Case Studies: Chapter 10 – Behavior-based Retention Marketing

US Telecom pioneers retention marketing based on digital behavior

This US Telecom company was one of the first to include website behavior data in their churn risk calculations. Their rationale was a no-brainer. If a customer is about to leave, there is probably some behavior they do during their website visits that differs from the behavior of happy customers. But what is that behavior?

To find out, the customer marketing team exported web behavior data from their web analytics system for a test set of 500 customers that closed their accounts, and 500 that didn’t. This data included journey-level information, e.g., what self-service tasks did customers perform recently? Then, they ran this through their predictive analytics tools to correlate behaviors with subsequent churn. The tools quickly identified the major leading indicators. 

For customers on personal accounts, it turns out that an address change was a significant indicator predicting churn.  On the other hand, the telltale behavior for business accounts was checking their rate plan. So the Telecom added these leading indicators to their churn risk modeling and retention marketing program. The result was over a 10% lift in the program’s success.

Before enriching with Experience Analytics data

Pageview level data is an indicator of the purpose of the website or app interaction.

After enriching with Experience Analytics data

Digital Body Language will provide a better understanding of the customers’ mindset and risk. For example, are they frustrated and have made up their mind? Or are they just weighing their options?

Additionally, even if the customer wasn’t at risk before their latest session, are they actively experiencing frustrations on the site or app that put them at risk now?