In this no-filter episode of Signal & Noise, hosts Brian and Andrew dive into one of the most pressing issues in market research: the misuse of fraud detection platforms. They unpack how digital fingerprinting tools, while valuable, are often implemented in ways that damage data quality and block legitimate respondents.

Brian and Andrew explain how overly-aggressive fraud settings can create non-response bias, limit sample diversity, and frustrate real participants. They reveal why using multiple fraud detection tools or relying solely on automation can lead to distorted data and wasted resources.

They share lessons from industry research, stories of clients who turned off their fraud filters and saw better outcomes, and practical insights into balancing data protection with respondent experience. The conversation builds toward Brian’s “Eight Steps to Winning,” a clear framework to improve quality, restore trust, and move the industry forward.

Key Takeaways:

• Why misusing fraud detection tools can do more harm than good

• How false positives block real people and skew your data

• The hidden consequences of using multiple fraud platforms

• The Eight Steps to Winning framework for better data quality

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