You know what unifies almost everyone? We all hate having to go buy a car. Unless you have so much money it doesn’t matter how much you spend, the whole thing is incredibly nerve-wracking and annoying. Sure, you can do your research on what kind of car you want and where to find it online these days, so it’s a lot easier than it was twenty years ago. Yet, at the end of the day, you’re still going to the dealership to walk around the car, check it over, and then haggle with the salesperson, trying to skim a few thousand off the price or get an extra or two thrown in. You never know for sure if he’s being honest with you on the condition of the car or how much they can afford to cut the price.
Those last points in particular demonstrate that the typical car buying experience is anything but transparent. What if it was though? What if there was a simple price that you knew was the price it was actually going to be sold at, there wasn’t any haggling to do, no salesperson, and strong guarantees on the quality of the vehicle? What if you could do it all online and have the vehicle delivered right to your driveway? In short, what if buying a car was like buying something on Amazon?
That is the experience that Carvana set out to create. Using data the right way they managed to create a user experience that allows for buying a vehicle in as little as ten minutes while actually increasing their profits. They were already doing well before COVID hit, but as soon as it did, Carvana really took off with their stock price going from $29 to $280. How did they manage to do this?
One of the big things they did was create an online shopping experience that works for everyone. By foregoing the car lot, they avoid a lot of overhead as well as having salespeople. Not having salespeople does more than just save money by having one less person to pay. It takes the subjectivity out of the equation. Other than the obvious temptation on the part of the salesperson to oversell a vehicle or steer someone to a more expensive vehicle for the larger commission, there are personality issues. If the salesperson and the buyer have incompatible personalities, there is a high likelihood that the sale doesn’t happen, even if the car is actually exactly what the buyer wants. Carvana does away with that subjectivity and keeps the focus on helping the buyer find the car that will best suit his needs.
When asked about how they use data so well, the CEO had a great, TARTLEesque answer. He said it wasn’t really about having an AI and machine learning, it was about getting the right data and doing the right things with it. That is exactly what we’ve been saying, it isn’t about the quantity of the data but the quality of it and being able to use it effectively.
It isn’t that they don’t make use of AI and machine learning, it’s that they use them very intentionally. For example, they have programs that monitor used car auctions, looking for cars that are in demand in certain areas and waiting for them to get to the right price so they can turn a profit. When that happens, Carvana gets a notification from its AI and purchases the vehicle. Then any needed restoration work is done and it is put up online and if needed, shipped to the region where it is most likely to sell.
Carvana uses their algorithms and data so effectively because they understand that they are more than a car company. They grasp that they are really a tech and data company before they are a car company. That, plus the desire to help get people in the car that they want to be in, makes Carvana one of the best and most interesting companies in the digital age.
If they can use data to revolutionize something as mundane as selling a car, imagine what can be done by millions of people all sharing their own data through TARTLE.
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