Sonos is the leading manufacturer of the smart speaker system that streams personal digital libraries and online streaming music that users can control through any internet-enabled device. The inherent unpredictability of home internet networks, as well as the ambient environment in which their speakers live, means there are instances in which customers will experience drops in audio connections. Imagine listening to your favorite song only to have it pause unexpectedly; we’ve all experienced it—that annoying buffering while the network tries to resolve problems and reestablish a connection with its host.
If Sonos could predict the conditions under which a given device will have a drop in audio quality, solutions could be developed that would guide the user through troubleshooting steps to resolve common issues on their own—for example, rebooting the router or changing wireless channel. The Sonos user experience would be improved, and calls to the support center would be reduced, significantly lowering overall support costs while at the same time improving customer satisfaction.
Sonos turned to Pythian’s data science team to discover whether the diagnostic data Sonos was collecting from the devices included the right data to build the predictive model.