Physical Address
304 North Cardinal St.
Dorchester Center, MA 02124
Physical Address
304 North Cardinal St.
Dorchester Center, MA 02124
Scott McKinley’s Journey from professional cyclist and captain of the 1988 US Olympic road cycling team in Seoul, Korea to CEO and founder of the company data validation provider Truthset was more linear than one might think.
Cycling is “the ultimate test of truth,” says McKinley on this week’s episode of AdExchanger Talks. “You run 120, 130 miles and the first one to get to the other side of the line is the winner. It’s very clean, it’s very responsible, it’s very individual.”
But as doping in cycling became more widespread in the 1990s, McKinley took that as a cue to stop.
“The crooks came in and the drugs came in and I wanted no part of it,” he says.
After retiring in the late 1990s, he worked as a web manager for Cox-owned television stations, then co-founded and ran several measurement software and analytics companies, and later joined Nielsen as EVP of Product Innovation.
But at that point, about 18 years into his career, something became crystal clear to him: Digital advertising has a serious data quality problem.
“And I basically decided that I was either going to leave the industry because I was so tired of the snake oil salesmen and the fog and the BS,” he says, “or I was going to create a company that tried to clean up a little bit of the mess and give everybody a better chance of using the data to predict who might be on the other end of the device.”
In 2019, McKinley founded Truthset, a startup that verifies the accuracy and quality of datasets.
According to Truthset’s analysis of public data markets, the average accuracy of age data is 32%, meaning that most age-related data is incorrect. Meanwhile, the average accuracy of gender data in publicly available segments is 61%, which is only slightly better than a coin toss.
So why are advertisers still buying this data?
One reason is “the advertising industry’s addiction to scale” at the expense of accuracy, McKinley says.
But there’s also a lot of “pretending” going on in the supply chain, he says, “what we like to call probabilistic modeling.”
“It’s basically a euphemism for pure guesswork, right, with an incentive to maximize range at all costs,” says McKinley. “Once you have those two variables, how can you trust what comes out the other end?”
Also in this episode: What happens when marketers use inaccurate data, McKinley’s raw opinion Bridging ID (he’s, uh, not a fan) and why cycling wasn’t the best way to get girls into high school.
For more articles with Scott McKinley click here.