Q01
Message
All templatesResearch
Participant Screener & Demographics
A clean recruiting screener: knock-out questions first, quota-ready demographics, an attention check, and an articulation check that verifies participants can give the rich answers qualitative research needs. Designed to disqualify politely and comply with prefer-not-to-say norms.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
13 questions · ~4 min
Q02
Multiple ChoiceRequired
Do you, or does anyone in your household, work in any of these industries?
- Market research
- Advertising or public relations
- Journalism or media
- The industry this study is about (replace with yours)
Q03
Multiple ChoiceRequired
Which best describes your role in decisions about the product category we're studying?
- I decide on my own
- I share the decision with others
- I influence but don't decide
- I'm not involved
Q04
Multiple ChoiceRequired
How often do you use products in this category?
- Daily
- Weekly
- Monthly
- Less often
- Never
Q05
Multiple ChoiceRequired
To confirm you're reading carefully, please select 'Weekly' for this question.
- Daily
- Weekly
- Monthly
- Never
Q06
Long TextRequired
In 2–3 sentences, describe the last time you used a product in this category — what you were doing and how it went. (This helps us confirm the study fits your experience.)
Q07
DropdownRequired
Which age group are you in?
- Under 18
- 18–24
- 25–34
- 35–44
- 45–54
- 55–64
- 65+
- Prefer not to say
Q08
DropdownRequired
How do you describe your gender?
- Woman
- Man
- Non-binary
- I describe it another way
- Prefer not to say
Q09
Dropdown
What is your approximate annual household income?
- Under $25,000
- $25,000–$49,999
- $50,000–$99,999
- $100,000–$149,999
- $150,000 or more
- Prefer not to say
Q10
Dropdown
What is the highest level of education you have completed?
- High school or less
- Some college
- Bachelor's degree
- Graduate degree
- Prefer not to say
Q11
Dropdown
Which best describes your current employment?
- Employed full-time
- Employed part-time
- Self-employed
- Student
- Not currently employed
- Retired
- Prefer not to say
Q12
EmailRequired
If you qualify, where should we send your invitation?
Q13
Message
Thanks — that's everything! We'll be in touch if the study is a match. Your contact details are used only for this research and never sold or shared.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- Knock-out questions first, an attention check, and an articulation check that verifies participants can give the rich answers qualitative research needs
- Inclusive demographics with prefer-not-to-say on every sensitive item, aligned to standard reporting brackets
- Industry/insider disqualification handled politely — unqualified participants exit with dignity
- Quota-ready structure: every screener answer is filterable for balancing your panel
SurveyMonkey
U.S. Demographics Survey TemplateUsed 7,000+ times; aligns demographic categories (gender identity, age, education, employment, household income, race/ethnicity) to federal ACS and updated OMB standards with inclusive, self-describe options. Excellent as a standards-aligned demographic block, but framed as demographics collection rather than a screening flow with qualify/disqualify branching and quotas.
What it does well
- Category wording aligned to ACS and 2024 OMB standards, including combined multi-select race/ethnicity with MENA
- Inclusive, current gender-identity language with self-describe options
- Standardized income brackets and consistent age/education ranges that benchmark to national data
- Backed by SurveyMonkey's skip-logic and reporting for segmentation
Where it falls short
- Presented as a demographic questionnaire, not a screener: no built-in qualify/disqualify termination logic or quota management on the template itself
- No attention/red-herring screener items to catch professional survey-takers or fraud
- No adaptive follow-up to confirm a borderline qualification (e.g., probe frequency/recency of a behavior)
- No transparent screening rationale shown to sponsor; termination is manual skip-logic the user must wire up
QuestionPro
Demographic Survey Questions + Sample Questionnaire TemplateExpert-designed demographic template spanning gender, age, marital/family, employment, income, education, ethnicity, religion, sexual orientation, housing, and political views, positioned for market, academic, healthcare, and non-profit research. Very broad question bank, but it is a demographic library rather than a screening instrument with disqualification and quota controls.
What it does well
- Unusually broad demographic coverage including psychographic-adjacent items (political views, lifestyle, religion)
- Expert-designed wording positioned for reuse across market, academic, healthcare, and non-profit research
- Free and directly cloneable into the QuestionPro builder
- Flexible enough to assemble a tailored respondent profile
Where it falls short
- No screener-specific qualify/disqualify branching or quota enforcement built into the template
- No attention checks or fraud/duplicate-respondent detection surfaced
- Long, static battery risks over-asking; no adaptive skipping to only ask what a screen needs
- No AI follow-up to disambiguate borderline eligibility responses
Jotform
Focus Group ScreenerA real participant screener form for focus-group recruitment on Jotform's drag-and-drop builder. Handles the intake mechanics well; qualification logic, quota tracking, and data-quality checks are up to the researcher to add.
What it does well
- Purpose-built screener form, free to use and easy to customize
- Jotform's conditional logic can disqualify as respondents answer
- Wide integration ecosystem for routing qualified participants
Where it falls short
- No built-in attention or articulation checks to protect qualitative data quality
- No AI follow-up to verify claimed experience is genuine
- Quota balancing and panel management are manual
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
Related templates
More studies from the same category.
Research
Vignette Experiment: Scenario & Framing Test
A true factorial vignette experiment: respondents judge realistic scenarios whose key details (price framing, messenger, wording) rotate systematically, so you can measure how each factor shifts judgment. The built-in vignette question type generates the scenario combinations for you.
View templateResearch
Photo Diary Study: Product Use in Context
A repeatable diary entry participants complete each time they use your product in real life: a photo of the moment, what they were trying to do, and what got in the way — with an AI probe on the day's friction. Run it daily or weekly to see usage where it actually happens, not in a lab.
View templateResearch
Unmoderated Usability Test with Screen Share & Voice
A self-serve usability session: participants share their screen, complete guided tasks on your website or prototype while thinking aloud, and the AI moderator watches, prompts, and probes — then debriefs them. You get recordings, transcripts, and task-level analysis without scheduling a single session.
View templateResearch
System Usability Scale (SUS) with AI Debrief
The standard 10-item SUS questionnaire, scored 0–100 and benchmarkable against decades of published research — with correct alternating positive/negative wording preserved. An AI debrief interview follows the score, so you learn what to fix, not just where you stand.
View templateResearch
Reproducibility in AI-Moderated Research: A Researcher Assessment
This survey explores researcher experiences with reproducibility, transparency, and data quality in AI-moderated research. It serves as a replication study template to understand current practices, identify barriers, and assess the role of platform transparency in enabling reproducible AI-moderated studies.
View templateResearch
Fintech App User Behavior & Needs Segmentation Survey
Segments financial app users by usage behavior, feature priorities, trust levels, and demographics to build data-driven personas and inform product strategy.
View template