Insights on expert networks, market research, UX research, and AI training from the CleverX team.
222 articles
Food delivery apps operate under time pressure, hunger-driven decisions, and multi-sided marketplace dynamics. This guide covers research methods, recruitment, and testing frameworks for product and UX teams.
HR tech products serve two audiences with competing needs: HR teams who administer the system and employees who interact with it reluctantly. This guide covers research methods, recruitment, and frameworks for people tech UX teams.
Banking user research operates under regulatory constraints, trust dynamics, and multi-channel complexity that generic UX methods cannot handle. This guide covers research methods, recruitment, and frameworks for financial services product teams.
Travel products serve users during high-emotion, high-spend moments where a single UX failure can ruin a vacation or a business trip. This guide covers research methods, recruitment, and frameworks for travel product teams.
Insurance products ask users to pay for something they hope they never use, creating a trust and comprehension challenge that generic UX methods cannot address. This guide covers research methods, recruitment, and frameworks for insurance product teams.
Automotive UX research happens at 70 mph. Distraction kills, safety is non-negotiable, and users interact with interfaces while operating heavy machinery. This guide covers research methods, recruitment, and frameworks for mobility product teams.
Choosing the right user research tools means knowing how platforms compare across method support, participant access, and pricing. This covers the top platforms in each category, with key specs, pricing models, and recommended stacks for B2B and B2C programs.
Participant screening determines whether the people who show up in research sessions actually represent the population the research needs to understand. AI-powered screening addresses the structural limitations of traditional screeners through behavioral consistency analysis, profile-based matching, and fraud pattern detection.
EdTech products serve two audiences whose needs often conflict: teachers who deliver instruction and students who receive it. This guide covers research methods, recruitment, and frameworks for education product teams.
The pitch for synthetic users is appealing: instant research subjects, any profile, no scheduling required. The problem is that the answers are not real. They are statistically plausible text generated by a language model, not observations of actual human behavior.
Most A/B tests fail because of poor planning, not poor execution. This template provides a step-by-step framework for structuring experiments that produce statistically valid, actionable results.
A research panel is a pre-recruited pool of individuals who have agreed to participate in research studies when invited. Panel members have provided profile information and consented to be contacted for research opportunities.