Lucid Creates Data Quality Measurement Model

Lucid researchers and scientists have created a data measurement model that the company’s Senior Vice President Ted McConnell and President Brett Schnittlich believe will change how marketers think about and rate the quality of data.

The model analyzes “attribute density” in a new way to identify the type of consumers the campaign reaches, and then measure the return on investment on those people who buy a product or service. “There’s probably a million data segments, so we cannot measure them all overnight,” McConnell said. “But we think that if data’s the problem, data quality is the next frontier of marketing.”

Data Score, the platform’s working name, begins with insight, intent and opinion data collected from people who have opted in and got paid to share their opinion, so the data model seems sheltered from any privacy legislation that might come down the pike, globally, such as GDPR and the California Privacy Act.



Lucid rolled out the measurement with a few unnamed advertisers in limited beta. The next step will be building out a platform that will enable the company to create “many hundreds of segments daily,” McConnell said.

Marketers get started with measuring their company’s first-party data. He said marketers think their first-party data is “rich” with people who have bought or have an intent to make a purchase in the category in which they sell products, but that’s not always true. And another way, he said, is to “fire a pixel in a campaign.” The data will tell the brand which audience to buy.

Lucid has measured several segments for a very large unnamed advertiser and several for agencies. The company also tested about 40 segments on its own to understand how the way questions are phrased influences the reliability of the measure.

Overall, tests were done on about 100 segments such as flat-screen TVs. One interesting findings centers on intent and the amount of money people are willing to spend on a product or service. For those with less money to spend on flat-screen TVs, for example, the intention lasts much longer. Those with more money, for the most part, might search for a better price, but the whole process might take 10 minute, whereas those with less money the buying process could last days or months, he said.

“Today we take a behavior and infer from that [the consumer] wants to buy a flat screen TV, which is the first problem,” he said. “By comparing the density of the segment you get all types of insights not previously available to the industry.”

McConnell thinks marketers can use this type of metric to improve the quality of the data. It becomes a key performance indicator (KPI). Data segments take about a week or two to quantify the quality.

It’s not clear how Lucid will price the segments, but the company believes that Attribute Density should act as a currency.  

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