All data is not created equal, and no one knows it better than Scott McKinley, founder and Chief Executive Officer of Truthset, a data intelligence company that evaluates the validity of consumer data.
In Infutor’s latest episode of Identity Revolution, host Cory Davis chats with McKinley about the challenges presented by inaccurate data and how understanding the degrees of accuracy in your data can lead to better outcomes, something he experienced while serving as Executive Vice President at Nielsen.
McKinley also talks about the importance of accuracy over scale. He also discusses how the digital revolution created an influx of availability of data and an opportunity for arbiters of accuracy, like Truthset, to contribute to data monetization in a meaningful way.
Scott’s Focus on Integrity Began as an Olympic Athlete
“The reason I quit cycling is that there was some influx of really potent drugs that came out of the Eastern bloc countries when the wall came down…To me, that’s lying. That was bulls*it. It undermined the beauty of sports.
And so, fast forward, I don’t think it’s any surprise for someone wired like me to operate with integrity and to try to win legitimately. To find myself in a position where I’m trying to help everybody who uses data understand what’s real and what’s not. Whether it’s an inadvertent emphasis on scale versus accuracy or whether it’s outright bad players in the ecosystem. I thought it’s kind of a nice tie back to finding truth and things.”
The Value of Independent Measurement
“I learned a couple of things [at Nielsen] that definitely led to the creation of Truthset. One was the value of independent measurement, the value of someone that sits between buyers and sellers and helps both sides understand the actual value of the asset being traded.
In the case of Nielsen, it’s how big the audience on television is? Nobody knew. And so you had a lot of claims of BS in the system. I think when Nielsen stood up a measurement system for linear television, it cleared up the market. It removed a lot of friction between buyers and sellers and allowed everyone to agree on the value of the asset being traded. In that case, it’s audiences on television.
[…]
I figured if Nielsen figured out how to make $2 billion a year being the arbiter of truth for how big an audience is on linear television, why isn’t there someone being the arbiter of truth for the new fuel that runs the economy, which is data?”
Data in the 1990s Was All About Scale
“Since the mid-90s, when data became just so broadly available and everyone’s sort of figuring out, ‘Wow, there’s so much data available about people and how they move on the internet, where they go, what they buy, who they might be,’ all this behavior information was generated from our behaviors.
And it was extremely powerful. It allowed marketers to really hone in on the audience. It allowed people doing their own customer analytics to be much more precise and accurate about how their customers are, how they buy, why they buy, and what sort of messages they respond to.”
Accuracy Beats Scale
“We bought some companies at Nielsen… I remember doing due diligence for a category of a company called a DMP (data management platform), where the head of data science bragged he could deliver something like eight million soccer moms in Kansas City.
This is an impossibly large number. The census would tell you there’s probably a hundred thousand moms in Kansas City, and there aren’t 8 million, and he said, ‘It doesn’t matter. I can mathematically back it up.’ I’m like, ‘Okay, this is a problem.”‘
Quality of Data Matters, Especially in Marketing
“There are providers who think, ‘What’s the difference? You’ve got providers A, B, C, and D. It’s all pretty much the same. They must source.’ It’s not true at all. There’s incredible variability.
For Hispanic segments, I’ve seen data providers come up with literally 15% or 20% accuracy in a pool of IDs that they are swearing up and down and sideways are Hispanic, while others are 80% accurate. And that’s a huge difference when you talk about if you’re Tecate and you’re marketing to Hispanics. You don’t want to throw 70% of your money on the floor, delivering ads to people who are not Hispanic.
We’ve brought accuracy into the equation. It’s not just price and scale. And we’re learning from our customers that it really does matter. It changes the outcomes of any operation that’s driven by data, particularly marketing.”
[7:42] “There’s no absolute truth.”
[17:54] “Our mission is to not only measure the quality and the accuracy of the world’s data but to turn around and use it so that participants can get better and more precise [data] with a layer of privacy and compliance on top of that.”
[21:51] “I think the last big, substantial gain in efficiency was probably viewability when everyone realized, holy smokes, half my ads aren’t viewable. I think [accuracy] could be the next biggest gain [in data], certainly the biggest gain in efficiency since viewability.”
[22:12] “Let’s say we can improve efficiency by 30%. We’re in a world where marginal gains are all you get. So to improve efficiency by 20% or 30% or 40%, that’s huge.”
