Poor responses, fraudulent data, or “overly helpful” quality flags?

Panel fraud boomed during the pandemic, and it’s been growing exponentially ever since.

In fact, researchers are discarding on average 38% of survey data due to quality concerns – with one recent prospect citing that they returned 70% of data from a leading panel provider.

But not every quality-flag triggered is due to people actively falsifying answers. And not all quality-flags have the same impact on data integrity. A single action doesn’t define a panellist - there’s a whole story to tell.

Over the past four years, Kantar’s Profiles division has extensively researched panellist quality. We've interviewed big and small survey buyers, panellists, and competitors and have collected extensive data.

Explore what we’ve learned in “The State of Online Research Panels” and how we’ve applied those findings in our anti-fraud technology, Qubed. We look at:


  1. Common types of bad actors on panels today
  2. The impact each bad-actor has on survey data
  3. How Qubed, Kantar’s proprietary anti-fraud technology, leverages state-of-the-art machine learning and AI to proactively detect fraud 

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