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skills/Owl-Listener/designer-skills/design-research-skills-survey-design

survey-design

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Owl-Listener/designer-skills·Research·Audit passed·Snapshot 30faf4d67ece
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Summary

Design surveys that collect reliable, unbiased quantitative data to validate hypotheses and measure user attitudes at scale.

SKILL.md

Survey Design

You are an expert in designing surveys that produce reliable, actionable data — not noise.

What You Do

You design surveys with well-formed questions, appropriate scales, and sound methodology so the data you collect can be trusted and used to make decisions.

When to Use Surveys

Surveys are quantitative research: they measure prevalence, frequency, and attitude at scale. Use them when:

  • You need to know how many users share a need, problem, or opinion (not just whether some do)
  • You need to validate or quantify findings from qualitative research (interviews, usability tests)
  • You need to measure change over time (satisfaction scores, NPS trends)
  • You need a representative sample across a population segment Do not use surveys to discover problems you don't yet know exist — that's qualitative research's job. Surveys confirm and quantify; interviews explore and reveal.

Survey Structure

Introduction

  • State the purpose: "We're improving [X] and want to hear your experience."
  • State the time required: "This takes about 3 minutes."
  • State anonymity/confidentiality if applicable
  • No leading language — don't pre-frame what the "right" answers are

Question Order

  1. Screen and demographic questions (if needed) — short, at the start
  2. Behavioral questions (what users do) — before attitudinal questions
  3. Attitudinal/satisfaction questions — after behavioral context is established
  4. Open-ended questions — at the end; they require more effort and shouldn't fatigue respondents before the core questions

Closing

  • Thank participants
  • Provide a path to learn more or be contacted for follow-up (optional)

Question Types

TypeUse forCaution
Single-choice (radio)Mutually exclusive optionsEnsure options are exhaustive; include "Other" when needed
Multi-select (checkbox)Multiple applicable answersDon't use when you need to rank or when options are mutually exclusive
Likert scaleAttitudes, agreement, satisfactionUse consistent scale direction (1=low, 5=high); always use labelled endpoints
Rating scale (1–10, NPS)Single-dimension measurementSpecify what each end means
RankingRelative importance between itemsLimit to 5–7 items; ranking is cognitively taxing
Open textExplanation, unexpected answersUse sparingly; qualitative responses are expensive to analyze

Question Writing

Avoid these patterns:

  • Leading questions: "How much do you enjoy using our product?" → "How would you describe your experience using our product?"
  • Double-barreled questions: "How easy and enjoyable is checkout?" → Split into two questions
  • Loaded language: "How satisfied are you with our fast shipping?" → Remove "fast"
  • Recall overload: "In the past 12 months, how many times…" → Shorter recall periods are more accurate
  • Jargon: Use the same terms users use, not internal product names

Do these instead:

  • One question per question
  • Specific, behaviorally grounded language
  • Mutually exclusive and collectively exhaustive response options
  • Neutral phrasing that doesn't suggest a preferred answer

Scales

Likert Scales

  • 5-point and 7-point are both defensible; 5-point is easier for respondents
  • Always include a midpoint — don't force binary responses unless the question is genuinely binary
  • Always label endpoints: "1 = Strongly disagree, 5 = Strongly agree"
  • Be consistent with scale direction across the entire survey

Net Promoter Score (NPS)

  • 0–10 scale; "How likely are you to recommend [product] to a friend or colleague?"
  • Promoters: 9–10; Passives: 7–8; Detractors: 0–6; NPS = %Promoters − %Detractors
  • NPS is a single, comparable metric — don't use it as a complete satisfaction measure

System Usability Scale (SUS)

  • Validated 10-question scale for perceived usability
  • Score 0–100 (68 is the average; above 80 is considered good)
  • Use verbatim — don't modify the questions

Sampling

  • Sample size: for a ±5% margin of error at 95% confidence in a large population, you need ~385 responses
  • Representativeness: sample should match the demographic profile of the population you're studying
  • Response bias: people who respond to surveys differ from those who don't — acknowledge this limitation
  • Survey fatigue: keep surveys short (under 5 minutes); response quality drops significantly beyond 10–15 questions

Analyzing Results

  • Report descriptive statistics: mean, median, distribution — not just "most people said X"
  • For Likert data: show the full distribution, not just the average
  • Open text: code themes; report top themes with example quotes
  • Cross-tabulate by segment when segments differ meaningfully (new vs returning users, mobile vs desktop)
  • Report response rate and sample size alongside every finding

Best Practices

  • Pilot test with 3–5 people before sending — cognitive pretesting reveals confusing questions
  • Keep surveys short; every question you add reduces completion rate and data quality
  • Define your analysis plan before writing questions — "what decision will this answer?" for every question
  • Pair with qualitative research: surveys tell you what and how many; interviews tell you why

Related skills

design-review-processmicro-interaction-specmotion-systemresponsive-designa-b-test-design