What research buyers are telling us about data quality
t CRC in Chicago, DQC's Bob Fawson joined leaders from SampleCon, Lindt USA, and Sago to unpack new GDQ research on data quality—and what buyers still want to know about the data behind their insights.
Last week at the Insights Association Corporate Researchers Conference in Chicago, Data Quality Co-op CEO Bob Fawson joined Rachel Alltmont, president of SampleCon, John Brodie, consumer insights manager at Lindt USA, and Melanie Courtright, chief strategy officer at Sago, for a discussion about the Global Data Quality initiative.
The session brought together several sources of evidence about how the industry is handling data quality: a new GDQ brand and client-side study of 173 research buyers across 29 countries, the second wave of GDQ/Insights Association quality benchmarking covering 46 companies and 1.8 million records and DQC data based on respondent behavior across studies and suppliers.
Together, the findings show considerable effort going into quality, along with questions from buyers about what happens to the data before they receive it.
Buyers are doing plenty of checking themselves
Research buyers in the GDQ study reported using an average of 4.9 quality checks. Poor or nonsense open-end responses were checked by 71%, 67% compared findings with expected results and half checked for straightlining.
Even with those checks, only 33% said they were confident poor-quality respondents had been removed before the data reached them. GDQ/Insights Association benchmarking found that agencies remove 28.5% of records before delivery.
One research buyer from Switzerland described part of the problem:
“Vendors don’t like going into details about the quality checks they do — it is always broad picture.”
There can be substantial work happening behind the scenes without buyers knowing which checks were used, what they found or why particular respondents were removed.
Quality is already affecting supplier relationships. In the GDQ study, 45% of buyers said they had eliminated a supplier over quality and 39% had paid more for stronger quality controls.
What buyers want to know
The study also asked buyers what they most wanted providers to disclose about quality. Cleaning rules and counts and information about sample source and recruitment were each selected by 62%. Fraud and bot detection followed at 60%, while independent certification was selected by 15%.
Those responses put some specifics around what buyers mean when they ask for more transparency. They want to know where respondents came from, what happened during cleaning and which fraud controls were applied.
A research buyer from the United Kingdom pointed to another problem:
“All of them say they provide high-quality data and we know that they don’t. They use different examples and jargon.”
Different terminology and reporting practices make it harder to understand what sits behind a provider's quality claims and to compare approaches across providers.
The Global Data Quality initiative is working toward common language, definitions and approaches that can make this type of disclosure easier across organizations.
DQC data shows how much practices can vary
DQC's own data provides another view of what happens within surveys. Across 15 agencies during the first half of 2026, five averaged fewer than two automated in-survey quality checks per survey start. Four averaged between two and four, three averaged between four and six and three averaged between six and eight.
The range is worth considering alongside 2024 research by Pinzon and colleagues cited in the presentation. After evaluating 31 in-survey quality checks, the researchers found that no single check proved reliable; only ensembles worked.
DQC sees similar variation in practice across the industry, with providers applying different numbers and combinations of checks. For buyers, knowing that quality controls are in place only tells part of the story. Knowing which controls were used and what they found provides more information about how the data was handled.
The CRC discussion showed how difficult it can still be for a buyer to know what sits behind a provider's quality claims. The GDQ research gives providers a fairly direct indication of what buyers want to see: where respondents came from, what checks were applied and what happened during cleaning.
Creating a more consistent way to share that information is part of the work now underway through the Global Data Quality initiative, and we’re proud to be involved.