Marketers must cut through a jungle of information to get to the river.
Who gets credit? Merrihew asks.
Some data is useful, some dubious and some nonsense. It’s tough to figure out which is which, say digital marketers trying to make practical sense of so-called big data.
Auto retailing relies on information, and lots of it, to decide how, when and where to pitch to consumers whose tracked online shopping activities show an interest in buying a vehicle. Search-engine marketers play tug-of-war for their attention.
“There’s the 99% rule,” says Lincoln Merrihew, vice president-transportation for market researcher Millward Brown Digital. “If online someone is looking for, say, a, 99% of companies are trying to steer that person in a different direction.”
The ability to track and aggregate consumer behavior has created a jungle of information. Marketers need to cut through it to get to the river.
“Data is coming out faster than ever before,” says Karl Brauer, Kelley Blue Book’s senior director-insights. “Control and manage it, but don’t let it overwhelm you.”
Boil down all that information into something that’s manageable and useful, advises Ernie Kelsey, American’s manager-regional marketing.
“We need to look at big data, but we’re using small data for regional marketing,” he says at a J.D. Power conference session called “Got Data? What Data Matters Most for Automotive Remarketers.”
A session theme is the need to derive “small insights” from big data, Merrihew says.
Consumers can travel all sorts of highways and byways in their online journey to a vehicle purchase. They may even take a U-turn or two.
The last click doesn’t necessarily deserve the most credit for the sale. An earlier banner ad or search-engine marketing effort may have had more to do with it. But it’s hard to sort that out, despite all of the talk about using metric measurements to gauge ad effectiveness.
“Who gets credit for the circuitous route to a brand?” Merrihew says. “The long and winding route to a click sale has various detours.” Maybe even some dead ends.
Still, automakers and dealers rely on metrics and grid-like tracking to provide some idea of whether their advertising is hitting the target or getting close.
“Manufacturers can’t afford to shoot from the hip,” Brauer says. “It makes no sense. If 80% of them shot from the hip before, that’s down to 20%.”
Measuring ad effectiveness is an imperfect science. “There has to be a better way of measuring brand lift, but I haven’t figured it out,” says Seamus McAteer, senior vice president-data and analytics for Millennial Media.
The industry’s reliance on data in the pursuit of customers can give people with certain job titles more say in planning marketing strategies, he says. “If it is between a marketing expert and a statistician, they’ll take the statistician’s word for it.”
But people with advanced degrees in statistical analysis can get too absorbed in data, says Chip Peterson, group director-analytics for the automotive marketing firm Team Detroit. “They want to play with it. They can get immersed in it. They’re not necessarily interested in making money.”
Merrihew advises: “Don’t let Ph.Ds swim around more than 20%.”
“Big data” is an overused term, especially if someone is manipulating it to further their cause, McAteer says.
“I know BS when I smell it,” he says. “When people start using buzzwords, I want to see the data. You’ve got to understand the input in order to understand the results.”
Data, especially on a massive basis, can contain imperfections. Clients, marketers and others should allow for margins of error, says Peterson. “Too often in digital, I’ve seen good sources discredited. Don’t discard good data even though it might not be 100% perfect.”