Device data is good. Mobility data is better
In chapter 1, we work to establish the modern definition of “mobility data,” which is essentially telematics data that has been contextually enriched and ready for analysis and use in real-world applications.
In chapter 2, we discuss why we, that is, anyone in the field of improving transportation, are making the transition to leveraging mobility data, in addition to telematics, to optimize the way we get around.
Device data is our foundation
Device data is any data that a mobile phone or mobile device collects; this includes location data (where you are in a point of time) based on GPS sources. The importance of this data has only become more important over the last 10-15 years. When a device owner opts in to share device data, we have access to trillions of data points from apps on mobile devices. In fact, GPS data has been an integral part of the sharing economy services since the beginning, and it continues to serve an important role.
Here’s where the shift comes in. We’re not only looking at device data on its own. Now we have the ability and opportunity to layer it with other data points for additional context.
When you take telematics data like this and enrich it with context, we call this mobility data. Mobility data is providing an even deeper understanding of how people move.
Why shifting to mobility data works
When we layer contextual information, we’re not only looking at the location of a vehicle at different points in time, but we’re also receiving a moment-by-moment picture of how an individual is moving from point A to point B, because their phone is always with them.
Are they walking, riding a bike or scooter, taking a train, ship, or airplane? What are the trends on different days of the week, different times, or when the weather changes?
With this type of information, we are enhancing the experiences and solutions we are already creating and determining how to innovate to make more.
Device data + context = The mobility data advantage
Mobility data provides a more well-rounded view of driving behavior, whether that is the weather, traffic, terrain, time of day, or another changing element, so we have a better picture of risk.
With mobility data, we can:
- Gain insight into how customers move throughout their day – for instance, in order to better understand patterns of travel
- Detect changes in speed
- Use device data to understand the different kinds of phone use while driving (also known as distracted driving), including scrolling, tapping, locking and unlocking, and hands-free phone calls
- Uncover deeper insights, such as contextual speeding, which is understanding speed in relation to things like slick roads or decreased visibility, unexpected traffic, type of road, and whether it’s sunny or dusk or dark outside
- Detect whether the device holder is a driver or passenger and the type of transportation, such as walking, biking, driving, or even riding in a plane, ship, or train
- Understand second-by-second common routes from home to work, how long they spend in the car, how far they drive and drive time trends
All of these insights help open up new value-add opportunities and create new revenue streams, build more personal and profitable app experiences, and find new ways to engage.
For instance, we can provide more relevant feedback such as Fuel Efficiency information, help more quickly during an emergency with Crash Detection, and assist with budgeting. Let’s dive deeper into how mobility data adds value.
More connections mean more opportunity for growth and value
When we leverage the connection that’s already there, that is, the mobile device in hand, we open up a whole new realm of opportunities. So many types of apps are most valuable (or only valuable) when movement and location data is shared; of course, you first think navigation, but also it applies to weather, finance, fitness, travel, and dining.
And yet, app publishers are struggling to engage their consumers and drive revenue. Why is this?
We can see that new engagement declines 10-40% within 1-30 days after downloading an app. And the majority of someone’s time (83%, in fact) is spent within the top five apps on their smartphone. Even so, in-app advertising spend reached $77 billion in 2019, so we’re convinced of its potential. But how many of those dollars reached the right people at the right time?
With mobility data – which is ultimately another form of behavior data – we can be much more confident we’re spending our budget on the audience that fits our product and services the best.
Mobility data and more targeted advertising
When we analyze mobility data and translate it into real-world insights, marketers and advertisers can present highly targeted offers in the apps that our ideal audience already uses, based on their individual preferences and behaviors. That not only increases reach, but it also reduces advertising dollar waste.
Not only that, but more targeted advertising provides more value to the consumer. That’s because the ads feel native and relevant to the consumer. These offers are affiliated with their habits and desires.
Imagine how we could layer device and location information in a personal context to enhance the experience.
You may have already experienced apps that tell you that the road ahead may be slippery due to weather and/or a more efficient route has been found for you. This kind of location-based data is bound to become even more helpful over time, especially as it’s layered contextually.
Mobility data makes transportation smarter
Transportation companies are already leveraging mobility data. Auto insurance, sharing economy, city infrastructure and planning departments, advertising services, and mobile app developers are just a few of the industries that have started to adopt telematics, device data and mobility data analytics as an integral part of their research and development.
The sooner we all connect – with each other and with the data – the smarter, safer, and more effective and efficient transportation will be for all. Contact us to learn more.