Data Quality Co-op Launches Data Trust Score™ to Benchmark Market Research Respondent Quality

New market research industry metric turns fragmented quality signals into one actionable score for sample buying, routing and supplier decisions

SALT LAKE CITY, Jan. 21, 2026 /PRNewswire/ -- Data Quality Co-op (DQC) today announced the launch of its Data Trust Score^™. Based on observed behavior across the data ecosystem, the Data Trust Score communicates the trustworthiness of each individual's data in a single metric.

"For decades, the industry has treated data quality as a series of disconnected checks rather than a shared system," said Simon Chadwick, managing partner at Cambiar Consulting. "What Data Quality Co-op is doing with the Data Trust Score is establishing a common framework that helps the market both manage quality operationally and communicate it credibly to decision-makers. That shift is essential if research is to retain trust, relevance and influence in an environment where data integrity is under growing pressure."

Built on DQC's shared quality infrastructure, the Data Trust Score combines fraud signals, in-survey behavior and participation history across the data ecosystem. Similar to a FICO score, it brings many quality signals together into a single, easy-to-understand metric. This allows teams to quickly assess respondent trustworthiness and reduce the risk poor-quality data poses to their insights, decisions and business outcomes by using benchmarks grounded in data from real, engaged people. Scores range from 0 to 1,000, with higher scores indicating more trusted data.

"Market research teams are facing a 'superfakes' problem," said Bob Fawson, CEO of Data Quality Co-op. "It has become very hard to tell the difference between synthetic and human respondents, and between thoughtful people and disengaged survey takers. The Data Trust Score gives the industry a common, transparent way to quantify trust in the data that underpins business decisions and drives hundreds of millions of dollars in investment decisions every year."

The score is calculated using three primary inputs:

• Technical fraud indicators, including whether a respondent's device has been flagged as fraudulent.
  
  
• In-survey behavior, including suspicious actions such as illogical survey responses, task speeding or unsatisfactory open-end text responses.
  
  
• Survey participation history, including frequency, outcomes and timing of participation across the data ecosystem.

Modeling by DQC shows that the combined Data Trust Score delivers more than double the predictive power of device-level fraud signals on their own when identifying quality-related removals. Predictive accuracy increases as respondents are seen in more projects.

To make the score and data quality markers easier to understand, DQC attaches a built-in recommendation and participant persona to each record. This helps users establish quality limits and improve data sourcing processes.

The Data Trust Score is available through the DQC Quality Tool and via API, and it can be viewed alongside device-level metrics, supplier benchmarks and trend reports in the DQC dashboard.

"This is not just about scoring risk," Fawson added. "By tying the Data Trust Score to clear personas, whether someone reflects gold-standard behavior or 'keyboard-mashing' patterns, teams can actively manage quality upstream and clearly communicate it downstream. That combination helps researchers, suppliers and procurement teams align on expectations, demonstrate rigor and get real credit for investing in better data. Bringing all the quality signals together in one metric also makes it easy to explain to stakeholders."

The Data Trust Score^™ will be rolled out to existing DQC clients starting this month, with broader availability later in the year.

About Data Quality Co-Op
Data Quality Co-op (DQC) is an independent first-party data quality clearinghouse. We transform how buyers and suppliers of first-party data measure, understand and manage the quality of their data. Our platform offers continuous quality measurement and real-time quality certification by aggregating, analyzing and benchmarking data quality signals across the ecosystem and the Data Trust Score^™, delivering unique, predictive quality intelligence. Together with our clients, we are shaping the future of fast, reliable data-driven insights. Headquartered in Salt Lake City, Utah, our mission is to ensure each business decision, marketing campaign or AI model is driven by data that's high-quality, high-value and perfectly suited for its purpose. For more information, visit www.dataqualityco-op.com.

Media contact: Marie Melsheimer, [email protected], +1-541-815-3951 

SOURCE Data Quality Co-Op