Access this on-demand session to learn how predictive analytics can help you identify customers at risk of churn early enough to act. Many organisations are rich in data but struggle to extract the signals that matter. With multiple channels, growing data volumes and fragmented customer histories, it can be difficult to see the patterns that indicate declining engagement. This session shows how predictive analytics cuts through that complexity.

You will learn how to use behavioural and transactional data to surface the key drivers of churn before customers decide to leave, enabling you to focus retention efforts where they will have the greatest impact. The session explains how churn models generate individual risk scores, how to interpret them and how to optimise interventions by selecting the right channel, message and offer for each at-risk customer.

Real examples illustrate how organisations have deployed predictive models to reduce churn and increase revenue, including cases where targeted retention strategies have delivered significant financial gains. This is a practical, accessible introduction for anyone who wants to shift from reactive churn detection to proactive churn prevention.

In just one hour you will learn:

• What predictive analytics is and what it could mean for your business.
• How to build a timely churn retention model that prevents defection before it happens rather than identifying patterns after customers have already decided to leave.
• How to build predictions, including identifying key risk groups and individuals from patterns in their transactional history.
• How other organisations like yours are already using predictive analytics to reduce customer churn. For example, you’ll discover how one B2B security company reduced its customer churn by 30% and generated more than £5 million in additional revenues by deploying just one predictive model.
• How you can deploy risk scores generated via predictive modelling back into your business for use in live customer interactions.