Data Mining

Data mining personalizes direct mail

Big data is turbocharging the old-fashioned business of direct-mail marketing, giving dealers the ability to pinpoint prospective customers and tailor their appeals right down to the desired monthly payment.

It’s a departure from the days of “spraying and praying,” when dealers would use mailers to pitch sales events or cash giveaways to tens of thousands of addressees, but save the details for those who actually ventured into the showroom.

Today the aim is to prime customers with enough specific, useful information to get them to make that critical phone call or visit to the dealership. Modern mailers can, for example, include specific offers for a new-vehicle purchase or lease that would lower the recipient’s monthly payment. Dealers who want more late-model Honda Civics on their used-car lots can send buyback offers to owners of that car, or they can craft pitches specifically to customers with damaged credit.

That ability to speak to customers individually has helped direct mail stay relevant as marketing dollars increasingly shift toward digital media. And it’s one reason Craig Waikem is a big believer in it.

Waikem oversees a team of eight Internet sales managers who handle the e-commerce operations of his family’s seven-franchise dealership group in Massillon, Ohio. While his Internet team converts about 20 percent of the roughly 800 monthly new-car leads it gets into sales, the group still runs direct mailers at least once every other month.

“As long as consumers are still getting mail from the USPS, direct mail will be effective,” Waikem says.

A staple of Waikem’s direct-mail menu is an equity mailer that offers past customers the chance to get out of their current vehicle and into a new one. A vendor crunches customer data from the dealership’s computer system — including name, address, vehicle identification number, sale price, amount financed and other information — to identify customers with equity in their current vehicles.

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