We like quality participants as much as the next researcher. With that in mind, we take several steps to vet and review our participant audience. We proactively and reactively monitor participant behavior, removing any participants who may be fraudulent or of poor quality.
Participants are asked to verify their account. No email address can be associated with more than one account.
In this day and age, most people can be found on social media. We encourage participants to sync at least one social media account. If a social media account has been synced, you'll see a Facebook, LinkedIn, or both icons next to the participant's name. Due to privacy regulations, you will not be able to access Facebook profiles from our platform. You will be able to access LinkedIn profiles by clicking the icon.
If there's one thing we respect it's everyone's time. We remind participants of upcoming sessions and clearly state our cancelation 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.
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.
Our staff manually removes any participants they have encountered as being rude, hostile, inappropriate, or are generally not exhibiting polite, professional behavior.
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 firstname.lastname@example.org so that they can be removed.
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.