Guides and research notes on synthetic users, AI personas and faster user research.
Use AI to inspect advertising concepts without mistaking generated ratings for effectiveness. Test comprehension, brand recognition and real outcomes separately.
Understand what AI focus groups actually contain, when group interaction matters and how to use simulated interviews to prepare better human research.
Compare AI research tools by their data, methods and limits. A practical selection guide for human interviews, survey analysis and synthetic respondents.
Evaluate AI personas by their evidence, audience coverage and intended use. A practical guide to separating customer facts from generated assumptions.
Separate three uses of AI in surveys. Learn what to check in a tool, how to pilot a questionnaire and why generated answers do not measure a market.
Build a concept test around comprehension, relevance and objections. Original question examples, a worked brief and limits for synthetic responses.
Choose concept testing tools for comprehension, comparison and behavioural validation. A decision matrix, evaluation checklist and worked example.
An adaptable brief for synthetic research: define the decision, audience, evidence, questions and human follow-up without embedding the desired answer.
A practical validation protocol: define the target, hold out human answers, compare baselines and separate model stability from predictive accuracy.
Choose synthetic survey runs by their purpose. Understand model variation, systematic error and why generated sample size is not a human margin of error.
AI market research runs from AI analysis of human data to fully synthetic respondents. What each approach replaces, what it costs, and where it breaks.
Synthetic user research is dependable for some questions and misleading for others. What the evidence shows, where critics are right, how to test it.
Synthetic personas are AI respondents built from real survey data. What they are, how they are built, where they fail, and how to tell a good one from a plausible one.
Synthetic users are AI-simulated research participants. What they are, how they are generated, where they hold up, and the questions you should never ask them.
