Your next smartphone buying decision might be made by ChatGPT

What Happened: OpenAI has unveiled Shopping Research, a new feature in ChatGPT designed to act as a personalized product-finding assistant.

Instead of browsing dozens of websites, users can now describe what they’re looking for – whether it’s the quietest cordless vacuum, a bike comparison, or a gift for a four-year-old – and ChatGPT will create a detailed, tailored buyer’s guide.
The feature is rolling out starting today on mobile and web for all logged-in users across Free, Go, Plus, and Pro plans. To support holiday shopping, OpenAI is offering nearly unlimited usage of Shopping Research for all plans throughout the season.
The system works by asking clarifying questions, scanning the web for up-to-date product details, checking reliable sources, and using ChatGPT Memory (if enabled) to personalize recommendations.

Why Is This Important: Hundreds of millions of ChatGPT users already rely on the tool to compare products, understand features, and navigate a crowded marketplace.

But until now, ChatGPT responses were limited by how quickly it could pull information and how much depth the user requested.
Shopping Research introduces structured, multi-step product evaluation – a deeper form of guidance traditionally requiring manual research across dozens of tabs.
It performs especially well for categories with complex specs and trade-offs, like electronics, appliances, beauty products, fitness gear, and home essentials.
This also marks one of the first major applications of GPT-5 mini, trained specifically for shopping tasks using reinforcement learning, optimized to read product pages, cite sources, and synthesize details across multiple sites.

Why Should I Care: If you’ve ever spent hours comparing products, reading reviews, checking specs, and making lists, this feature dramatically reduces the effort.

You simply describe what you need, answer a few clarifying questions, and ChatGPT returns a personalized, up-to-date buyer’s guide with recommendations, differences, trade-offs, pricing, and availability.
As you interact with suggestions – using prompts like “More like this” or “Not interested” – the research adapts in real time. And because user chats are not shared with retailers, the recommendations remain organic and unbiased.
Whether you’re holiday shopping, comparing gadgets, or replacing home appliances, Shopping Research offers a curated experience that saves time and cuts down on choice overload.