In this webinar, we discuss:
- How innovators are using spatial data and analysis to make mobility planning decisions.
- Why spatial data is becoming essential in data science workflows to understand and predict patterns.
- How mobility companies use thousands of routes and data points, such as weather data, in machine learning models to optimize their scooter fleet usage.
Watch it now at: https://go.carto.com/webinars/micromobility-revolution-recorded
Multi-billion dollar industries are being
built on location data
80%Of all data collected has a
location element on it
10%Is actually used to Power
...and micromobility was born connected:
How are my
...and the market is booming:
In investments in
of investments made in
faster user acquisition than
car sharing or ride hailing
Source: McKinsey, Jan 2019
Micromobility players & cities
don’t need to know where.
They need to know why.
● Free ﬂoating services need to be able to
balance supply (scooters available) and
demand (riders wanting to book a
● Riders are satisﬁed if they ﬁnd a vehicle
within an acceptable walking distance
(typically 230 metres).
● It’s not about increasing the number of
vehicles only, it’s about increasing vehicle
availability in high demand areas.
● How can we rotate scooters from low
demand areas to high demand areas?
Options for relocation?
Users contribute to relocate in
exchange for free rides.
Space range using a van to
move scooters. Not scalable.
● Downtime = the time a scooter is inactive
between one ride and the next.
● Thinking about the problem spatially, we
can use spatial features to drive
decisions about user-driven relocation.
What if new data streams could help?
Points of interest
● A micromobility company wants to enter
a new market, but is ensure of which
cities / areas of larger cities to launch in.
● Census data is outdated, making it
diﬃcult to use that as accurate predictor
of potential success.
● The company wants to be able to see
how demand evolves over time and
changes from season to season.
● New data streams unlock insights by setting the context and elevating
models to their full potential
● Spatial analysis allows micromobility players to go beyond observing
where things happen to uncover why, and drive business outcomes
● Mobility companies are very well positioned to tap into new data and
analysis due to their digital-born nature and established data science
Thanks for listening!
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