Conversation Is Over: In AI-powered shopping, dialogue only gets in the way (aboard.com)

🤖 AI Summary
A hands-on comparison of AI shopping shows that dialogue-heavy chatbots aren’t necessarily the best way to buy stuff. The author asked ChatGPT, Perplexity, Claude and Google for messenger-bag recommendations and found striking differences: ChatGPT produced a thoughtful, concierge-style dossier (took ~50 seconds) with curated picks and decision guidance; Perplexity and Anthropic’s Claude returned more text-and-link–focused results (~10s) and didn’t consistently funnel to commerce; Google’s “AI Mode” was fastest (first results ~3s, complete in ~6s), ran multiple searches across >100 pages, and delivered rich shopping modules—tables of features, product rankings, stock/pricing, reviews, Reddit threads and real-time discounts. The author calls Google’s output “hustle”: a full commerce experience that blends LLM summarization with live product data and ads, while ChatGPT feels like a high-end concierge. This matters because shopping — not pure conversational novelty — is poised to drive large-scale LLM adoption and reshape search/SEO into what the author terms “Generative Engine Optimization.” Practically, merchants should prioritize structured product data (Shopify/Etsy integrations, schema compliance), surface narrative use-cases, and convert customer language into machine-readable attributes to appear in LLM-driven buying flows. Technically, winners will combine large-scale product graphs, real-time pricing/inventory, user intent signals and LLM summarizers; companies with those data moats (Google, big marketplaces, platform-integrated shops) have a decisive advantage in the new AI commerce stack.
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