OpenAI introduces shopping research tool in ChatGPT for guided product discovery

OpenAI has expanded ChatGPT’s capabilities with a new feature called shopping research, aimed at helping users navigate product choices without combing through multiple websites. The experience is being introduced across Free, Go, Plus and Pro plans on both web and mobile, widening access as consumers prepare for peak holiday shopping.

The feature lets users describe what they are seeking, such as a household device, a shortlist comparison or a specific type of gift and ChatGPT compiles a tailored set of recommendations. It follows up with targeted questions around budget, intended usage and preferred attributes, gradually shaping a clearer understanding of what the user wants. The tool is designed for deeper decision-making, offering structured comparisons and outlining key differences or trade-offs when the query demands more context.

Shopping research performs strongly in categories that rely heavily on specifications and detailed attributes, including electronics, beauty, home and garden items, kitchen appliances and outdoor gear. While simple requests continue to receive standard instant responses, the new tool takes a few minutes to assemble more comprehensive guidance drawn from reliable online retail sources. Throughout the interaction, users can flag items they like or reject options they no longer want to consider, allowing the system to refine its suggestions in real time.

OpenAI has cautioned that the feature may occasionally surface inaccuracies around pricing or product availability, encouraging users to confirm details directly on merchant sites. The company also plans to link the experience with Instant Checkout, its purchase flow for supported retailers, enabling direct transactions in future.

For Pro users, the feature is additionally visible in ChatGPT Pulse, which can surface relevant shopping recommendations based on previous conversations. With this launch, OpenAI positions ChatGPT as a more active participant in product research, aiming to reduce the manual effort typically required to evaluate alternatives and arrive at a confident choice.