I recently had the pleasure of presenting at Monetizing The Digital Car Virtual ‘Live’ 2021 – a global event bringing together automotive OEMs, big data tech companies, mobility service providers and other stakeholders at the forefront of unlocking the full potential of monetized car data. The event fostered discussion around how increasingly connected cars, and the volumes of data they are producing, is poised to generate valuable revenue opportunities that extend beyond OEMs to nearly every industry today. In case you missed it, here’s a few key takeaways from my session:
#1: For in-car commerce to soar, we must change how think about data.
The concept of using the car as a payment platform is not novel. Lofty promises of in-car commerce have been around for nearly a decade. Why then are those payment experiences not the norm today? It all comes down to the data and how it’s being applied. While studies have shown there is tons of data being generated from the connected car, that information is not being organized in a way that easily solves problems for drivers when it comes to commerce. The industry has historically focused on collecting data from the car, aggregating it and then looking for use cases. For in-car commerce to grow in adoption, that approach needs to be reversed. We must first understand where drivers have needs related to commerce and then find the data that can solve for them.
#2: Creating compelling use cases means meeting drivers where they are.
The key to advancing in-car commerce is to build on what drivers and passengers are already doing in the car and to make those experiences more intuitive, convenient, and enjoyable. For in-car payment use cases to be compelling, they need to solve for problems a driver already has and be relevant to their journey. Take parking, for example. A driver using their car’s navigation to a specific destination may want to understand what the parking options are when they arrive. Providing the ability to securely reserve and pay for parking through the car by voice commands is a great use case, because it intuitively and seamlessly solves for something the driver is likely to need within the context of their broader experience. You can then build on that experience, offering covered parking options if it’s raining or suggesting making a reservation at a nearby restaurant.
#3: In-car commerce requires integration of data sources – onboard and in the cloud.
While understanding use cases is critical, delivering those experiences requires us to think more broadly about connected car data. We need to bring the data from the car into the cloud, aggregate it with content and service partners, and then bring it back to the car with voice to seamlessly solve the driver’s problem. Consider the parking example again. Deep integration with the car’s sensors could identify a driver gazing at a spot on the street and asking, “can I park here?” For the car to provide a useful response to that question, the information from the car must be processed in the cloud with third-party information, including perhaps a 3D model of the environment, live data on available parking, and pricing based on day of the week and time of day. If it’s a spot that requires a meter fee, then it must integrate with a payment system and be able to securely initiate a transaction.
Contactless, in-car payment experience through voice-powered AI
Today, solutions and data in the car are fragmented, resulting in a clumsy experience with multiple passwords and access points that is hindering the advancement of in-car commerce. That’s why we built Cerence Pay. It can orchestrate applications to deliver in-car experiences that solve problems for drivers and open revenue opportunities for OEMs and other businesses. Cerence Pay connects third-party applications through OEM user management, reducing the siloed data problem that is frustrating drivers while acting as the foundation to in-car payment use cases.