Maria I. Nezgovorova
Synthetic respondents are progressively shifting from an experimental technique to a routine instrument in social and marketing research. This article examines this transition and delineates the methodological risks, conditions of applicability, and data-verification standards that define emerging research pipelines. It is shown that synthetic approaches can accelerate exploratory phases, broaden the range of qualitative analysis, and enable statistically controlled reconstruction and augmentation of quantitative datasets; simultaneously, they intensify epistemic constraints arising from dependence on data sources, profile variability, research-question formulation, and validation procedures. The paper proposes a coherent typology of six types of synthetic respondents and explicates the transition logic among them, from conversational personas to simulations of group dynamics, survey reconstruction, multimodal interpretation of stimuli, and the construction of “digital twins.” It concludes that industry practices (Ipsos; Livepanel) and developer solutions (Yabble; Synthetic Users; Lakmoos), together with academic experiments (including Stanford studies on generative agents), are converging on a shared language of validation and articulated limitations. Russian cases further indicate that institutional uptake is strongest in UX and product research as an accelerator of exploratory work and hypothesis formulation, whereas within the quantitative infrastructure of OMI/Livepanel the emphasis shifts toward “augmented synthetic respondents” and machine-based survey imputation, supporting scalable use of large survey datasets and statistically controlled enrichment of complex target audiences with high accuracy and measurement reproducibility.