AI-driven target lists are built by clustering, scoring, and ranking HCPs using predictive models that analyze patient flows, prescribing patterns, and market dynamics. This ensures targets are selected based on predicted opportunity reflected in real-world data, rather than static rules.

It uses predictive analytics to identify emerging prescribing opportunities, new potential writers, and HCPs treating relevant patient populations as well as early signals of churn and discontinuation risk, allowing teams to intervene before revenue is lost.

By focusing on higher-quality, higher-potential HCPs, commercial teams have achieved up to 9× more claims per HCP and a 20% increase in engagement rates. The impact comes from improving target quality, not just increasing activity.