You can try the proportional hazard model https://en.wikipedia.org/wiki/Proportional_hazards_model https://en.wikipedia.org/wiki/Proportional_hazards_model In

You can try the proportional hazard model https://en.wikipedia.org/wiki/Proportional_hazards_model https://en.wikipedia.org/wiki/Proportional_hazards_model In this setting, things like age, gender, or other features of interest are the covariates/predictors. You can then also use indicator features like UK or US for geography. If the geography based features are significant, then the difference in churn between the regions is perhaps not simply due to age etc.