While the idea of a one-size, fits-all approach sounds nice, it seldom works. We want our coffee made to order with specific measurements, clothing tailored for our unique body type and personalized messages and interactions from every company we purchase from. To put it simply, we want customizable solutions and experiences that give us value—and that translates to the automotive industry, too.
At my company, KAR Auction Services, we provide sellers and buyers across the global used vehicle industry with innovative, technology-driven remarketing solutions. We know that each customer is unique—and value can take on many different meanings. But as new data and technology are transforming the industry at a rapid pace, we’re at the forefront of translating this data to create actionable insights for our customers, and provide the customized solutions that they need to optimize the value of their vehicle portfolio—however they define value—and succeed. A great example of this is our recently launched data-driven solution, Pricing Insights.
Pricing Insights is the newest addition to KAR’s suite of data science capabilities, which helps automotive OEMs, captive finance customers, and other consignors optimize the price of their vehicles down to the individual VIN level to get the highest economic value. In other words, our proprietary data science and analytics algorithms produce accurate predictive models that tell customers the exact channel and price to sell each vehicle type to get the specific results they’re looking for—no guesswork involved.
But like the analogy above, we can’t give each customer the same blanket results, as their strategic objectives and remarketing priorities are each unique. By customizing the solution for each consignor and its brands, we have achieved a $170 per-unit net economic gain overall — creating more than $86 million in annualized value for our customers.
To better illustrate how Pricing Insights works, here are three quick examples of how that data can be tapped to yield customized outcomes adapted to specific value definitions and targets.
Strategy 1: Utilize the upstream online platform as a premium marketplace experience. For some customers, a strategic priority is to provide a “white glove” experience for their online buyers coupled with premium inventory. This strategy maximizes proceeds.
Strategy 2: Maximize the number of vehicles sold upstream on all digital channels. Unlike Strategy 1, this strategy targets increasing the volume of its vehicles sold through digital channels — whether through private label sites to other like-franchise dealerships, or other upstream channels to all participating franchised and independent dealers. This strategy optimizes on upstream conversion.
Strategy 3: Increase the net economics per vehicle. This strategy provides a heightened focus on pricing cars more accurately within each channel, helping to optimize channel mix and increase the per-unit gain. This strategy optimizes on price and proceeds.
As the strategies outlined above illustrate, there’s no right or wrong strategy; value means different things to different customers. So, by first determining what value truly means for each customer, we’re able to adjust Pricing Insights to serve their unique needs. No matter how you define value—and no matter how your definition changes over time—you can use data to get you more. So, say so long to the days of force-fitting off-the-shelf solutions—and say hello to data-driven customization.