arXiv AI September 25, 2026 By Yuting Deng, Jingxuan Liu, Olivier Toubia, Naman Jain

AI-Moderated Interviews for Market Research and Digital Twins Calibration

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.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI

Jun 4

Synthetic Personalities: How Well Can LLMs Mimic Individual Respondents Using Socio-Economic Microdata?

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

llms rag

arXiv AI

Sep 15

Synthetic Data in Marketing Research: How to Evaluate and When to Trust

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By Oded Netzer, Rajan Sambandam

llms rag

arXiv AI

Sep 10

When Can LLM Digital Twins Reduce Human Measurement? From Behavioral Fidelity to Statistical Substitutability

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By Steven Wang, Kyle Hunt, Shaojie Tang, Kenneth Joseph

llms

arXiv AI

Aug 7

Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

arXiv:2603. 00059v3 Announce Type: replace-cross Abstract: How well can AI-derived synthetic research data replicate the responses of human participants?

By Jason Miklian, Kristian Hoelscher, John E. Katsos

llms agents

arXiv AI

Jun 29

Psychometric Comparability of LLM-Based Digital Twins

arXiv:2601. 14264v2 Announce Type: replace-cross Abstract: Large language models (LLMs) act as digital twins for human respondents, yet their psychometric comparability remains uncertain.

By Yufei Zhang, Zhihao Ma

llms benchmarks safety

arXiv Computation and Language

Aug 24

Beyond Raw Transcripts: Structured Persona Extraction for LLM-Based Digital Twins

arXiv:2608.20344v1 Announce Type: new Abstract: LLM-based "digital twins" aim to simulate how an individual would behavein new environments or respond to novel questions, given some representation of...

By Iris Ye, Tianze Deng, Ozan Candogan

llms benchmarks

One email a morning, machine-written

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Synthetic Data in Marketing Research: How to Evaluate and When to Trust

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