Audit data labeling operations fast with this survey template. Measure instruction clarity, bias mitigation, QA rigor, and workflow. Easy to customize; private.
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AI-Powered Questions
Intelligent follow-up questions based on responses
Automated Analysis
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Template Overview
26
Questions
AI-Powered
Smart Analysis
Ready-to-Use
Launch in Minutes
This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
Welcome! This short survey (about 5–7 minutes) asks about your labeling work in the last 30 days. Please answer based on your experience; there are no right or wrong answers.
Q2
Multiple Choice
In the past 30 days, which tasks have you performed? Select all that apply.
Labeling/annotation
Reviewing/QA
Q3
Dropdown
How long have you worked on this labeling program?
<1 month
1–3 months
4–6 months
7–12 months
1–2 years
2+ years
Q4
Opinion Scale
Overall, how clear were task instructions in the last 30 days?
Range: 1 – 10
Min: Very unclearMid: NeutralMax: Very clear
Q5
Long Text
Briefly describe one unclear or conflicting instruction you encountered.
Max 600 chars
Q6
Rating
In the last 30 days, how often did instructions change mid-project?
Scale: 11 (star)
Min: NeverMax: Very often
Q7
Multiple Choice
Which bias topics are covered in your current guidelines? Select all that apply.
Demographic bias (e.g., gender, race, age)
Domain or jargon bias
Geographic/vernacular variation
Label leakage or proxy signals
Harmful stereotypes and toxicity
Context/translation bias
Q8
Opinion Scale
In the last 30 days, how often did you encounter biased inputs or labels?
Range: 1 – 10
Min: NeverMid: SometimesMax: Very often
Q9
Long Text
Share one recent example of potential bias and how you handled it.
Max 600 chars
Q10
Opinion Scale
When bias is suspected, how clear is the escalation path?
Range: 1 – 10
Min: Not clearMid: ModerateMax: Very clear
Q11
Rating
How clear are the acceptance criteria used for reviewing work?
Scale: 11 (star)
Min: Not clearMax: Very clear
Q12
Multiple Choice
Which review approach is used most often?
Blind double review with adjudication
Spot checks (fixed percentage)
Heuristic-triggered review (rules-based)
Peer review within team
Self-review before submit
Not sure
Q13
Matrix
Please rate the review feedback you received in the last 30 days.
Rows
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Feedback was timely
•
•
•
•
•
Feedback was specific
•
•
•
•
•
Feedback was actionable
•
•
•
•
•
Tone was respectful
•
•
•
•
•
Q14
Opinion Scale
Attention check: To confirm attention, please select Neutral for this item.
Approximate percent (%) of items returned for rework in the last 30 days.
Accepts a numeric value
Whole numbers only
Q16
Ranking
Rank the top causes of rework you observed (most to least).
Drag to order (top = most important)
Unclear or changing guidelines
Reviewer–labeler disagreement
Edge cases not covered
Tooling or platform issues
Time pressure or quotas
Insufficient training/context
Q17
Constant Sum
Distribute 100 points across your typical weekly time on this program.
Total must equal 100
Labeling/annotation
Review/QA
Guideline reading/updating
Meetings/sync
Training/onboarding
Escalations or questions
Other
Min per option: 0Whole numbers only
Q18
Multiple Choice
Which tooling issues most slowed quality or speed recently? Select all that apply.
Slow loading or lag
Limited shortcuts or templates
Poor diff/compare views
Unclear error messages
Hard to flag bias or edge cases
Limited audit trail/metadata
Q19
Short Text
What single change would most improve clarity, fairness, or QA?
Max 100 chars
Q20
Dropdown
What is your primary working region? (optional)
North America
Latin America
Europe
Middle East
Africa
South Asia
East Asia
Southeast Asia
Oceania
Q21
Dropdown
What is your primary working language? (optional)
English
Spanish
Portuguese
French
German
Chinese
Japanese
Korean
Hindi
Arabic
Q22
Dropdown
Total experience in data labeling/annotation
<6 months
6–12 months
1–2 years
3–5 years
6+ years
Q23
Dropdown
Employment type on this program
Full-time
Part-time
Contract/Freelance
Not sure/Prefer not to say
Q24
Long Text
Anything else you’d like us to know about clarity, bias, or QA?
Max 600 chars
Q25
AI Interview
AI Interview: 2 Follow-up Questions on labeling operations
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Q26
Chat Message
Thank you for your time—your feedback helps improve clarity, fairness, and quality.
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