Because we host many participants for different researchers we are able to aggregate the quality data from many researchers and exclude low quality participants for all of them. This anonymous sharing of information ensures a healthy pool of quality participants while retaining participant privacy
It’s our job to make sure you get responses you can rely on, so we only source from panels with a track record of being reliable for research.
In addition to this our quality control and demographic filtering features ensures that you only get participants that are suitable to your study.
Consistent and reliable delivery of high-quality participants is crucial to your research.
We set stringent standards to help ensure you get only the best respondents, examining factors in real-time that could eliminate participants if they do not meet our quality checks.
Our proprietary quality metrics and historical participant data allow us to deliver only participants that will drive your research forward.
We want you to have confidence in your results, that’s why we have these unique quality standards in place. We do not compromise and continuously ensure the validity of these quality checks for all participants.
Unengaged participants can tarnish your data, that’s why we have systems in place to help ensure your respondents will be thoughtfully answering each of your questions.
By default we only allow participants who are in good standing and consistently perform well according to the community of researchers on our platform.
Our digital fingerprinting technology uses browser data, unique participant identifiers, and IP addresses to help ensure that each participant is unique.
A larger pool of respondents allows a more representative sample for your research, as our systems pull a wide range of participants that come with diverse backgrounds and opinions
Researchers are encouraged to report any any data-quality concerns to us and we investigate rigorously, take appropriate action and inform the researchers of the outcomes
We actively monitor and analyse our internal data for any unusual patterns or suspicious behaviour
We use IP address data to detect and restrict to or report on the estimated country of the device used by the participant, this can be matched to the country targeted by the researcher. IP address estimation is not 100% accurate but this is still a useful data point to monitor for unusual patterns.