Paying for parking, toll roads and EV charging can be a chore for drivers, but in-car payment functionality is now available in a greater proportion of cars than ever before, streamlining the process. However, this relies on vehicles having very precise location data. If data is inaccurate or out of date, drivers could find themselves struggling to pay, or even worse, paying for a service in a nearby location, potentially resulting in them receiving a citation, for instance, despite having been charged to park.
In-car payments now let drivers pay for parking, tolls, EV charging and more straight from the infotainment screen, no card, no app. It only works if the car actually knows where it is.
The catch is data quality. Get the location or restrictions wrong, and the payment either fails outright or goes through for the wrong thing entirely.
The hidden cost of compromising on data quality
To bring connected features to market, some car manufacturers cut corners on the quality of the data they use for their parking and charging functionality. While relying on cheaper or less regularly verified data sets might seem like an easy way to reduce overheads, that’s precisely where accuracy breaks down.
In-car transactions rely on hyper-accurate location pinpointing. The vehicle needs to know exactly where it is to communicate with the correct payment terminal or service provider. When location details are murky, systems struggle to recognise which service the driver is actually trying to pay for, resulting in failed transactions, error messages and a poor user experience.
To illustrate the complexity of this, consider many busy urban environments where there are numerous car parks and EV chargers in close proximity, along with countless shops, take-aways and other services that may accept in-car payment. Not only is it difficult for drivers to discern which service they need to pay for in this environment, but things get even more complex in the future with the use of AI agents, which may make their own independent decisions about payments.
The 'next car park over' data dilemma
Imagine a driver pulling into a busy city centre car park ahead of an important meeting. They park and their car flags that in-car payment is available. However, when they try to pay, the car can’t determine which car park the vehicle is located in due to inaccurate data. This prevents the driver from paying or, worse still, submits payment for parking in the next car park over.
In these circumstances, poor data quality prevents drivers from using a service that they know is available and should save them time. Instead, the car causes additional stress by forcing them to find another mode of payment and gives them a poor impression of the OEM. Run that same scenario again, but with high-quality, verified data however, and the driver has a fully seamless experience, pulling into a space and clicking on their infotainment screen to activate in-car payment. Not only does this minimise stress, it also saves drivers time and gives them a positive view of their vehicle OEM, as it has simplified the end-to-end journey.
Retaining customers is increasingly difficult for automakers in a highly competitive market, and drivers who have a positive view of the brand are more likely to pay a premium for features next time around. Trust from today’s drivers, once lost over something as preventable as poor in-car payment integrations, is hard to win back.
Why high-quality, verified data is non-negotiable
For in-car payment features to transition from a novelty to a trusted daily utility that takes stress out of drivers’ lives, precision is paramount. Car manufacturers must prioritise the integration of high-quality, regularly verified data.
Driving true value for motorists
In-car payments are only as good as the data behind them. Get the location data right and the feature disappears into the background, which is the whole point of Invisible Utility. Get it wrong, and you've built a feature that fines your own customers on your behalf. Nearly two-thirds of European drivers say they will switch brands when purchasing their next car, according to BCG, while brand loyalty dropped from 51% to 49% in the latest J.D. Power U.S Automotive Brand Loyalty Study with Honda loyalty falling 3.3 percentage points from 2024 to 2025, Lexus premium SUV loyalty dropping by 2.8 percentage points and Subaru SUV loyalty down 2.0 percentage points.
Whether a driver switches OEMs next time round increasingly comes down to details exactly like this. The OEMs still treating parking and charging data as an afterthought are the ones about to find out the hard way.