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AI assistants' purchase influence hard to measure, study finds

By PulseAugur Editorial · [1 sources] ·

A new paper from arXiv analyzes 317 AI conversations to understand how often generative assistants influence purchasing decisions. The study found that while AI assistants frequently offer recommendations or conditional preferences, it is difficult to observe subsequent buyer responses. Out of 67 analyzed purchase-related interactions, only 18 included a user follow-up message, and none explicitly stated a purchase commitment, completion, or abandonment. The research highlights a measurement limitation in current AI conversation logs, where recommendation content is more readily available than transaction outcomes. AI

IMPACT Highlights limitations in measuring AI's influence on consumer behavior, suggesting a need for better data collection on user decisions post-recommendation.

RANK_REASON Research paper published on arXiv detailing findings about AI conversations. [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 →

AI assistants' purchase influence hard to measure, study finds

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Research paper published on arXiv detailing findings about AI conversations. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Benjamin Tannenbaum ·

    Purchase Advice and Observable Buyer Responses in Real AI Conversations

    How often does a generative assistant persuade someone to buy, or persuade them not to buy? Conversation logs contain recommendations, but they do not necessarily record subsequent decisions. We audit 317 historical interactions from Aiso's proprietary research database of licens…

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