Synthetic Respondents

Synthetic respondents. Grounded in your research.

Generate synthetic respondents from your own research and run studies with them. Explore follow-up questions and refine concepts before your next round of human interviews.

Start a Study See how it works
  • Grounded in your research
  • Run synthetic studies
  • Validate with real people
TL;DR

Synthetic respondents are AI-generated participants used to simulate answers to research questions. Grounded in teams’ own research, User Intuition’s synthetic respondents can run exploratory studies, giving existing customer evidence another use between live research waves. In-house teams can explore follow-up questions before recruiting again; agencies can refine a client brief or narrow concepts using research they are authorized to reuse. Grounding provides context that a demographic persona alone cannot, but it does not turn a simulation into a real customer or guarantee accurate predictions. Treat synthetic results as exploratory evidence: identify promising questions, inspect the assumptions behind the output, and validate consequential conclusions with fresh human interviews. Keep synthetic outputs clearly labeled and separate from human findings in client reporting. When you need new evidence, use your own audience, supported external panels, or User Intuition recruitment. Start with relevant source research and a bounded question, not a claim that simulated answers represent an entire market.

The Workflow

From existing research to a better next question.

Use simulation to focus your exploration. Use human research to establish what customers actually think.

01

Start with your research

Choose research relevant to the audience and question. Check that you have permission to reuse it, and note where the source evidence is incomplete or out of date.

02

Generate respondents

Create synthetic respondents from your own research in User Intuition. Ground the exploration in what people actually shared, not only a demographic persona.

03

Run a synthetic study

Explore follow-up questions, narrow concepts, or refine a client brief. Treat the answers as modeled outputs and look for questions worth investigating.

04

Validate with real people

Test consequential conclusions with fresh human interviews. Keep synthetic outputs distinct from human evidence, including in client deliverables.

Who It's For

Keep learning between live studies.

01

Product and insights teams

A new question arrives after the study has closed. Explore it using existing research, then focus the next round of customer interviews on what still needs evidence.

02

Research agencies

A client wants to explore more directions before fieldwork. Use authorized research to refine the brief, label simulated outputs, and keep your recommendation grounded in validated evidence.

03

Ongoing research programs

Use synthetic exploration between human research waves to identify follow-up questions. Bring in fresh interviews to evaluate whether customer needs or behavior have actually changed.

The Evidence

Grounding matters. It is not an accuracy guarantee.

In our preregistered synthetic-user fidelity study, we compared conditioning methods using 53 panel members, 265 held-out question–answer pairs, and 1,625 predictions. Demographic-only respondents recovered 19% of the distance between a stranger baseline and the full-interview ceiling. Real interview content closed 81% of the remaining fidelity gap.

That is a relative fidelity result within this study—not 81% accuracy, a market-representativeness claim, or a guarantee for your research. The evaluation used model judges and a bounded sample. Read the methods, uncertainty, and unsupported hypothesis alongside the headline findings.

Our earlier Synthetic Mirage study compared 117 real interviews with 90 persona-prompted synthetic interviews. It found missing dissent and lived detail in that setup. It did not test every synthetic-research method. Together, these studies support a practical distinction: research-grounded exploration is different from inventing a persona, and neither replaces fresh human validation.

Explore now. Validate what matters.

Start with a bounded question and research you are authorized to use. For client work, agree how synthetic outputs will be labeled and which conclusions require human validation.

Start a Study Read the decision guide

Building a model and need a commissioned grounding corpus? Explore human preference data. Delivering client studies? See research for agencies.

Team

Who's running this.

User Intuition runs a self-serve research SaaS used by product, customer-experience, and insights teams to commission AI-moderated voice interviews and the structured outputs derived from them. The same platform infrastructure — including the User Intuition MCP server, our connection for agents to commission research and retrieve participant evidence — produces the human preference datasets described here.

The team is led by the founder and CEO (Harvard MBA, BS Electrical Engineering, Yale), and the broader User Intuition Research Team — the methodologists, engineers, and panel operators who design protocols, build the ontology, and run the studies.

Methodology, infrastructure, and team have produced tens of thousands of structured human-cognition interviews across consumer and professional domains since the platform was built.

FAQ

Synthetic respondent questions, answered.

Synthetic respondents are AI-generated participants that simulate answers to research questions. User Intuition lets you generate them from your own research and run studies with them. Their answers are modeled outputs, not new testimony from real customers.

Yes. You can generate synthetic respondents from your own research, then run studies with them in User Intuition. Start with research relevant to the audience and decision you want to explore. Use only source material you have permission to use.

Use them to explore follow-up questions, refine hypotheses, or narrow concepts before recruiting real participants. They are useful for deciding what to investigate next; they do not establish what a market currently believes or how customers will behave.

Yes. Agencies can generate respondents from research they are authorized to use and run synthetic studies to explore a client brief. Label outputs as synthetic, explain the source research and limitations, and validate consequential recommendations with real participants.

No. Grounding adds context, but a simulation can still miss changing behavior, minority views, and experiences absent from the source research. Use real interviews to investigate unfamiliar audiences and validate decisions with meaningful commercial consequences.

Accuracy depends on the source research, audience, task, and validation method. No single benchmark guarantees accuracy for your study. Compare predictions with held-out human evidence relevant to your decision, and report disagreements as well as agreement.

Yes. Run a separate human study using your own audience, User Intuition recruitment, or supported third-party panels: Prolific, Cint / Lucid, and CloudResearch. Keep human findings and synthetic outputs distinct when interpreting the evidence.

Yes, as an exploratory input. Use synthetic studies to surface questions between human research waves, then test them with fresh interviews. A repeated simulation is not fresh customer evidence and cannot establish that customer opinions have changed.