The biggest challenge of Churn Prevention lies in finding the best measures to effectively avoid an imminent churn. In a data analysis profitability and individual requests of customers are collected. Those form crucial indicators for a successful Churn Prevention.
Measures for recovering or holding customers are often assigned a specific budget for customer retention.
The key to a long-term customer relation
Our solution identifies and simulates customer behavior. Which customer can be held by making an attractive special offer? Make targeted use of your customer retention budget using our prognostic models and stabilize your customer base via Churn Prevention. Self-leaning systems ensure constant adaptions to current behavior based on structured data, unstructured or polyglot data of your CRM, and contract management. This way, the churn rate is calculated automatically, to reduce churn.
How does this work?
Our algorithms for data-driven Churn Management include all accessible information to derive patterns and to make predictions about the churn rate. Big Data from multiple data sources is analyzed and structured to, for example, evaluate the communication with your customer.
Rotational churn describes the act of canceling old contracts, while simultaneously signing up for a new deal. In this case study, you learn how we supported a client with the analyses of customer behavior and rotational churn.