How Real-Time Analytics Have Made Uber A Success [PSFK SAN FRANCISCO]
PSFK talks to Bradley Voytek about consumer data and how it can provide insight into behaviors and purchase decisions.
We are very excited about returning to San Francisco on November 21 to present the fourth volume of PSFK’s Future of Retail report. We have a line-up of speakers confirmed with more to come, hailing from companies such as Google, Zappos, and Foursquare.
One of these speakers will be Dr. Bradley Voytek, Assistant Professor of Computational Cognitive Science and Neuroscience at University of California, San Diego and the Data Evangelist for the on-demand car service company, Uber, Inc. In his neuroscience life, Brad studies cognition, and neural network communication, and brain-computer interfaces. He co-created the meta-analytic neuroscience research aggregation tool and hypothesis generation site http://brainSCANr.com with his wife Jessica Bolger Voytek. He’s an avid science teacher and outreach advocate and is the world’s zombie brain expert.
We spoke to Bradley about what Uber is up to and the effects of real-time analytics on where people choose to go to spend their time and money.
Tell us about Uber and the recent work you have been doing.
I’ve been very interested in how Uber users move around their cities. I can look at a snapshot in time – say 10pm Friday night in Manhattan – and look at a graph showing how people are mostly moving between certain neighborhoods like the East Village and the Lower East Side as opposed to, say, from the Financial District. Every city has a “flow” of people moving between different neighborhoods at different times of day. It’s amazing. Digging deeper, you can get a feel for these neighborhoods and how people use Uber in them. For some neighborhoods at some times of day, people are more “picky” and likely to close the app without requesting a car if the nearest car is more than, say, four minutes away.
What are the larger changes in consumer behavior when it comes to retail and shopping habits?
The introduction of smart-phone enabled services will be changing shopping habits a great deal, I believe. Location and time-aware services such as Google Now and some of Apple’s services are going to have a big impact. However, Uber is not involved in the retail domain.
How do you see the trend of real-time analytics, which lets retailers take immediate action thanks to access to up-to-the-minute data, changing the retail landscape?
Expanding on the above point, location-awareness will allow for ad revenue driven companies to provide real-time experiences based on where you are. If you pass by a Starbucks, say, your Starbucks iPhone app could push you a coupon to incentivize you to come into the store.
How is Uber navigating this trend?
Uber is famous for its real-time supply and demand management but we have no ads or any presence in the retail domain. For Uber, real-time analytics allow us to examine when demand is high and when supply becomes limited as the system reaches capacity. Uber can incentivize more drivers to come onto the system by dynamically increasing the cost of a ride, which helps regulate both supply and demand in real time.
Thank you Bradley!