High-quality insights depend on high-quality participation

As the data quality landscape evolves, traditional fraud checks alone are no longer sufficient. Today’s environment requires a more comprehensive approach that considers both respondent legitimacy and engagement.

We designed this checklist to help research teams evaluate how well their current approach supports data quality throughout the research process.

We also know that keeping pace with today’s data quality challenges requires more than individual tools or isolated checks. It calls for a connected approach that brings the right signals together and applies them consistently throughout the research process. And yes, that can be a lot to manage on your own!

We’re experts in building that structure into every study. RADAR (Respondent Analysis & Data Anomaly Recognition), our proprietary quality framework, is part of how we do that. It evaluates both technical indicators and participant behavior to help ensure respondents are not only legitimate but also prepared to contribute thoughtfully before they enter your survey.

Our role is to help make the process easier to manage. We work alongside our clients to understand their needs, identify potential risks, and support a data quality approach that aligns with their research goals.

Let’s identify practical ways to strengthen data quality in your next study.
Contact us learn more.