can you avoid losing subscribers?
If we know which customers are in danger of leaving and their causes, we can implement actions focused on retaining them.

• The messages are received as annoying when impacting at inappropriate times.
  • Impact at the optimal time: use the sending with ‘Best Time‘ so that each user receives the messages at the most appropriate time.
• It does not attract attention.
  • Personalize messages, for example, by adding the name of the campaign recipient.
• Users receive too many notifications.
  • Segment using interest groups or filters for example based on geolocation.
• Communication is unattractive.
  • Study how to improve campaign communication: Use a/b testing to create more than one notification for the same campaign so you can test and learn which messages have the greatest impact.

How indigitall uses Machine Learning to predict Churn
Of course, you can’t predict the future perfectly, but you can detect which users are the most likely to unsubscribe from notifications.

From indigitall we identify users by their probability of abandonment, based on the risk profiles we generate through Machine Learning. 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. We have based on the historical data of the last 3 months taking into account geolocation, click on campaigns, age, visit to the web/app, browser, type of device, etc.

We’ve added a new filter so you can send a special retention campaign to one of the segments.

With this filter you can create specific campaigns according to the probability of abandonment of your users. For example, create a discount campaign for those at high risk of churn while showing a campaign with new products to those at low risk. In addition, if you need to, you can incorporate these segments into your CRM using our churn prediction API.

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 active. Keep sending notifications so our AI can learn and segment.