Survey Designer
Design validated survey instruments with bias checks and branching logic
What You Can Do
You can rapidly prototype survey instruments from research questions to implementation-ready form specifications. The skill produces validated question sequences with explicit reasoning, matches appropriate scales (Likert, NPS, semantic differential) to your research goals, diagrams branching logic for conditional routing, flags potential biases and confounded items, and recommends pilot test protocols with sample size guidance—accelerating the instrument validation phase before deployment.
Features
generates validated question order with explicit reasoning for each item type and placement
recommends appropriate measurement scales (Likert, semantic differential, NPS, ranking) aligned to research objectives
visualizes conditional routing rules in implementation-ready format for Typeform or Google Forms
identifies leading questions, double-barreled items, anchoring effects, and confounded scales with correction suggestions
specifies data quality checks and attention filters to ensure response integrity
provides sample size recommendations, data quality thresholds, and iteration checkpoints
formats all question text and branching rules for direct import into survey platforms
tailors question language and complexity to target respondent characteristics
Example Output
Survey Example Output:
Question 1 (Screener) Text: "Have you used a mobile banking app in the past 6 months?" Type: Yes/No branching Branching: Yes → Q2 | No → Thank you page
Question 2 (Open discovery) Text: "What is your primary reason for using mobile banking?" Type: Open text (5-10 words) Validation: Minimum 5 characters Reasoning: Exploratory, captures unaided motivations before closed options anchor responses
Question 3 (Satisfaction scale) Text: "How satisfied are you with the speed of transactions?" Type: 5-point Likert (Very Dissatisfied → Very Satisfied)
- ⚠️ Bias flag: Question is specific (speed only). Consider parallel items for security, UI clarity to avoid response set bias.
Branching Logic: IF Q3 = "Very Dissatisfied" OR "Dissatisfied" → Route to Q4 (follow-up diagnostics) ELSE → Skip to Q5 (general satisfaction)
Pilot Test Recommendation: Sample: n=20–30 cognitive interviews Primary check: Verify Q2 responses cluster into 3–5 clear themes Secondary check: Confirm Q3 scale discrimination (no >40% single response option)
What's Included
- SURVEY-DESIGNER.md: Core skill instruction file with question taxonomy and scale selection logic
- Question Bank Template: Pre-built question sets for common UX research scenarios (discovery, satisfaction, usability, NPS)
- Branching Logic Worksheet: Step-by-step guide to map conditional routing and skip patterns
- Bias Detection Checklist: Systematic checklist for identifying leading questions, ambiguity, and response set bias
- Pilot Test Protocol: Sample size guidance, cognitive interview framework, and data quality acceptance criteria
Who It's For
- UX Researchers designing product discovery and post-launch satisfaction surveys
- User Research Leads validating survey instruments before deployment at scale
- Product Managers building feedback mechanisms and NPS tracking programs
- Academic Researchers developing questionnaires for human subjects studies
- Customer Success Teams creating satisfaction and churn prediction surveys
Best For
- Exploratory discovery surveys mapping user behaviors and motivations
- Post-launch satisfaction and NPS tracking instruments
- Usability testing feedback forms with conditional routing
- Screening surveys to segment respondents into research tracks
- Iterative survey refinement and pilot testing before full deployment
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