- Gridwise, an app that helps ride-hail drivers maximise their earnings across apps, is expanding to New York City, Boston and Philadelphia.
- In an interview, CEO Ryan Green explained how he empowers drivers to make the best financial decisions with the data from half a million trips to back him up.
- He doesn’t see himself as an Uber or Lyft competitor, but for firms that rely on data, any loss of control could be bad news in a cutthroat industry.
An overwhelming majority of on-demand drivers work for both Uber and Lyft, often toggling between the two competing ride-hailing companies dozens of times in the same shift.
For many, it’s a crap shoot of hoping the other option may have more rides available or with better prices. That’s where Gridwise comes in.
The app – which on Tuesday announced its launch in New York City, the US’ most lucrative ride-hailing market (as well as in Boston and Philadelphia) – has 20 million miles worth of trip data from half a million fares to help drivers compare demand and earnings across multiple companies. So far, it claims to have helped drivers increase their earnings by an average of 39%.
“Drivers are leveraging a lot of different sources to plan ahead and understand when they should be out on the road, when it’s going to be the best time for them to drive, looking at events, the weather, and a lot of different factors that actually impact people’s earning,” Gridwise CEO Ryan Green, a former driver himself, told Business Insider in an interview.
“All of this information is fragmented across sources and some of it’s even inaccessible.”
Tuesday’s announcement of expansion into New York City, Boston, and Philadelphia precedes plans to launch in every major US city over the course of 2019.
Gridwise, which has raised about $US750,000 worth of venture funding after graduating from the TechStars accelerator in 2017, can also help drivers decide where to wait for new ride requests. If a fare has taken them out of a dense city center to the suburbs, for example, the app can help them decide whether it’s worth circling residential streets or heading back downtown.
All of this crowdsourced data powers machine-learning models on Gridwise’s back end, and it helps the company serve up highly targeted advertising to drivers. They may see ads for insurance services or other aftermarket car accessories, for example.
“The beauty of our technology is that you don’t rely on integrating with any of the service providers,” Green said. “We’ve embedded ourselves into this workflow of a driver, so when they start driving for a shift they will turn on Gridwise and then they will turn on the other services they drive for.”
But all this data could also take away some level of control from the companies, who also use every parameter of driver data to maximise revenue and rides. And while Uber, which is known to monitor how smooth rides are, may not tell a driver where to go between fares, other companies like Via aim to have drivers following a set route at all times to maximise efficiency.
After all, each competitor only has access to its own data, and no one else’s.
This could be especially helpful when payout rates change, like the ones that Uber has been rolling out for select cities recently. Many drivers have told Business Insider they aren’t pleased with the new value placed on time, as opposed to being paid purely by distance – even if Uber says it is to help their pay remain consistent.
Data from Gridwise could theoretically detect which trips will pay more after a change, before a single driver can piece together anecdotal evidence.
For now, at least, Green isn’t scared of angering the giants in the room.
“I see us as complementary, if anything,” he said.
“Increasing the welfare of rideshare drivers is beneficial for Uber and Lyft. One of their biggest challenges is the churn of these drivers.”
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