Rachel Banawa is an Experience Specialist at Nielsen Norman Group. Rachel leverages her extensive training in quantitative methods and statistics in her research to turn complex data into actionable, evidence-based insights. She holds a Ph.D. in health policy and management from the University of California, Los Angeles.
AI saves UX practitioners time on nearly every task, yet most feel lukewarm about it: mandates, unreliable output, and inflated expectations eat the gains.
The participants you recruit for your study matter. Convenience sampling is fast and common in UX research. Learn how to do it effectively and avoid bias in your studies.
AI can produce polished survey drafts quickly, but experienced human review is still needed to catch subtle survey-design flaws that weaken data quality.
Learn when and why to use post-task and post-test questionnaires in quantitative usability testing – and how combining both can help you pinpoint issues and improve UX.
When creating screener surveys, use fake answer options – called foils – to spot misrecruits before they join your study. Learn how to craft foils that protect your data and catch cheaters early.
