You did the research. Now answer the question.
A real study can still leave the team without the cut, scenario, or sample depth the decision needs. Simulacra fits the response structure of measured survey, sensory, behavioral, or sales data, then generates the cuts and scenarios the original study could not support, inside the same schema.
Brand trackers / FMCG, pharma, beverage
The brand tracker came in short on Gen Z switchers.
Stabilize underpowered cohorts without re-fielding.
Pricing & promotion / FMCG, weekly POS
Need price–volume curves before the committee meets.
do(price = x) scenarios on your existing pricing data.
Concept testing / priority cohorts, competitive contexts
Concept won overall. The priority cohort was n=38.
Stress-test winners under different cohorts and competitive contexts.
Segmentation / U&A, sub-cohort reads
U&A is fine in total. The cuts the team wants are not.
Expand measured segments without breaking the relationships that define them.
Hard-to-reach research / pharma, finserv, B2B
The audience is valuable. The sample is small.
Extend small high-quality samples: HCPs, executives, niche B2B.
Agency white-label / headless API
Client wants AI capability. Their data-science team wants validation papers.
Headless API for validated synthetic data.
If the study is tabular and the variables are measured, we can generate it.
Trackers, U&A, segmentation, conjoint, MaxDiff, concept tests, ad tests, pack tests, claim tests, behavioral data, sales data, loyalty data, and more. Tell us the scenario; we'll tell you whether Simulacra can model it.