Market Shares under Delegation
Model heterogeneity drives different product shares; demand can concentrate.
Research Highlights
How ACES - Agentic e‑CommercE Simulator- Works
It starts with a simple prompt. We provide an AI agent with a shopping task, like "find the best fitness watch".
AI Model Preferences Analysis
AI Model Preferences: Fitness Watches
See how different AI shopping agents choose completely different products
🟠 Claude Sonnet 4 strongly prefers Fitbit Inspire (45.2%)
Fitbit Inspire 3
$79.95
👑
Fitbit Versa 4
$149.95
Garmin Forerunner 55
$166.40
Garmin vívoactive 5
$220.89
Smart Watch (Generic 1)
$24.99
Smart Watch (Generic 2)
$29.99
WHOOP 5.0
$359.00
Generic Fitness Tracker
$28.99
Performance Heatmap Analysis
Webpage Heatmap of AI Shopping Agents
Selection rate of the same product across different positions for three AI agents.
Position 1
11.5%
Position 2
27.0%
Position 3
23.4%
Position 4
15.4%
Position 5
3.4%
Position 6
7.9%
Position 7
6.9%
Position 8
4.5%
Key Research Takeaways
Key Takeaways
Agentic e-Commerce: Market Shares, Platform Levers, Seller Strategy
Platform Levers and Position Effects
Strong top-row bias; rankings, promotions, and sponsorships affect models differently.
Seller-Side Listing Agents Move Share
Minor, model-targeted listing edits can materially shift market share.
Team
Citation
@article{allouah2025aces,
title={What is your AI Agent buying? Evaluation, Implications and Emerging Questions for Agentic e-Commerce},
author={Allouah, Amine and Besbes, Omar and Figueroa, Josué D and Kanoria, Yash and Kumar, Akshit},
journal={arXiv preprint arXiv:2508.02630},
year={2025}
}