arXiv:2606. 04592v1 Announce Type: cross Abstract: LLM-based digital twins promise to scale and accelerate market research, but most published twins are either coarse persona bots conditioned on a few demographic questions or detailed individual-level twins built on purpose-collected surveys and interview transcripts.
By Leonard Kinzinger, Jochen Hartmann
AI‑moderated interviews are a scalable market‑research method that can match human moderation in depth, cover more themes, and recover more customer needs while keeping budgets constant. Participants, however, feel more emotionally engaged with live humans. Digital twins built from AI‑moderated data predict consumer responses better than demographics‑only personas, but the added richness does not improve quantitative predictions over static interviews, and prediction errors stem from differences in thinking styles and data‑distribution gaps.
By Yuting Deng, Jingxuan Liu, Olivier Toubia, Naman Jain
SYN-DIGITS is a model‑agnostic, post‑hoc calibration framework that uses relationships learned from digital twin simulations to predict human responses, especially in cold‑start scenarios where no target question data is available. It transfers these relationships to improve individual‑level correlation and distributional predictions, even when only marginal reference data is available. Experiments on three datasets and thirteen persona constructions show significant gains—up to 417% improvement in correlation and 57% reduction in distributional error—over uncalibrated baselines.
By Grace Jiarui Fan, Chengpiao Huang, Tianyi Peng, Kaizheng Wang, Yuhang Wu
arXiv:2607. 26348v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market decisions.
By Zihan Chen, Di Zhu, Lei Nico Zheng
arXiv:2609.07987v1 Announce Type: new
Abstract: LLM-based digital twins promise to reduce repeated human data collection by generating person- specific responses, yet existing evaluations provide lit...
By Steven Wang, Kyle Hunt, Shaojie Tang, Kenneth Joseph
arXiv:2609.13148v1 Announce Type: cross
Abstract: Large language models are increasingly deployed as synthetic consumer panels, promising $97\%$ cost reductions over traditional surveys. Yet aggregat...
By Robson Tigre, Hugo Gobato Souto