Which taxi alternative will dominate cities of the future may come down to who develops the best software. Right now, Lyft and Uber are two sides of the same ride-sharing coin: Lyft brands itself as a "sharing" experience, reminding its users that their driver is just an average Joe with time to drive you around for money. They’re essentially cab drivers, but they obey instructions from the cloud instead of a human dispatcher, and can work as they please. Uber focuses on the ride itself—the convenient and even luxurious experience of getting a car and driver exactly when you want them.
But as Marcus Wohlsen points out in Wired, the technology behind the apps is key to the services' success, and it needs to improve. People use Uber and Lyft because they’re convenient, and whichever service can offer even more convenience—faster service, that is—will probably win favor in more cities than the one that lags.
Lyft's new VP of data science, Chris Pouliot, previously led the data analysis team at Netflix, which is known for utilizing the heck out of its user data. He's got big plans for Lyft, too. "We can use data to provide more accurate [estimated times of arrival] when a passenger requests a ride, to set high expectations and provide a better user experience," Pouliot told VentureBeat in December. "The success or failure of the business is highly correlated to how the company uses data." He also hopes to make an algorithm that predicts the likelihood that someone nearby will need a car in the next three minutes. That way, each individual is sent a ride that’s convenient for them as well as the entire user base. The drivers-as-friends shtick might get a software boost, too: Pouliot imagines that a Facebook connection could tell passengers about interests they have in common with their driver.
Uber has a current job listing for a "leading data scientist," so it could be that they're still trying to get their own Pouliot-level analytics whiz.
This post originally appeared on Quartz, an Atlantic partner site.