Our synthetic audience methodology, in the open.
Replism pressure-tests a decision against a synthetic audience in hours, not the weeks a panel takes. Every study ships with the methodology behind it: the cohort, the sample, the distributions, and the crosstabs. The platform itself is validated in the open against a public benchmark, so when someone asks how you know, the answer holds.
What synthetic audience methodology means here.
A synthetic audience methodology is the documented process for building, sampling, and validating AI populations against real human data. It is what separates a grounded synthetic audience from a model told to play a role. Replism grounds personas in real data, samples a defined cohort for each study, and benchmarks the answers against human panels. Every step is written down. Every claim traces back to a source.
The three artifacts we ship with every study.
A synthetic data research methodology is only as good as what it leaves behind. We leave three artifacts behind, the same ones a research firm hands a client.
Cohort definitions.
We define each cohort the way a research firm writes a screener: by demographic, geographic, attitudinal, and behavioral frame. Nothing comes from a stock library. The population you test is the one you defined.
Sample sizes.
Every study reports how many personas were drawn, and from which frame. A result without a sample size is an opinion. We do not ship opinions.
Response distributions.
You get the full distribution and crosstabs across cohort segments, not a single headline number. Distributions show where a result holds and where it splits. That split is where most decisions are made.
Public eval reports, on a quarterly cadence.
A synthetic audience quarterly eval report is a public benchmark comparing synthetic responses to human panels, published in the open. It is the public record of how closely Replism tracks real human behavior, the kind of proof a board or a war room can lean on.
Most vendors will not show you their synthetic audience accuracy against a known benchmark. We publish ours. The first report is live now, and a new one follows each quarter. A one-time number can be cherry-picked. A public record, updated on a fixed cadence, cannot.
Our first report replicates a Pew American Trends Panel study, Wave 163. Against it, Replism reached 93.6% accuracy versus human self-replication, close to the limit of how consistently real people even agree with themselves. That is the bar that matters, and we publish exactly how we hit it.
Replism Evaluation Report
Pew American Trends Panel, Wave 163
First report published Q2 2026. A new report follows each quarter.
Strongest where the stakes are highest.
A synthetic audience is the fastest way to pressure-test a decision at scale. Here is where it is sharpest, and where the smart move is to pair it with fieldwork.
- Built for scale. A synthetic audience pressure-tests messaging, pricing, and positioning across a full population in hours, at a volume no panel can match. For the unscripted moment in a focus group, pair it with qualitative work.
- Sharpest where the data is rich. The more grounded a cohort, the sharper the read. We tell you up front where coverage runs deep, so you know exactly how much weight a result can carry.
- Tuned to the human ceiling. We calibrate to how consistently real people match their own answers, not to a vanity 100%. That discipline is why the number holds up when someone checks it.
- Fast first, confirmed when it counts. For questions moving faster than any dataset, run a synthetic audience to set direction in hours, then confirm the highest-stakes calls with fresh fieldwork.
Questions about the methodology.
Reference: Replism evaluation against Pew ATP Wave 163 (PDF).
Put it to work on a decision that matters.
Define a cohort, ask it a real question, and walk into the room with the methodology behind every answer.