
Multiple choice questions: Design best practices for surveys
Design multiple-choice questions that are clear, exhaustive, and unbiased so your survey yields dependable, actionable data and not misleading noise.
Insights on expert networks, market research, UX research, and AI training from the CleverX team.
86 articles

Design multiple-choice questions that are clear, exhaustive, and unbiased so your survey yields dependable, actionable data and not misleading noise.

Use single-response questions to force prioritization, collect clean, analyzable data, and segment users: ideal for demographics, preferences, and priorities.

Detailed case studies of AI-moderated interview implementations: challenges faced, approaches used, results achieved, and key lessons. Actionable insights for your research strategy.

Use AI to analyze interviews faster. Learn automated coding, theme extraction, quality validation, and which platforms work best.

AI is fundamentally changing user research. Learn about emerging capabilities, future trends, and how to prepare your team with proven strategies and examples.

Automated vs. human interviews: understand benefits, limitations, costs, and scalability to make the right choice for your research.

How is AI changing user research? Use cases in interviews, analysis, recruitment, and synthesis, with real examples from product teams.

Quick rundown: trade-offs in speed, cost, and insight quality, plus when to combine both.

Top AI research tools compared: user interviews, qualitative analysis, and insight generation. features, pricing, use cases, and recommendations to find your ideal platform.

A short look at how AI runs interviews, boosts efficiency, and when to keep humans in the loop.

Stop recruitment chaos: define clear criteria, use multiple channels, screen out fakes, and build a participant panel that delivers fast.

Discover how to run effective remote user testing that rivals in-person research quality. This practical article covers platform selection, session facilitation techniques, and proven practices from product teams conducting successful distributed research.