Insights on expert networks, market research, UX research, and AI training from the CleverX team.
Struggling to find users for research? Learn 15+ proven methods to recruit high-quality participants for user interviews, usability tests, and product research studies.
UX designers can conduct moderated testing, five-second tests, preference tests, and card sorting independently. Here's how to integrate research into your design process.
Real estate transactions are among the highest-stakes decisions people make, yet many PropTech products are designed with minimal user research. This guide covers methods, recruitment, and frameworks for PropTech UX teams.
Social media apps are shaped by algorithms, network effects, and user psychology. This guide covers research methods, participant recruitment, and frameworks for testing social platforms effectively.
Learn how to conduct user research for fitness and health apps. Covers workout tracking testing, habit formation research, wearable integration, and recruiting active fitness app users.
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.
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.
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.
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.
User research has always been constrained by analyst time. AI research assistant tools handle meaningful portions of the mechanical work within each research phase, freeing researchers to spend more time on the judgment-intensive work that determines research quality.