Shopping Research Assistant In ChatGPT

Nov 25, 2025 - 7:51 am 0 by

Chatgpt Shopping

OpenAI announced shopping research within ChatGPT, "a new experience in ChatGPT that does the research for you to help you find the right products," as OpenAI put it. This is clearly OpenAI's response to Google's AI Mode and Gemini 3 shopping experiences.

ChatGPT can now help you research the right product for you. OpenAI wrote, "it asks smart clarifying questions, researches deeply across the internet, reviews quality sources, and builds on ChatGPT’s understanding of you from past conversations and your ChatGPT memory to deliver a personalized buyer’s guide in minutes."

Shopping research is starting to roll out now on mobile and web for logged-in ChatGPT users on Free, Go, Plus, and Pro plans. OpenAI will make it "nearly" unlimited usage available to all plans through the holidays.

Here is a video of how it works:

Back in April, OpenAI first brought shopping search to ChatGPT and then last month introduced Agentic Commerce Protocol to help automate buying through ChatGPT. This is the next level of making shopping better within ChatGPT.

To use it, ask ChatGPT a shopping question and ChatGPT will suggest shopping research automatically. Tap it to begin, or you can also select ‘shopping research’ from the (+) menu. After a few minutes, ChatGPT will give you a "personalized buyer’s guide with the top products, key differences, tradeoffs, and up-to-date information from reliable retailers." "It’s a clear summary that normally would take a lot of comparing, reading, and checking on your own," the AI company wrote.

How does it work? This is what OpenAI wrote:

Shopping research is powered by a version of GPT‑5 mini trained with reinforcement learning specifically for shopping tasks. We trained it to read trusted sites, cite reliable sources, and synthesize information across many sources to produce high-quality product research. We also designed it to be an interactive experience that could update and refine its research in real time—incorporating new constraints and adjusting to feedback on user product preferences—resulting in a response that feels both well-researched and personalized.

This doesn't sound good for affiliate sites, as Glenn Gabe wrote on X. "Alarms are going off at affiliate sites now. And wait, it "reviews quality scores."

Forum discussion at X.

 

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