February 21, 2019

Zoba raises $3 million to help mobility companies predict demand

Scooter share, bike share and ride hailing are quickly becoming staple commodities in cities all over the world. As companies in those respective spaces try to improve their economics, Zoba is aiming to contribute to those goals by predicting demand for scooters, bikes and, eventually, rides in particular areas. To support Zoba’s mission, the company has raised a $3 million seed round led by CRV with participation from Founder Collective, Mark Cuban and others.

Using spatial analytics, Zoba aims to better understand the relationships between different phenomena in order to improve the efficiency of cities. Mobility is Zoba’s first focus, Zoba co-founder Dan Brennan told TechCrunch. More specifically, Zoba looks to better understand the relationship between demand and environmental data (e.g. weather), as well as city layout. From there, Zoba helps mobility companies determine the best places to put their vehicles.

“The key is this type of spatial analytics and machine learning is very specific,” Brennan said. “You don’t see a lot of data scientists trained in this. What we do is say, ‘no matter what skill set of your data scientist, you can look at all this spatial and temporal stuff.’ We’ll make it like you have three really highly trained spatial data scientists.” 

Zoba would not disclose which companies it’s working with, just that it’s working with some of the industry leaders in bike, scooter and car share. Down the road, Zoba also envisions working with on-demand delivery companies, as well as urban logistics companies.

“The world is experiencing a Cambrian explosion of smart mobility and logistics services, all requiring geo-based forecasting and optimization,” CRV general partner and Zoba board member Izhar Armony said in a statement. “We knew after meeting with the Zoba founders that they’re the best team to tackle this hard problem. What they’re doing will change the way we live and we’re excited for what’s to come.”

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