Marketing Research and Insight Glossary

Definitions, common uses and explanations of 1,500+ key market research terms and phrases.

What is a Professional respondent?

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Professional respondent Definition

A participant who attends many sessions by volunteering for the recruitment lists of different facilities. Most moderators seek to eliminate professional respondents from groups, since they do not generally respond in the same objective way that fresh respondents.

A professional respondent is an individual who frequently participates in research studies – often across multiple panels or recruiting sources – primarily to receive incentives, rather than to genuinely contribute opinions or insights.

What are the key characteristics of professional respondents in marketing research?

  • Frequent participation in surveys or focus groups.
  • May provide dishonest or biased answers to qualify for more studies.
  • Often sign up for multiple panels or use multiple identities.
  • Motivated mainly by compensation.
  • May affect data quality due to overexposure or response fatigue.

Why are professional respondents an issue in market research?

Professional respondents present a significant risk to data integrity and insight validity. Identifying and minimizing professional respondent participation is critical to ensure research results are reflective of genuine, diverse consumer perspectives.

Who relies on professional respondents in marketing research?

  • Unfortunately, some studies may unintentionally rely on them due to poor screening.
  • Fraud detection vendors monitor and mitigate their involvement.
  • Panel providers and sample firms aim to limit their access.
  • Market researchers need to identify and exclude them to protect data quality.

How do market researchers use professional respondents?

Market researchers seek to avoid the use of professional respondents as their repeated participation and questionable motivations can introduce bias and compromise the validity of research findings. Researchers deploy tools such as digital fingerprinting, attention checks and screening algorithms to detect and remove such participants. By managing this risk, they maintain sample quality and ensure that insights drawn from studies reflect authentic consumer behaviors and attitudes – not just the opinions of survey-savvy repeat participants.