How Data Analytics Can Help Improve Used Car Operations

July 13, 2018

The term “artificial intelligence” or “AI” may conjure up sci-fi images of robots and futuristic machines. But many businesses today are using AI to obtain more accurate data and help owners and managers make better decisions.

This includes auto dealerships, where AI and data analytics are driving new types of innovation, especially in used car inventory management. By using data analytics tools, dealerships are better able to manage their used car inventory and maximize selling prices. And this, dealers are pleased to know, may result in faster inventory turnover and higher profits.

Reducing uncertainty

One of the biggest challenges dealerships face when selling used cars is uncertainty — for example, not knowing how long it will take for cars to sell or how much they’ll eventually sell for. According to a vehicle inventory intelligence company, half of the used vehicles on dealers’ lots sell either too quickly or too slowly.

Both scenarios can lead to reduced profits. Vehicles that sell too quickly may have been underpriced. And those that sell too slowly were either overpriced or not a good match for the marketplace. Better information and more certainty will help improve your game.

Getting the price right

A wide range of factors go into how dealerships price used vehicles. These include the car’s condition, features, age, mileage, make and model. Dealers consider these components, along with book values and local sales trends, as they strive to set the right price for each used vehicle on the lot.

Market supply and demand is another critical factor in pricing used cars. But this kind of data tends to be more subjective and changes over time, making it harder to gauge. And the longer a vehicle sits on the lot, the more volatile supply and demand for that specific car will be.

Data analytics can help you manage these uncertainties by combining objective data such as a car’s make, mileage and features with current market information. Using this data, the software can predict not only how much the car will sell for, but also how long it will take to sell. Typically, data analytics software will constantly monitor changes in local supply and demand and alert you when action should be taken.

For example, if the local demand for a certain vehicle is on the rise and the supply is low, the software will recommend that you hold firm on the price because the vehicle will likely sell soon. Conversely, if demand is waning and supply is high, it’ll recommend that you lower the price, change your promotional strategy or wholesale the vehicle sooner.

Analyzing online shoppers’ behavior

Data analytics tools also can shed valuable insights on used car shoppers visiting your website. For example, the software can analyze the behavior of online shoppers to determine how long they’ve been looking at specific vehicle makes and models.

Consider two different online used car shoppers: One spends 10 seconds looking at a certain used car online, while the other spends 10 minutes looking at several different cars of the same make and model. The second shopper is probably a serious buyer for that particular car while the first shopper most likely isn’t.

While the software doesn’t identify who the individual shoppers are, it does let the dealer know it might have a serious buyer for the car. Based on this knowledge, the dealer can make more informed decisions about the vehicle’s final selling price.

More data = better results

Remember that, when it comes to AI and data analytics, the more data you enter into the software, the better results you’ll get. The software gets “smarter” as it receives more information.

Now would be a good time to meet with your used car manager and salespeople to discuss whether data analytics tools could help upgrade your used car operations.

Data analytics and VIN numbers

Most dealerships rely on VIN decoders to gather detailed information about used cars they might purchase for inventory. But VIN decoders are incomplete. They may only reveal 60%–70% of a vehicle’s actual features, according to a vehicle inventory intelligence company.

Also, up to 25% of used car listings reportedly have a significant error. Common errors include missing features such as alloy wheels, navigation and keyless entry, which add value to the used vehicle.

Data analytics software can help you get a more detailed picture of a used vehicle before you buy it and place it on your lot. The software collects data from millions of used cars sold in recent years to identify features specific to certain vehicles. Using this, it provides a complete and accurate picture of each used vehicle’s features.

With more complete data about features, your dealership can appraise used vehicles with increased accuracy. And this can help you realistically maximize your asking price.

© 2018