Screeners rank applicants and can screen out the ones who clearly don't fit. Anyone can apply to your study; your screener answers determine each applicant's eligibility score, and that score determines who rises to the top. Here's everything that follows from that.

With conditional logic, you can skip applicants to different questions based on their answers, so they only see the questions that apply to them. A Knockout answer ends the screener early. You still see every applicant with all of their answers, and knocked-out applicants are hidden behind a filter. Screeners are for screening, not data collection; if an answer is just nice-to-have, ask it in your session or survey instead.

When you write a multiple-choice question, you set each answer to May select, Must select or Knockout. An applicant's eligibility score is the share of Must select answers they chose, out of the Must select answers they were shown. Someone who chooses every Must select answer they see scores 100%. Choosing a Knockout answer screens them out rather than lowering their score.

Must select is only available on multi select questions. On single select questions, set the answers that rule people out to Knockout.%.

Open-text (short answer) responses carry no weight in the score. The system can't judge free text, so an open-text-only screener leaves every applicant unscored on the things you care about. This is the most common screener mistake we see, and it's the usual cause of wrong-fit recruits: a study asks "What is your role?" as an open question, scoring treats everyone the same, and the wrong people get invited. If a criterion decides who gets in, make it multiple choice with Must select or Knockout answers.

This matters doubly with automated participant selection, where only applicants who score 100% are invited automatically.

If you want Apple eaters, an applicant who selects Apple, Banana and Mango meets this question's requirement, because they chose the Must select answer. An applicant who selects only Banana and Mango doesn't, so their score goes down. An applicant who selects "I don't eat fruits" is screened out.

If you specifically want people who don't choose something, set that answer to Knockout. For example, to recruit people who don't eat bananas, set Banana to Knockout.

This pattern is useful for finding people who don't use your product or service.

You can edit screener questions freely while your study is in draft or in review. Once the study is live, screeners are locked, because changing the questions mid-recruitment would make applicants' scores incomparable. If you need a change on a live study, message us on live chat and with your permission, we can edit it on your behalf or see can I add a screener question after my study is live.

In the Recruit tab's Screener questions section, use Copy from another study to pull in questions from a previous study. This works for studies within your own team; if you need screeners copied across from a different team, message us on live chat and we'll do it for you.

The score is a ranking aid, not a verdict, and it can blur together when you have a complex matrix of criteria. Use segments to filter applicants by the specific answers that matter and manage your quotas precisely.

If you have any questions while writing your screeners, message us on live chat.