Applying Large Language Models to Sponsored Search Advertising

This paper presents a human-in-the-loop LLM framework that boosts search engine ad performance and explores cost trade-offs and boundary conditions.

Authors

David A. Schweidel (ORCID: https://orcid.org/0000-0003-2665-3272)
Thomas Reutterer (ORCID: https://orcid.org/0000-0003-1276-8239)
Martin Reisenbichler (ORCID: https://orcid.org/0009-0007-0128-9685)

Institutions

Vienna University of Economics and Business (AT)
Emory University (US)

Publication Details

Journal: Marketing Science
Published: 2025-11-03
DOI: https://doi.org/10.1287/mksc.2023.0611
Primary Topic: Consumer Market Behavior and Pricing
Type: article
Field-Weighted Citation Impact: 0.00

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article

Applying Large Language Models to Sponsored Search Advertising

David A. Schweidel, Thomas Reutterer, Martin Reisenbichler

Nov 3, 2025

Marketing Science

Consumer Market Behavior and Pricing

article

Applying Large Language Models to Sponsored Search Advertising

David A. Schweidel, Thomas Reutterer, Martin Reisenbichler

November 3, 2025article en

Abstract

This paper presents a human-in-the-loop LLM framework that boosts search engine ad performance and explores cost trade-offs and boundary conditions.

Marketing ScienceVol. 45(1)

Vienna University of Economics and Business (AT), Emory University (US)

Openalex Percentile: Top 58%

Consumer Market Behavior and Pricing

DOI Source OpenAlex

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Applying Large Language Models to Sponsored Search Advertising — David A. Schweidel, Thomas Reutterer, et al. · Marketing Science (2025) | TGRS Research Map | TGRS