Dealer Tire gains traction with data science

Dealer Tire is predicting when tires and other automotive parts will need replacing, an approach it says will help dealership and manufacturer partners generate more revenue.

Dealer Tire gains traction with data science
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In 2016, Dealer Tire executives posed a salient question to the 100-year-old company's fledgling data science team: Can we predict when each consumer will need tires? The answer — critical for a company that must get to customers before they buy tires somewhere else — was a resounding yes.

"It was the first ‘a-ha’ moment," Chris Schron, Dealer Tire's director of data science, tells CIO.com. "We realized if we could build some predictive models to answer that question, it could really add value."

That has paved the way for Dealer Tire, a distributor of tires and other automotive parts, to leverage analytics to create new data products and consulting services it could sell to its dealerships and auto-manufacturer partners. The value-added distributor is betting that big data will yield big money.

Strategies that leverage troves of transactional and other data to boost revenues abound. To fulfill these big data goals, companies are investing in analytics projects, whose core tools include software that can clean up, organize and model data for cultivating business insights. Worldwide revenues for big data and business analytics software will reach $260 billion in 2022 with a compound annual growth rate of 12 percent from 2017 to 2022, according to market research from IDC.

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