How I Used Machine Learning To Price Used Cars

Andrew Carman is a software engineer at Shift.

At the core of any market is pricing. If you get pricing wrong, your marketplace doesn’t work. Our success at Shift—as a marketplace that makes it easy for anyone to buy and sell used cars—hinges on accurately and competitively pricing cars. 

Dealerships traditionally have a team of experts that price trade-ins for customers and manage the prices of their vehicles. They haggle over those prices with buyers that come to their dealerships, and often take advantage of consumers who have less access to car price data.

Our goal is to make selling and buying a car a fun, fair, and accessible experience by using technology to disintermediate what car dealerships do poorly. So we build software instead of back-office sales teams to price our cars, which increases efficiency, levels the playing field for our customers, and lets us systematically improve the accuracy of our pricing over time.

Read on to see exactly how we did it, and pass this along to the folks who might be interested in our approach.

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