Anti-churn is a cornerstone of predictive analytics applications, and our solutions let you get the most out of the analytics by leveraging industry-specific expertise-led assets and methodologies.
A careful eye for automation and control is also crucial in making sure all analytical steps are safe, effective, and as little time-consuming as possible.
Our approach to attrition is based on the use of a specifically-built data model, albeit open to customization, and a guided process though the steps needed for a successful retention project, such as:
- Single or multiple definitions of churn events;
- Multi-faceted approach to modeling letting you choose between easy automated modeling all the way up to integrated your own data-scientist-driven models;
- A methodologically sound approach to model backtesting and monitoring;
- A production facility, so that customer scores are updated automatically with the correct periodicity;
- Choice an anti-churn selection criterion for targeting (such as risk levels, risk trends, customer value, etc.);
- Molding of the best offer for each customer, based on customer habits, attitudes and value considerations;
- Monitor retention actions;
- Select control groups to thoroughly separate and measure model and action effectiveness.