Synthetic Research
Synthetic Research
Deep, AI-moderated interviews with synthetic individuals. Directional insight in hours, not weeks.
In short
Synthetic research uses AI-moderated interviews with synthetic individuals to produce qualitative and quantitative signal in hours, without recruiting real participants. The individuals are anchored to real data and calibrated, so the answers track how a real population would respond.
What you can run
Deep interviews at scale
Run hundreds of in-depth, AI-moderated conversations in parallel and code the themes automatically.
Concept and message tests
Put an idea or a framing in front of a segment and hear the reaction in its own words.
Onboarding and flow validation
Catch confusion in a product journey before you ship it, not after.
Reach hard-to-access audiences
Talk to niche professionals and international segments that are slow or expensive to recruit.
Synthetic research vs traditional research
| Synthetic research | Traditional research | |
|---|---|---|
| Time to insight | Hours | Weeks |
| Cost per study | Low | High |
| Iterations | Unlimited | One or two |
| Reach | Any segment | Recruitment-limited |
| Sample size | Any | Small |
How a synthetic study runs
Describe the audience and the questions
iMario builds a calibrated panel of synthetic individuals
An AI moderator runs the interviews in parallel
Read the coded themes and the answer distribution
Accuracy and validity
iMario calibrates to real-world data and is honest about the limits. On the public accuracy benchmark, synthetic answers match real survey distributions to about 89% on quantitative questions, and the open-ended, coded-theme results are scored against real human answers too. Rerunning a real survey on fresh people agrees with itself only about 93% of the time, which is the ceiling any method is measured against.
Synthetic research augments human research, it does not blindly replace it. The point of anchoring and calibration is to know where the synthetic signal is trustworthy and where a small human study is still worth running.
Qualitative and quantitative in one run
A synthetic study gives you both layers at once. The AI moderator runs open-ended interviews so you get verbatims and themes in the participants own words, and the same population produces a distribution you can quantify, so you see how common each theme is rather than guessing from a handful of quotes.
Every open-ended answer is coded to a consistent scheme automatically, which is the slow, expensive part of real qualitative research. You end a study with the story and the numbers behind it, ready to act on or to sharpen before a human study.
- Verbatims and themes, coded automatically
- A distribution behind every theme, not just quotes
- Unlimited follow-ups and reruns
- Both layers from one calibrated population