On-the-go physical crowdsourcing systems aim to take advantage of users' everyday routines to complete tasks for other community members. For example, imagine that someone is picking up coffee for themself, and they are asked to deliver coffee to someone else on their way to work. Mercury uses predictive modeling to help requesters in these systems navigate the uncertainty that comes with these systems and understand how to make decisions that help achieve their goals.