Insights on expert networks, market research, UX research, and AI training from the CleverX team.
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.
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.
Analyzing user interviews manually is one of the most time-intensive operations in qualitative research. AI interview analysis tools have changed this economics substantially: transcription that would take hours takes minutes, and initial theme identification that would take a day surfaces within an hour of session completion.
Continuous discovery builds customer contact into the routine work of the product team itself, weekly interviews, structured synthesis, and assumption testing: so that product decisions are grounded in current evidence rather than the memory of the last research project.
Research operations, commonly called ResearchOps or ReOps, is the discipline focused on the infrastructure, processes, systems, and governance that enable user research programs to operate effectively at scale.
Participant recruitment is the process of finding, screening, scheduling, and managing the people who take part in user research studies. It is one of the most foundational operational functions in any research program.
Evaluative research assesses how well a product, design, or concept performs against user needs. It requires something concrete to test: a prototype, a live product, or a concept, and answers whether that thing works for real users.
Generative research discovers what to build before design begins. It explores user needs, behaviors, and mental models to replace assumptions with direct evidence before those assumptions get baked into design and engineering decisions.
Hiring a UX researcher requires five things done well: defining the specific role before writing the job description, attracting candidates through channels where researchers actually look for work, interviewing for research thinking rather than tool familiarity, evaluating portfolios for insight quality rather than deliverable polish, and ensuring the organizational conditions exist for a researcher to have genuine impact.
No single method answers every research question. Understanding the full range of user research methods: generative and evaluative, qualitative and quantitative, attitudinal and ? behavioral: is what allows research programs to match the right approach to each question rather than defaulting to the most familiar method.