Large Language Models for Market Research: A Data-Augmentation Approach

This paper proposes a statistical data augmentation approach that efficiently integrates LLM-generated data with real data in conjoint analysis.

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Publication Details

Journal
Marketing Science
Published
2026-03-17
DOI
https://doi.org/10.1287/mksc.2025.0009
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00
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article

Large Language Models for Market Research: A Data-Augmentation Approach

Mengxin Wang, Dennis Zhang, Heng Zhang
Marketing Science
Sentiment Analysis and Opinion Mining
article

Large Language Models for Market Research: A Data-Augmentation Approach

Mengxin Wang, Dennis Zhang, Heng Zhang
article en

Abstract

This paper proposes a statistical data augmentation approach that efficiently integrates LLM-generated data with real data in conjoint analysis.

Marketing Science
The University of Texas at Dallas (US), Washington University in St. Louis (US), Arizona State University (US)
Openalex Percentile: Top 22%
Sentiment Analysis and Opinion Mining
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Large Language Models for Market Research: A Data-Augmentation Approach — Mengxin Wang, Dennis Zhang, et al. · Marketing Science (2026) | TGRS Research Map | TGRS