There’s a basic issue prevalent across the motor industry, and it’s called a disconnected buying experience for the customer. There are myriad reasons for this, some of which boil down to legacy systems, boundaries between companies, or a lack of competition and industry challengers. Yet, on the near horizon are a few successful models that are beginning to show us how things can be improved for the customer, and how artificial intelligence (AI) will play a part in the digital transformation of the customer’s journey.
Let’s say you want to buy a car: your first port of call may be the ever popular Auto Trader, where you do your research on the vehicles you want and you look through an inventory system of used cars, for example. You create a shortlist of three cars you want to know more about and would like to see what finance deals are available for them. Unfortunately, the inventory system where you found out about the cars isn’t connected to the motor finance system. You need to work it through one car at a time.
When you move on to applying for a car loan, you’re faced with a loan application that asks for your personal details without reference to your shortlisted cars. The fact is that many of these personal details already exist in your Auto Trader profile, but they’re not connected. You may also want to shop across multiple finance companies to get the best rate, but you find yourself doing all of the legwork and putting the package together with paper and pencil. You have to find the car, get the best deal on that car, find a good loan rate and also the best insurance. Each of these stages of the car-buying process is disconnected, and assumes knowledge on the part of the customer. It’s ridiculous.
These stages should all be connected in a unified customer journey, from production to sales and beyond. So far, the provision of a connected process to make the customer journey smooth for the car buyer has been slow to materialise, particularly in the UK. There has been some improvement recently: at least the inventory data is making its way across the divide for one car, even if your own name hasn’t yet made the grade. But there are a few visionary startups that show how it could be done, and they’re mostly in the US. Let’s take Carvana as an interesting example.
Carvana and Tesla customer journeys
With Carvana, you have the unified buying process that goes beyond servicing (which it includes), to fulfilment, and acts much like Amazon (in fact, Amazon is doing this too). You buy the vehicle and it appears on your driveway in a couple of days. The whole buying process is online, they deliver it to your doorstep, and if you don’t like the car, you can return it within seven days. And if you haven’t checked out the Carvana vending machine yet, take a look at this video:
Let’s look at Tesla as an example of how smooth the customer journey can be within a complete ecosystem. Not only does Tesla produce high-quality vehicles, it also created a network of branded recharging stations, an app for customising and purchasing your Tesla model, and a story that includes addressing the issue of climate change and sustainable energy that makes you feel like you’re contributing to improving the health of the planet. Go online and order your new £88,000 Model S in under five minutes. This is about customer experience.
The experience exemplifies a company that sees beyond the car, to the relationship the company wants to have with you as their customer. The success of Tesla isn’t only about engineering – it’s the entire package, including in large part how you purchase your vehicle, finance it and maintain it. The motor finance industry can learn a thing or two from the Tesla customer journey when it comes to encouraging brand loyalty, too.
How will AI help with the motor finance process?
Where AI could play its part is in transforming the buying process, so that the connected facets of the buying process revolve around the customer. Why not begin where the customer wants to begin? For some customers, this may be pre-approval for what the customer can afford, not the inventory available. Some customers may like to go through an online conversation about what they’re looking for, and who they are, before being presented with vehicles that other people with similar profiles rate highly. This type of matching process is where AI can be applied across the chain, helping people find their next car.
Why have things been slow to develop?
There’s an entrenched way of selling cars to customers, and regulation isn’t mandating change to force it to adapt to new methods (unlike open banking regulation). Regulation is breaking up the monopolies on the high street in banking, looking very carefully at how the high street banks are treating their customers; consumers feel they are getting a better deal from the likes of Starling or Monzo. It’s different in motor finance, yet change is on the near-term horizon. In the US, entrepreneurs have more access to an online market, with new business models well funded by venture capital.
As the current models of vehicle motor finance change and adapt to digital processes and modern thinking, artificial intelligence can help. It can provide the competitive edge needed to make major improvements to the customers’ experience. At the sharp end of motor finance, change is how we use AI to create a unified buying journey – one that’s more competitive against new entrants that are slowly but surely beginning to emerge.