Use AI to speed up research, analyze data faster, and improve decision-making. But remember—AI is here to assist, not replace critical thinking.

This library is designed to help you make the most of AI while keeping human expertise at the center.

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How to use this?

📌 What's inside?


1. AI prompts for defining research goals & planning

“What should I focus on? How do I frame my research goals?”

AI Prompt Follow-up Prompts Verdict
"Define 5 research objectives for evaluating [feature/product]" "Can you make them more specific?"
"Which one of these is easiest to measure?" ✅ AI provides structured goals but may be broad
"Suggest the best research method for [feature]—usability testing, surveys, or interviews?" "What’s the best approach if I have a short timeline?"
"What if my budget is super tight?" ✅ AI lists methods but lacks feasibility checks
"Turn these user complaints [paste feedback] into research questions" "Can you rephrase them so they don’t sound biased?"
"Which of these would work well in a survey?" ✅ AI helps reframe but still needs refining
"Generate hypotheses on why users drop off at [step in journey]" "Can you prioritize these based on impact?"
"How would I validate this with real data?" ✅ AI generates hypotheses but lacks nuance
"Summarize key industry trends in UX research" "Which of these are actually gaining traction?"
"Can you make this sound less generic?" ✅ AI gives broad insights but lacks depth
"Generate 5 potential A/B test ideas for [feature]" "Which of these would have the biggest impact?"
"How would I measure success?" ✅ AI suggests test cases but lacks real-world prioritization
"Create a roadmap for a 10-day UX research sprint" "Can you make it work for a 5-day sprint instead?"
"What are the most critical steps?" ✅ AI drafts timelines well, but lacks context
"Suggest ways to make remote UX research more effective" "What are the top tools for this?"
"How do I keep participants engaged?" ✅ AI provides good remote research tips

Pro Tips:

Extra Resources: 10-day UX research timeline template


2. AI prompts for finding the right participants

“Who should I recruit? How do I find the right users?”

AI Prompt Follow-up Prompts Verdict
"Create a screening survey to recruit participants for [usability test]" "Make sure it’s neutral"
"Ensure diversity in selection" ✅ AI writes a solid draft but needs bias checks
"Write a recruitment email that sounds human and compelling" "Make it less formal"
"Give a clear reason to join" ✅ AI drafts an email but often sounds generic
"Segment users based on behavior for [test type]" "Identify power users separately."
"Include hesitant users for contrast." ✅ AI suggests segments but lacks emotional nuance
"Suggest ways to recruit niche participants for [specific study]" "Focus on offline and unconventional sources" ✅ AI offers common ideas but lacks creativity
"Write a follow-up email for confirmed participants" "Make it warm and engaging" ✅ AI creates a good structure but might lack personalization
"What are 5 common mistakes in participant recruitment?" "Give solutions for each mistake" ✅ AI highlights typical errors but needs deeper analysis
"List incentives that work best for UX research participants" "Differentiate based on B2B vs B2C users" ✅ AI suggests typical incentives but may lack motivation analysis
"What’s the best sample size for usability testing?" "Explain trade-offs of smaller vs. larger sample sizes" ✅ AI gives a standard answer but lacks research context