Studio

Companies in categories like consumer packaged goods, quick service restaurants, streaming, and retail need to choose between many versions of a decision, a price, a shelf placement, a promotion, a launch timing, a cancellation flow, but can normally only test a handful in the real world before committing. Surveys capture what people say they would do, not what they actually do, and a single real-world rollout risks revenue and shelf space on a guess. The page frames this as choosing one version of a launch without knowing how the other eleven would have performed.

Studio ingests public signals (social chatter, reviews, census data) and a client's own data (point of sale, loyalty, CRM, app events) and uses it to build a 'society model': cohorts of a market (named things like loyal regulars, deal-triggered, switchers, adopters, skeptics) with modeled influence between them, built from 200 million modeled consumers and 300+ cohorts per society. It then runs a proposed decision, such as a price point, promotion, or store placement, through multiple parallel versions of this society and reports behavioral outcomes (adoption, trust, repeat rate, revenue lift) rather than stated preferences, so a team can compare versions before choosing one to execute. The site states runs take 30+ weeks of simulated time, claims repeatable results for the same inputs, and states data is PII-scrubbed at ingestion and isolated per tenant.