Connected cars are creating thousands of data attribute types that provide insights into driver behavior and vehicle health. Consumption and analysis of this data gives app and service providers from existing and emerging markets the ability to provide new services to consumers or to significantly improve existing ones.
The opportunities for these new driver services are endless, but not all markets have the same degree of maturity when it comes to understanding how to use automotive data, or any data for that matter, to materialize them. For example, the mapping and navigation market is very proficient in implementing data from multiple sources to create a clear and usable picture for drivers. It seems only natural to incorporate car data in there as well.
The same applies to the insurance industry. Insurance companies already know how to gather driver behavior data. They are analyzing car data from dongles and telematics devices to construct usage-based insurance (UBI) programs like Pay As You Drive (PAYD) or Pay How You Drive (PHYD). Data derived directly from the vehicle can provide similar insights and more, so the next logical step is to add these attributes into their models as well.
On the contrary, emerging markets like electric vehicles (EVs) management, subscription-based fueling, in-vehicle delivery and parking applications are still in their initial steps when utilizing data. This is partially because these markets are still emerging themselves. However, since “data is the new oil”, we can safely assume that they too will advance to using data, and specifically car data, as they develop.
Here at Otonomo, we’ve been researching the automotive ecosystem for quite a while. Using our experience, we created a mapping of the potential industries that can grow as the utilization of vehicle data grows in the automotive ecosystem. The graph, dubbed the “Otonomo OtoGraph”, shows the layout of these different industries according to their market maturity in terms of data utilization.
The market maturity of these use cases is shown in the Y axis of the graph:
The X axis presents the estimated value per vehicle in each of these markets, regardless of their maturity degree. For example, the aforementioned insurance use case has a higher value delivery potential per car compared to the mapping use case, even though they are both mature markets.
In most cases, the value difference has to do with the type of data each use case utilizes. Insurance companies manipulate driver-specific data, enabling them to provide personalized services. Whereas mapping companies use aggregate data, based on anonymized car data attributes, which offers more general services to the public. It’s probable that data from one vehicle that provides tailored services to that specific vehicle generates more value to the vehicle’s driver (and is more profitable as a result), than the value (and in turn, revenue) per vehicle than vehicle data that is gathered from multiple vehicles generates.
But, this does not mean the use case is less worthwhile as a whole. Use cases that are more valuable per vehicle also require driver consent to share data, which could be harder to obtain. In addition, the cost of acquiring subscribers is likely higher. Consequently, services that are based on aggregating data from thousands of vehicles might be more profitable as a whole.
In fact, when inspecting different use cases and their utilization potential, OEMs should take all available data they have into account. The total value of their data depends on use case maturity, data attribute types, the amount of data being sent from the OEM’s vehicles, timeliness of data delivery, and any future availability of additional parameters.
At an ecosystem level, we see more connected cars and therefore more vehicle data coming online each day. As a result, we predict that all these use cases will move to the right on the OtoGraph, meaning that they will become more seasoned in utilizing car data to provide driver services. Data is expected to be the main generator of service creation, service shaping, and service optimization.
Part of this process requires educating the market about all the possibilities, since many of these opportunities are still in the early stages. OEMs can advance this process by licensing their vehicle data to companies like Otonomo, where we ingest, harmonize, aggregate, and normalize it to make it useful and valuable to providers of such use cases as displayed on the OtoGraph. In turn, this data is used to develop apps and services which benefit drivers, enhance the driving experience, and increase OEM loyalty and CLV.
Contact us to learn how your car data can be used to create value for drivers and for the car manufacturers who create it.