With rental car companies embracing connected-vehicle technology, their fleets are capable of accumulating vast amounts of data, whether it's on vehicle location, braking patterns or even how often windshield wipers are engaged.
And data can translate into dollars.
On Wednesday, Avis Budget Group announced a partnership with Otonomo, an Israeli company that aggregates data gathered by vehicles and sells it to companies and public agencies that want to develop apps and services.
Under the partnership, Avis Budget's data is available on the Otonomo platform.
Avis Budget's vehicles are expected to travel 4 billion miles this year, and the company projects that its fleet will be fully connected in 2020. On the customer side, connected-car technology enables drivers to use an app to manage rentals, find vehicles and in some cases lock and unlock them, and Avis has said it envisions offerings ranging from remote start to in-vehicle retail purchases.
In a Wednesday blog post, Otonomo CEO Ben Volkow said data from Avis Budget's connected cars can be used to create smarter cities and manage traffic.
"For example, by identifying traffic 'hotspots' at certain times, streetlights can be adjusted, potholes can be fixed and resting areas can be constructed," Volkow wrote. "Real-time data can be used to issue safety alerts, while historical aggregate data can be used for long-term planning of infrastructure and transportation."
Roger Lanctot, director of automotive connected mobility at Strategy Analytics, calls data aggregation and analysis a "force multiplier" for the auto industry. Otonomo ingests more than 2 billion data points a year from more than 18 million vehicles covering 196 billion miles.
J.D. Power is an early customer for the Avis Budget data. In a statement, Dave Sargent, Power's vice president of global automotive, said the company plans to use the data for "Voice of the Vehicle" analyses. "The fleet is large, yielding high-quality data with excellent national coverage — and it is also very diverse, with over 200 makes and models, spanning multiple years in the dataset we've evaluated. We're particularly interested in the signals we get from a fleet that is constantly refreshed with a wide selection of new vehicles."
-- Leslie J. Allen