Rethinking respondent experience with a whitelisting-first mindset

What if we rewarded good survey participants instead of punishing the bad? This is exactly the question that our head of commercial, Katie Casavant, explores in her latest article for Greenbook. She dives into how a whitelisting framework (a kind of “FICO score for research”) could transform the respondent experience and strengthen data quality across the industry.

In "What if We Rewarded Good Survey Participants Instead of Punishing the Bad?," Katie lays out a simple but powerful idea: instead of relying solely on blacklists and friction-heavy fraud defenses, we should consider ways to let trustworthy participants carry their credibility with them. As she writes, whitelisting is “a framework that enables verified participants to earn trust and carry that credibility from survey to survey.”

This shift isn’t about being lenient; it’s about being strategic. Good respondents are often stuck in the same repetitive traps as bad actors, losing time, patience, and ultimately any desire to participate. Katie points out how “the fragmented nature of survey ecosystems… means that even great participants get caught in a loop of redundant checks and unclear incentives.” One industry veteran even spent more than 20 minutes in routing limbo without ever reaching a survey; a familiar story for many who’ve tried to walk the respondent path themselves.

The impact is particularly acute in B2B research. Professionals want surveys that “respect their time, feel relevant, and deliver something of value in return,” yet they often face the same disjointed experience. For executives and specialists with limited availability, a few frustrating minutes can mean abandoning the survey altogether, and taking high-quality data with them.

Whitelisting, as Katie frames it, offers a path forward. A dynamic “fast-pass-style certification” could allow verified respondents to bypass redundant screening, unlock better-designed surveys, and participate more efficiently. Researchers, in turn, could benefit from lower dropout rates, faster field times and cleaner datasets.

Katie is clear that this won’t solve every challenge. It will take industry coordination, shared identifiers, and new thinking around incentives. But it’s a direction worth exploring. “When we start designing systems that prioritize good actors instead of obsessively targeting the bad,” she writes, “we open the door to better experiences, better data, and ultimately, better decisions.”

Her full article in Greenbook expands on the vision and why now is the right moment for our industry to rethink how we treat the people at the heart of every study. Read Katie’s piece on Greenbook to dive deeper into the whitelisting model and what it could mean for data quality: https://www.greenbook.org/insights/data-science/what-if-we-rewarded-good-survey-participants-instead-of-punishing-the-bad