SynthCrowd simulates how real segments of 50 national populations respond to your ideas. Calibrated AI personas, each defined by nearly two thousand demographic, psychological and behavioural attributes, evaluate concepts, creative, products and policy, and explain the reasoning behind every judgement.
From a first idea to a board-ready conclusion: quantitative prediction across the whole sample, qualitative depth where it matters, and the context of each market built in.
Every persona in a stratified sample receives a score and an intent probability, with confidence intervals and low-base flags.
Verbatims, inner monologue and stated reasoning from a subsample that answers from its full profile.
Heatmaps by generation, settlement, income, party and psychographics, with a written explanation for any segment.
Variance explained by each dimension and the psychological traits that correlate with acceptance.
Attitudes, trust, concerns, media and retail in percentages for each market, to see where a product will struggle before launch.
A dated briefing per market on prices, mood and news, refreshed by SC AI and read by every respondent.
Responses are archived and returned to each persona as memory, so attitudes evolve consistently across studies.
An AI moderator runs discussions in which personas argue and change their minds; any persona can be interviewed one to one.
Feed reactions and comments from the personas who actually use Instagram, TikTok, Facebook, X or YouTube.
Copy, concepts, slogans, product names, prices and images: automotive and furniture design, packaging, policy, apps.
Define the sample by demographics, region, party, generation or platform use, then compare variants on identical people.
A written report with recommendations and an optimised version, plus CSV exports of every score and verbatim.
Each dot is a persona, placed by social and economic views and coloured by party. Select a dot to open the full profile.
Every persona carries a latent psychometric vector from which all other attributes are derived with fixed, published loadings. Attributes are correlated the way they are in people, reproducible on every read and traceable to their drivers.
A live persona drawn from the population. Each has a personality profile, health and fitness, fears and aspirations, tastes, media diet and a response history.
Any stimulus that a person can read or see. Categories are open: the stimulus is analysed and mapped onto the persona model at the start of each study.
Demand, feature appeal and purchase intent by segment, before development budgets are committed.
Compare headlines, claims and executions on the same sample; see which audiences each variant wins and loses.
Automotive, furniture and packaging concepts from text or images, read against aesthetic preferences and brand affinities.
Price variants tested against income, price consciousness, deal proneness and willingness to pay.
Support and mobilisation by electorate, generation and region, with the values that drive each reaction.
Anticipate how employees, customers and the public interpret announcements before they are published.
A study combines a deterministic predictive model over the full sample with a qualitative subsample that articulates its reasoning.
The same persona returns the same attributes on every read; sampling is seeded per study.
Every score decomposes into the variables, affinities and traits that produced it.
Confidence intervals, low-base flags and model-to-response agreement on every result.
Responses are archived and returned to the persona as memory, keeping opinions consistent over time.
Distributions follow census, survey and polling structure for each market. Shown for the United States.
Create a study in minutes; results arrive while the brief is still fresh.
SynthCrowd