1. A method, comprising: employing at least one processor configured to execute computer-executable instructions stored in a memory to perform the following acts: constructing a hierarchical predictive model comprising multiple predictive models across multiple levels of granularity; training each of the multiple predictive models based on accumulated data automatically at a predetermined interval; evaluating performance of each of the multiple predictive models after the training; and activating for use a root predictive model of the hierarchical predictive model and at least one child predictive model that outperforms a parent predictive model at a more specific level of granularity than the parent predictive model, wherein the parent predictive model is at an immediately preceding and more generic level in the hierarchy than the child predictive model.