SAMPLE AUGMENTATION
Boost: Synthetic expansion of existing survey samples for deeper subgroup analysis. Twins: Simulated respondents from partner audiences or your own quantitative and qualitative research.
PRODUCT PROFILE
Fairgen documents two related offers: Boost, which augments small survey segments using patterns in an existing survey, and Twins, which makes modeled respondent audiences available for structured studies and follow-up conversation. Its public material distinguishes early directional work from statistically confident field research.
Information from the company's product materials.
Boost is designed to generate augmented respondents for underrepresented or hard-to-reach segments from an existing survey structure.
Fairgen documents both survey-data augmentation and digital-twin audiences for structured studies, reports and follow-up conversations.
Fairgen Boost: AI Synthetic Respondents · Fairgen Twins: product and FAQs
Fairgen states that Twins is intended for decisions before a larger study and is not a replacement for field studies or decisions requiring statistical confidence.
Boost is offered through a supplier conversation. Twins also supports a marketplace and private audiences built from a customer or agency dataset.
Fairgen Boost: AI Synthetic Respondents · Fairgen Twins: product and FAQs
Methods described by the company.
Fairgen says Boost uses patterns in an existing survey to generate augmented respondents that follow the survey structure, including logic such as skips, piping and multi-selects.
The Twins workflow documents structured questions across multiple digital twins, quantitative and qualitative outputs in a report, and subsequent chat with an individual twin.
Data and settings the company says teams can choose.
Fairgen says Boost is trained on a general-audience survey and generates augmented results from the patterns in that data, without external data sources.
For a private audience, Fairgen asks for a core respondent-level quantitative dataset and says interview transcripts, segmentation decks and analysis documents can add qualitative and segment context.
Results reported by the company, with details about how they were tested.
Fairgen reports a pilot using Boost with real brand-lift survey data processed through Google's Ads Data Hub. The supplier says the pilot covered 52 study cuts across five industry verticals and examined recoverable statistical precision through augmentation.
This is Fairgen's own account of a specific pilot. It should be read as a scoped augmentation study, not as a general guarantee for all questionnaires, segments or model configurations.
Fairgen's public material says generative synthetic respondents can support early ideation and exploration but are not a substitute for statistical inference. Its Twins documentation directs decisions needing statistical confidence to fieldwork.
Fairgen: Google synthetic-data pilot summary · Fairgen Twins: product and FAQs
Fairgen says Twins cannot model an audience when it has no relevant market audience or original research data. The company says more relevant data can improve its answers.
Lists synthetic sample generation among its research technologies.
Generates synthetic survey responses, augments existing datasets and supports private panels, with respondent-level exports for analysis.
HarmonAIze Boost: Post-fieldwork synthetic augmentation for smaller or hard-to-reach survey groups. Synthetic Personas: Synthetic survey-taking personas for screening claims, ideas, flavors and brand messages.
