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Research quality depends on the people you’re talking to. If a participant is rushing through questions, copy-pasting answers, or gaming the system to collect an incentive, the data they produce can skew your analysis and undermine your findings. Listen checks participants when they enter a study, and rates every response after the interview. These checks run automatically on every study. There is nothing to configure.

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How the Checks Work

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When a Participant Enters a Study

  • Device checks: Listen checks device signals when a participant opens your study, to catch duplicate accounts and known bad actors.
  • Participation cooldown: A participant who recently answered one of your workspace’s studies cannot take another until the cooldown ends. The default is 7 days. Admins can set it from 0 to 90 days in Workspace settings, and each study can override it.

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After Each Interview

Every response gets one quality rating: Excellent, Good, Average, Low, or To Review. Each rating comes with the reason for it and up to three quotes from the interview as evidence. The rating looks at whether answers address the question, how much detail they give, how the participant handles follow-up questions, and whether answers repeat. To Review marks a response that may be fraudulent. Read it before you decide to keep or hide it.

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What Happens to Low-Quality Responses

For participants recruited from a Listen panel, Listen sends the rating to the panel:
  • General Population: Low and To Review responses are rejected with the panel.
  • Focused Population: Low and To Review responses are flagged to the panel for review.
Whether a rejected participant is replaced depends on the panel and your study setup. For participants you recruit yourself, nothing is sent to a panel: you decide which responses to hide.

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Your Visibility Into Response Quality

You can see how every response was rated. Nothing is hidden or removed without a trace.
  • Quality rating on every response: In the Responses tab, the Quality Score column shows each response’s rating. Open a response to see the reason and the supporting quotes.
  • Manual response management: If you disagree with a quality decision — or want to exclude a response for your own reasons — you can manually hide any response from your analysis without permanently deleting it.
  • Screened-out response visibility: Responses that were removed by your screener are visible in the Screened Out Responses view, so you can review how your screener criteria are performing and adjust if needed.

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Enterprise Security

Listen is built for teams that take data security seriously. The platform meets the highest standards for compliance, encryption, and data governance.
  • SOC 2 Type II certified — independently audited controls for security, availability, and confidentiality
  • GDPR and CCPA compliant — full compliance with global and U.S. data privacy regulations
  • Triple ISO certification — AI Management (ISO 42001), Information Security (ISO 27001), and Privacy (ISO 27701)
  • 256-bit encryption at rest and in transit — your data is protected at every stage
  • Your data is never used to train AI models — participant responses belong to you, not to Listen’s AI systems
Questions about quality or data security? Email support@listenlabs.ai.