How to fight against customer attrition?

The fight against customer attrition is a real problem for companies faced with customers who are still in their database but inactive. 

Inactive customers: customer attrition

When you work on your animation strategy, you often find that you have to deal with a major problem: the inactivity of some of your customers. Indeed, as soon as an activity has a certain age, we quickly notice that the inactive segment will take a preponderant place in the customer file. However, these inactive customers, apart from no longer being of any use to the brand, will often have a cost (hosting the data, promotional actions to reactivate them, etc.). As a result, fighting against customer attrition will become an issue that should not be neglected.

Treating attrition: curative or preventive

When it comes to dealing with customer attrition, there are two ways to look at it: curative and preventive.

1.    The curative method 

Traditionally, retailers deal with attrition in a curative way. Two main devices are then implemented: 

• Triggers: these are set up to act automatically as soon as a drop in activity or prolonged customer inactivity is detected. Depending on the existence or not of a customer segmentation, different types of triggers can be used to refine the actions to be implemented
• Reactivation actions: because when a customer becomes inactive, it means reactivation action. As a general rule, the longer a customer is inactive, the more difficult it is to reactivate them. The animation plans therefore favor the reactivation of inactive customers whose last transaction is recent.

Unfortunately, working on attrition in a curative way is sometimes already too late and the efforts to reactivate a customer can be as important as recruiting a new one. This is where preventive attrition treatment is of great interest.

2.    The preventive method 

Indeed, the idea of the preventive fight against attrition is to anticipate the fall into inactivity by setting up a predictive model. This attrition score will allow us to estimate the probability that a customer will become inactive in a given time frame. It is then necessary to determine the period during which we want to measure the activity or not of the customer. Thus, based on past data (customer profile, consumption data, actions and reactions to animation actions, etc.), it will be possible to calculate the adaptation model and thus anticipate the fall into inactivity.

Once this probability has been calculated, we can then define a specific target in the animation plan on which we will implement retention actions. These actions will be either through specific offers designed to encourage customer consumption, or relational actions to encourage customer commitment. The general idea is to reduce the cost of retention actions (volume of messages sent, generosity rate…) compared to reactivation actions while improving performance.

How does datacadabra deal with attrition?

datacadabra allows you to deal with issues related to attrition. The Segment module allows you to build easily active segments on which to define triggers. The proposed transition matrices will also allow you to measure the different issues of the animation strategy. At the same time, the Predict module will allow you to work on different scores, including the attrition score.

Want to know more? Do not hesitate to contact us or to ask for a demo of datacadabra