By: Mary Draper, VP, Strategic Accounts & Quality, EMI
The market research industry has never had more tools to combat fraud. Advanced fingerprinting, AI-powered detection, digital identity verification, behavioral analytics. Biometric, real-time scoring, and more. New platforms continue to enter the market, each promising to identify more bad respondents before they impact research.
Yet one uncomfortable reality remains:
No single company - not a technology vendor, sample provider, research agency, or brand - has solved the data quality problem. And perhaps that's because no single one can.
The Industry Has Been Solving Different Pieces of the Same Problem
Every organization involved in online research sees fraud through a different lens.
• Sample providers focus on respondent acquisition and authentication.
• Research agencies focus on survey execution and respondent engagement.
• Technology companies focus on detecting suspicious behavior.
• Brands focus on making confident business decisions.
Each perspective is valuable. Each is also incomplete.
That's one of the clearest lessons emerging from industry initiatives like the Global Data Quality’s (GDQ) Benchmarking Report, which has brought together dozens of organizations across multiple countries to benchmark quality metrics using shared definitions and reporting standards.
Standard Definitions Matter More Than We Think
After more than 20 years in online sampling and conducting research-on-research into the industry, including tools like fraud detection platforms, one of the more subtle data quality themes that has emerged isn’t about fraud detection technology at all. It was about language.
Historically, companies have described quality using different terminology. What one supplier calls "fraud," another may call a quality failure. What one agency labels an in-survey removal, another may classify as post-survey cleaning. Those differences make benchmarking difficult.
The GDQ initiative represents meaningful progress because it begins to create common definitions for pre-survey, in-survey, and post-survey quality management. Once everyone is speaking the same language, the industry can begin measuring progress in meaningful ways.
Better Data Requires Better Partnerships
Technology alone cannot compensate for poor collaboration between providers and clients.
Consider a typical online study:
• A sample provider authenticates respondents.
• The research firm designs the questionnaire.
• Fraud detection software screens participants.
• Researchers monitor fieldwork.
• Clients determine project objectives.
Every one of those decisions influences data quality. If any link in that chain breaks down, quality suffers. The problem is that many of these steps are often done in the silos of the sample provider, research firm, and end-client.
Data quality is no longer the responsibility of one organization. It is the outcome of many organizations working together.
Layered Quality Extends Beyond Technology
Much of the industry's discussion around a layered quality approach focuses on stacking multiple fraud detection tools.
While this is important, it’s only one component. A true layered data quality approach extends further. It includes:
• Better respondent sourcing
• Smarter survey design
• Effective in-survey quality controls
• Post-field validation
• Human review
• Shared reporting
• Common standards
Technology is only one layer. True partnership is another.
Looking Forward
We know fraudsters collaborate with one another; why don’t we?
The organizations that will produce the most trustworthy data won't necessarily be those with the newest detection platform. They'll be the ones that successfully connect people, processes, and technology into a coordinated quality strategy.
Because the future of data quality isn't built by one company. It's built by an industry.
ABOUT THE AUTHOR
Mary Draper, VP, Strategic Accounts & Quality, EMI
With a wealth of market research knowledge and experience under her belt, Mary joined the EMI team in 2014 as a Sr. Research Manager. Now, as the Vice President, Strategic Accounts & Quality, she ensures the health and integrity of the data we provide clients, offering expertise on online sample, project management, and quality best practices. Mary’s keen attention to detail and reliability make her a valuable asset to the team, even in the most fast-paced and dynamic environments. When she’s not working, Mary can be found traveling the world, ranking burgers, binging on Netflix, and shopping at Publix.