Research

My research focuses on how AI and large language models are reshaping consumer product discovery, brand visibility, and marketing communication. I combine empirical methods with applied marketing strategy to study how digital intermediaries influence consumer consideration sets and brand outcomes.

Research Interests
AI-Mediated Communication LLM Optimization (LLMO) Consumer-Brand Relationships Customer Analytics Marketing Communication Digital Intermediaries Retail Technology
Papers
Under Review

"The Fragmented Shelf: How Large Language Models Create Divergent Brand Visibility"

Gale, John C. and Cian, Luca
Journal of Marketing
Examines how large language models produce divergent brand visibility across platforms, providing new evidence on AI-mediated consumer discovery and its implications for marketing strategy and retail brand positioning.
Working Paper

"LLMO for Retail: How Large Language Models Shape Product Discovery and Brand Visibility"

Gale, John C.
Explores how large language models influence product discovery in retail contexts, with implications for brand positioning and marketing strategy.
In Preparation

AI-Mediated Product Discovery (Practitioner Article)

Gale, John C., Cian, Luca, and Wathieu, Luc
Target: Harvard Business Review
Grants & Funding

NRF Business of Retail Initiative Research Grant

$2,600

Georgetown University, McDonough School of Business (2026)
Project: "LLMO for Retail" — Selected under "Retail Resilience" theme

Conference Presentations
Jun 2026 "Large Language Model Optimization for Consumer Discovery." Frontiers in Service Conference, CERS Helsinki (Invited).
Apr 2026 INFORMS Marketing & Data Science Panel, National Harbor (Panelist).