designing-surveys
Survey design framework grounded in product research best practices from nine leaders.
- Prioritize CSAT over NPS for better statistical properties and business outcome correlation; use 5-7 item scales
- Design single-variable questions only; avoid double-barreled phrasing that conflates multiple concepts
- Target customers 3-6 months post-signup when memory of the "before" state is fresh and relevant
- Use MaxDiff (Most/Least) methodology for feature prioritization rather than unlimited rating scales
- Force respondents to prioritize by limiting selections (e.g., "pick your top three") and measure frequency to weight impact
Designing Surveys
Help the user design effective surveys using frameworks from 9 product leaders who have built rigorous research and feedback systems.
How to Help
When the user asks for help with surveys:
- Clarify the goal - Determine if they're measuring satisfaction, identifying problems, or prioritizing features
- Choose the right metric - Help them select between NPS, CSAT, PMF survey, or custom approaches
- Design clean questions - Ensure each question measures one thing precisely
- Target the right respondents - Help them reach users with fresh, relevant experience
Core Principles
NPS is scientifically flawed
Judd Antin: "NPS is the best example of the marketing industry marketing itself. The consensus in the survey science community is that NPS makes all the mistakes. Customer satisfaction, a simple CSAT metric, is better. It has better data properties, it is more precise, it is more correlated to business outcomes." Use CSAT with 5-7 item scales instead.
Force prioritization with constraints
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