Synthetic Audience
Synthetic Audience
A virtual panel that mirrors your target market, ready to react to any concept, message, or creative you put in front of it.
In short
A synthetic audience is a panel of AI-generated individuals that mirror a real target market, so you can test concepts, messages, and creative in hours instead of weeks. It is a group of synthetic individuals, calibrated to answer the way the real market would.
What teams use a synthetic audience for
Concept testing
Screen dozens of ideas across a market and back only the ones that land, before you commit budget.
Message and positioning
See which framing wins with which segment, and why, in a single afternoon.
Creative and ad pre-testing
Score ads, emails, and posts before launch, with no media spend.
Learn morePricing and packaging
Read willingness to pay and plan preference across segments in parallel.
Cross-market validation
Pressure-test one idea across countries and segments at the same time.
Synthetic audience vs traditional methods
| Synthetic audience | Focus group | Online panel | |
|---|---|---|---|
| Speed | Hours | Weeks | Days |
| Cost per study | Low | High | Medium |
| Scale | Unlimited | 6 to 10 people | Hundreds |
| Repeatable | Yes, instantly | No | Costly |
| Reach | Any market or segment | Local recruits | Panel-limited |
| Accuracy check | Public benchmark | Is the benchmark | Sampling noise |
How iMario builds your audience
You describe the market you care about in plain language. iMario builds a panel of synthetic individuals that mirror it, anchored to real demographic and sociological data so the composition matches the real population rather than a stereotype.
You control the demographics and segments, run your stimulus, and read the reaction the same afternoon. A calibration layer corrects the answers toward the distributions real people produce, and every audience is repeatable at any sample size.
- Real-data anchored audiences, not prompt-only guesses
- Full demographic and segment control
- Calibrated toward real answer distributions
- Repeatable and comparable at any sample size
How accurate is a synthetic audience
On the public iMario accuracy benchmark, synthetic audiences match real survey answer distributions to about 89% across 11 populations and more than 900 questions from Pew Global Attitudes, ANES, CGSS, and the Stack Overflow Developer Survey. Rerunning a real survey on a fresh sample of people only agrees with itself about 93% of the time, so a well-anchored synthetic audience sits close to the noise floor of real fieldwork.
Accuracy is highest where there is relevant real data to anchor and calibrate against. The honest pattern is to iterate fast with a synthetic audience, then validate the few finalists with a small real study for the highest-stakes calls.
What a synthetic audience read looks like
A synthetic audience returns the same shape of result a real study would: a distribution, not a single opinion. Ask which of two value propositions lands and you get a split, say 62 to 38, broken out by segment, so you can see that one message wins with enterprise buyers while the other wins with small teams.
Because the run is repeatable, you can add a third option, change the wording, or swap the segment and compare the reads side by side in minutes. That is what turns a synthetic audience from a novelty into a decision tool: you act on the split, and you know which segments to double-check with real people.