| How User Interviews maintains our high-quality participant audience. |
This article applies to User Interviews
Who is this article for?
🗣️ All researchers (both admins and users)
⭐ Recommended for users of all User Interviews plans
On this page:
- Our approach to participant screening
- Participant audience recruitment
- Participant account verification
- Participation policies
- Researcher insights
- Predictive data
- Indicators for AI use
Our approach to participant screening
- We like quality participants as much as the next researcher. With that in mind, we take several steps to build, vet, and review our participant audience.
- We proactively and reactively monitor participant behavior, removing any participants who may be fraudulent or of poor quality.
- Want to learn how to spot and prevent participant fraud? Our 4-lesson Academy course on Preventing & Recognizing Fraud will teach you everything you need to know to recruit with confidence.
Participant audience recruitment
- We currently recruit within these 34 supported countries.
- Our audience reflects the general population, though we tend to skew toward major urban areas.
- However, we are consistently growing our reach in smaller and niche markets through sponsorships and outreach on social media.
- A significant portion of new participants is referred from our existing participant audience.
- Read why people like participating on User Interviews.
Participant account verification
New account verification
Participants are asked to verify their accounts. No email address can be associated with more than one account.
Sync social media
- In this day and age, most people can be found on social media.
- Participants can choose to provide links to their LinkedIn or Facebook profiles—we encourage participants to provide links to at least one social media account for verification.
LinkedIn profile and identity/workplace verification
- Participants are encouraged to connect their LinkedIn to their UI accounts to add trusted, verified professional details to their UI profile.
- You’ll be able to see participants’ LI verification status directly in the participant table and profile drawers.
- Indicators show whether the participant has logged in and verified ownership of their profile, or completed additional identity and/or workplace verification on LinkedIn.
Participation policies
No show policy
- If there's one thing we respect, it's everyone's time. We remind participants of upcoming sessions and clearly state our cancellation policy.
- Any participant who does not show up for their scheduled interview—a "no-show"—will automatically be flagged in our system.
- These flags add up, making it more difficult for them to be accepted into future studies.
Honesty policy
- If we notice discrepancies between a specific participant's screener responses, we'll flag their account for further review.
- If we find our assumptions to be true, the participant will not be allowed to partake in future studies.
Misbehavior policy
- Our staff manually removes any participants they have encountered as being rude, hostile, inappropriate, or who are generally not exhibiting polite, professional behavior.
Researcher insights
Participant feedback ratings
- When you mark a session as completed, you'll be asked to rate the participant.
- If you give a participant a poor quality rating, you can expect an email from us requesting more details.
- We'll record your insights internally (and privately).
- A participant who receives poor feedback will be unable to participate in future studies until further review.
If you experience any unacceptable or flagging behavior prior to a participant's participation, please email us at projects@userinterviews.com so that they can be removed.
Predictive data
- We've recognized some common threads between participants, and have systems set up to watch for and remove any participants that match that criteria.
- We're always on the lookout for new trends in fraudulent behavior so we can build on our automated detection system.
- So we don't tip off possible fraudulent participants, we won't share here what criteria flags our system.
Indicators for AI use
Highlighting copy-pasted screener responses
- Our system will automatically flag free text screener responses that have been copy-pasted to give you that extra bit of signal when reviewing applicants.
- Behind the scenes, our automated fraud detection will also catch and ban participants with suspicious pasting activity over time.