The auto business seems simple: come to a dealer, choose a car, fill out the paperwork, and leave in your new car. However, car buying and selling is a complex process requiring qualified personnel, careful market analysis, and modern technologies.
AI has changed the automotive industry from industrial robots in manufacturing plants to driverless vehicles. That is why Tesla, Mercedes-Benz, Volkswagen, Toyota, Volvo, and many other major automakers are implementing AI technologies to improve customer service. At the same time, the proliferation and availability of AI techs permit all market players to ameliorate their processes. Indy Auto Man, a local Indiana dealer, shares their experience in technology implementation and explains what else dealerships can do with AI in their work.
Sales tactics
Choosing the most advantageous strategy for selling a car is a cornerstone for business success. How does a dealer find an ideal balance so that the vehicle does not end up in a toxic drain and the dealer gets the maximum possible profit in the current market situation? Here comes the smart dynamic pricing. If buyers observe the Indy Auto Man inventory of used cars for sale a couple of times a week, they will see the price fluctuations. This is a smart tool that analyzes hundreds of parameters related to the current market situation, the dealer’s own sales experience, and the sales tactics of competitors in just seconds. It also takes into account the individual characteristics of the vehicle. The smart system can work autonomously and regularly revaluate cars without the participation of employees.
Tools for car valuation
Now let’s consider a situation where a buyer wants to find a dealer who will offer the best terms for buying a new or used vehicle under a trade-in program, in which they hand over their old car in exchange for a new or used one of a higher class, with an additional payment.
For a successful transaction, the valuation of the current car should be suitable for both the buyer and the car dealership. AI can predict the real car value on the market. The neural network considers the make, model, year of manufacture, mileage, generation, modification, and color of the car, as well as the number of owners, local market fluctuations, and numerous other parameters. It is essential to note that the neural network continually learns based on extensive data from all classifieds, as well as the history of car sales for a particular dealer.
Despite high credit rates, dealers need to assess a car’s creditworthiness. This parameter allows you to determine whether there is demand for buying a vehicle handed over in trade-in.
A neural network can also assess the credit potential. It takes into account all the characteristics of the car and builds a forecast based on data from bank brokers, information on collateral from reports, and data on the dealership’s financing deals.
If the dealer understands that it will be hard to make money when reselling the car, but it has a high credit potential, the specialist can still decide to buy it at an attractive price since there is confidence that in the future, they will be able to sell it.
Predictive maintenance
As AI leverages the capabilities of IoT in automobiles, it also helps certified dealers in predictive maintenance. IoT systems monitor the health of cars in real time by analyzing a huge amount of vehicle data. With this information, managers can determine when maintenance is required. Once an IoT sensor suspects a potential problem, it alerts auto company managers to take preventive measures before a malfunction arises. Moreover, AI also helps optimize fuel efficiency, reduce emissions, and improve the overall vehicle performance.
Modern tools for a successful business
All these solutions are necessary to build a successful car business in modern realities. Now, it has long outgrown the traditional buy-and-sell scheme, competition is growing, and the market has seen serious challenges.
Under such conditions, it is essential to enhance buyer trust and prioritize customer service. This is possible only with qualified personnel able to efficiently respond to requests and smart tools to build effective business processes.
