Churn prevention: Find out early if customers plan to leave

Frequently, you won’t know that a customer has said goodbye to your business forever until after it has already happened. Transgourmet was dealing with precisely this challenge. Without accurate data and reliable triggers, it was difficult to initiate targeted churn prevention measures and strengthen weaker customer relationships. Yet, you can detect some signs of potential churn early on, as long as you have the right data and the right trigger.

Lena, a customer and restaurant owner who used to place regular orders with Transgourmet, now orders fewer key products and places less frequent orders. 

With the help of AI-powered data analytics, Transgourmet recognizes that Lena’s buying behavior is a potential sign of churn and upgrades her churn likelihood. 

Since Lena is an “A” customer, Vicky, the account manager responsible for Lena’s account, receives a notification of Lena’s higher churn likelihood and contacts Lena with an individual offer or an invitation for a personal consultation. 

All other at-risk customers automatically receive a personalized voucher on their preferred channel. 

As a result of this proactive approach, Lena feels valued. She accepts the offer and continues to be a loyal Transgourmet customer.