Prevent customers from leaving with predictive churn scoring

Churn, as scary as it is real, means the end of a relationship. It affects all businesses at some point and no one, not even the most successful retailers in the world, are excluded. Churn is a fact and you have to work very hard within every corner of your business to prevent and reduce customer churn. One very effective way of managing this is to measure and act on predictive churn scores. In other words, the likelihood of a customer leaving you. 

Your CRM platform, in this case Voyado, will keep an eye on each customer’s overall engagement to make an assessment whether this customer shows signs of declined interest in your brand by looking at things such as opening rates, click rates, purchase frequency, etc., Voyado then presents the probability of each customer leaving you.

The churn scoring predicts behavior with a certain margin of error. Using this type of values means that you can keep an eye on those customers which are predicted to have a high risk for churn.

Score Description
0.0 – 0.50 Active (Low churn score)
0.51 – 0.69 Declining (Medium churn score)
0.70 – 1.00 Churning (High churn score)
How to take action on predictive values

If a customer has a high churn rate, it is very likely that he/she does not open your emails often and does not have an overall interest in your brand anymore. For this reason, it is recommended that you test different channels to approach the customer to see which channel works. Go back and see if they’ve opened more SMS than emails historically for example. Or perhaps they might be a price sensitive customer who only act on sales communication. Knowing why they score is low can help you segment out those who should receive less communication from you, to stop them from leaving all together.

 

Prevent churn as early as possible

We recommend that you combine the predictive churn score with recent behavior. Set up an automation that fetches possible churners and process them with offers relevant for their profile. Here is an example:

  • At the end of every month, check which customers that made a purchase during this past month.
  • Now check the churn scoring. Is this customer flagged as a potential churner? If so, this could in fact be the last purchase in quite a while.
  • How do you rank this customer? Is this a customer who usually have a large order value or receipt? Then this is a customer you might want to spend some money to make sure they don’t leave (offers, campaigns, etc.)
  • If this is a customer that does not have a large order value in the past, well you might want to try and keep them around but maybe not spend a lot of your budget on trying to do so.
  • Create a randomized split and try different channels and measure the response.

 

No brand is safe from customers leaving, but with Voyado you have all the tools you need to prevent as much churn as possible. Identify dropping scores early, analyze the reason for why they are becoming less active and set up campaigns and tests to keep them coming back. If you’re not yet working with churn score automation, get in touch to book a demo today.