About

I built a machine learning model to predict which Zerve users will upgrade to paid plans. Using 409K user events, I engineered engagement features (sessions, events, AI tool usage) and trained a Gradient Boosting classifier.
The model achieved 0.79 ROC-AUC, identifying that users who explore more
features are most likely to convert. This can help prioritize sales outreach.