It’s no secret that Uber is powered by data. The ridesharing service is built on analytics and famously encourages passengers and drivers to rate each other. But data scientists at the company aren’t just focused on the service’s core functionality. They often delve into some pretty nitty-gritty details of how passengers use the service–and they can dig up some unexpected insights in the process. Using Bayesian statistics, Uber’s data team showed how it’s been able to accurately predict the destination of its users three out of four times. To do this, they built an algorithm designed to figure out specific destinations–not just the intersection or another rough approximation, but exact addresses–and then tested it against the actual behavior of 3,000 anonymous Uber riders.