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survey-design skill

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This skill helps you design rigorous surveys with objective clarity, sampling plans, QA, and logic to improve data quality and insights.

npx playbooks add skill gtmagents/gtm-agents --skill survey-design

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: survey-design
description: Use to craft rigorous survey instruments with sampling, question logic,
  and QA standards.
---

# Customer Survey Design Kit Skill

## When to Use
- Launching new surveys or refreshing existing templates.
- Diagnosing low response quality or bias in ongoing programs.
- Training GTM teams on survey best practices.

## Framework
1. **Objective Clarity** – define single-topic goals, hypotheses, and decision criteria.
2. **Audience & Sampling** – specify personas, quotas, suppression rules, and incentive plan.
3. **Question Architecture** – balance quant vs qual questions, avoid double-barreled prompts, include screener + validation items.
4. **Logic & Branching** – outline conditional flows, progress indicators, and completion time targets.
5. **QA Checklist** – test across devices, languages, anonymity rules, and data export formats.

## Templates
- Survey brief (goal, audience, sample, success metrics).
- Question bank categorized by objective (adoption, satisfaction, pricing, roadmap).
- QA script for reviewers to confirm copy, logic, and translations.

## Tips
- Cap surveys at <10 minutes unless offering significant incentives.
- Randomize answer choices when appropriate to reduce bias.
- Pair with `stakeholder-ops` to align approvals and launch windows.

---

Overview

This skill helps craft rigorous customer surveys with clear objectives, sampling plans, question architecture, branching logic, and QA standards. It standardizes survey briefs and templates so teams can launch reliable instruments that produce actionable insights. Use it to reduce bias, improve response quality, and accelerate decision-making from survey data.

How this skill works

You provide the project context (objective, audience, timeline) and the skill generates a complete survey artifact: a brief, a question bank organized by objective, a branching map, and a QA checklist. It recommends sampling rules, quotas, screening items, and validation checks, then produces copy-ready question text and logic scripts. The output includes time estimates, randomization suggestions, and a test plan to verify translations and exports across devices.

When to use it

Launching a new customer survey or refreshing an existing template
Diagnosing low response quality or suspected survey bias
Designing quotas, suppression rules, or incentive plans for sampling
Preparing stakeholder-ready survey briefs and approval artifacts
Training GTM teams on practical survey best practices and QA

Best practices

Define a single clear objective and associated decision criteria before writing questions
Cap estimated completion time under 10 minutes unless incentives justify longer surveys
Balance quantitative and qualitative items; avoid double-barreled or leading questions
Include screener and validation items, randomize choices where appropriate, and document suppression rules
Run a device- and language-aware QA script: translations, anonymity, branching, and export formats

Example use cases

Product adoption survey: brief, adoption question bank, and segmentation quotas for power users
Pricing sensitivity study: randomized price anchors, follow-up qualitative probes, and quota controls
Post-release satisfaction pulse: short template with progress indicators and completion time goals
Market segmentation screener: detailed sampling rules, suppression lists, and persona quotas
Internal QA review pack: reviewer checklist to validate logic, copy, and CSV/JSON export fields

FAQ

How long should a survey be?

Keep surveys under 10 minutes for general audiences; longer instruments require clear incentives and explicit consent.

How do you reduce selection bias?

Specify clear sampling frames, use quotas, apply suppression rules, and randomize answer order where appropriate.