Gig mobility data: What it is and what it means for your business

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The gig economy is here, and it’s taking over urban mobility in the form of ride-hailing and on-demand delivery. 

Ride-hailing has become the new favorite transportation method for people of all ages. As evidence, we need look no further than the financial results of the two industry leaders.

Uber has grown from $5.4 billion in gross bookings during Q3 of 2016 to 18.1 billion in gross bookings during Q4 of 2019.

During the same period of time, Lyft also experienced astronomical growth. In Q1 of 2016 Lyft says it had 3.5 million active riders, and by Q4 of 2019 that number had grown to 22.9 million.

The explosive growth of ride-hail was not realized by other forms of traditional transportation. According to the 2020 Public Transportation Fact Book, while ride-hail has been on the rise, public transportation has been consistently decreasing since its peak in 2014.

Source: American Public Transportation Association, 2020 Public Transportation Fact Book, March 2020.

The 2020 COVID-19 pandemic has exacerbated the migration from public transportation to ride-hail.

Using Gridwise’s network of over 200,000 ride-hail and delivery drivers, we analyzed ridership trends during the 2020 COVID-19 pandemic. We could see that ride-hail usage had significantly declined, but riders have been quick to come back.

The same is not true of public transportation, however. Based on data from Apple’s Mobility index, public transportation has bounced back more slowly, and is once again on the decline.

But it isn’t just ride-hail that’s taking over urban mobility; the demand for food and grocery delivery has soared during 2020. According to DoorDash’s recently filed S-1, their business has more than doubled since Q1 of this year.

The emergence of gig mobility will bring new opportunities for firms across dozens of industries that understand the gig economy and the immense impact it will have on mobility. Those that don’t may miss out on staying relevant as mobility continues to change. 

Let’s take a look at this emerging market and examine how gig mobility data can be used. We’ll cover:

What is gig mobility data?

Understanding gig mobility data starts with understanding the meaning of mobility, which refers to the movement of people and goods.

Gig mobility services refers to ride-hail and on-demand delivery, such as food, grocery, and parcel services. Examples of these services include Uber, Lyft, DoorDash, Amazon Flex, and Instacart, among others. 

Gig mobility data is a specialized form of mobility data; specifically, it’s data that is generated by ride-hail and delivery services. Gig mobility data helps us understand how people and goods move across on-demand delivery and ride-hailing services.

Gig mobility data makes it easy to understand supply patterns, demand patterns, gig driver wages, and gig service fleet efficiency. It helps us answer questions like:

  • From where are people or goods originating?
  • Where are people or goods going? 
  • What are the most common routes for traveling by gig-service vehicles?
  • What is the density of delivery orders or passenger trips within a given city?
  • How efficiently are gig mobility services utilizing their fleets, and what is their throughput?
  • How much do gig-drivers earn, and on what platforms?

Who would find gig mobility data useful?

Gig mobility data is invaluable for businesses, researchers, regulators, and government entities of every conceivable type. They can use the data to analyze the exact ways mobility impacts their operations, and how they can adapt their goods and services to better cater to populations that rely on ride-hailing and delivery services.

Here are some of these entities, and how gig mobility data can benefit them:

Gig mobility service providers can see how services other than their own are routing trips and allocating resources.

Cities can leverage a multitude of gig mobility data to be positioned to build the smart cities of the future by informing themselves on how to better manage the curb, improve the flow of traffic, introduce new monetization models, and more. 

Transportation organizations can better understand traffic patterns, get genuine wage information, and identify geographic areas where people might benefit from targeted economic development activity. 

Financial service providers can view service-specific economics in addition to supply and demand patterns to make more informed investment decisions.

Real estate firms can leverage origin and destination patterns to better inform site selection, accomodate more innovative parking infrastructure, and figure out the right residential areas for their clients. 

Autonomous vehicle operators can use utilization patterns, per trip/order economics, routing and traffic patterns, and more to determine areas of operation and program their vehicles for commercial purposes.

Labor organizations can leverage gig worker wage data to better inform wage standards and worker classification for gig economy workers. 

Logistics and last-mile providers can use density of delivery routes and utilization data to optimize their last-mile efficiencies..

Electric vehicle-charging platform providers can discern where vehicles go most frequently and where they dwell to determine optimal site selection for charging stations.

Retail establishments can leverage origin and destination patterns to better inform site selection of new establishments.

Airports can plan more efficient traffic management systems, properly allocate curb space, and become capable of planning for realistic needs for parking and other services.

The challenges involved in leveraging gig mobility data

The biggest challenge businesses and other entities face when trying to leverage gig mobility data is accessibility.

At best, information about ride-hail and delivery has been scattered in several different places and almost impossible to access. Why? Because ride-hail and delivery companies don’t share this data.

Some general mobility data that details the general movement of vehicles in cities is available, but cannot provide additional context into the what or the why for how those vehicles are moving. 

Current general mobility data can tell you that a vehicle is driving down the road. Gig mobility data can tell you where that vehicle is going, where it is coming from, the purpose of the trip, and the economics behind the trip.

In short, accessing gig mobility data that companies need for better decision making hasn’t been easy.

Until now that is.

How can I access gig mobility data?

Today, organizations can turn to Gridwise Analytics to understand supply patterns, demand patterns, and gig wages and efficiency in gig-mobility.

How?

We have built a network of over 200,000 rideshare and delivery drivers across the U.S., who leverage every major platform to provide analytics on how people and goods are moving across ride-hailing and delivery services.

Organizations can use data from Gridwise Analytics to gain a rich understanding of driver behavior available nowhere else.

If you’re interested in understanding gig mobility, don’t hesitate to reach out to data@gridwise.io to learn more.

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