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New AI system tracks e-commerce competition via "Agentic Share-of-Search"

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a multi-agent AI system called Agentic Share-of-Search (ASoS) designed to help e-commerce sellers monitor and understand their competitive landscape in the era of AI shopping assistants. The system uses query agents to gather data from various AI platforms and a diagnostic agent to identify root causes for changes in visibility. A feasibility study involving 100 trials indicated that the system could successfully recover ablated signals in a significant portion of cases, suggesting its potential for competitive decision-making. AI

IMPACT This system could provide e-commerce sellers with crucial insights into competitive dynamics driven by AI shopping assistants.

RANK_REASON The cluster contains a research paper detailing a novel AI system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AI system tracks e-commerce competition via "Agentic Share-of-Search"

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2 / 100
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The cluster contains a research paper detailing a novel AI system and its evaluation. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Spandan Ghose Chowdhury ·

    Agentic Share-of-Search: A Multi-Agent AI System for Competitive Decision-Making in LLM-Mediated E-Commerce

    AI shopping assistants increasingly redirect consumer discovery, creating an urgent need for tools that support seller-side competitive decision-making. We present a multi-agent AI system that automates competitive visibility measurement and root cause diagnosis in LLM-mediated e…

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