OpenAI Launches “Shopping Research” to Automate Online Product Discovery
OpenAI has unveiled a new ChatGPT feature called “Shopping Research,” designed to help users find the best products without manually browsing dozens of websites. Instead of comparing specifications, reading reviews and switching between marketplaces, users can now describe the type of product they want - and ChatGPT will handle the entire research process.According to the announcement, the tool is capable of performing deep web analysis, searching across multiple sources, comparing technical characteristics and filtering products based on personal preferences. The feature also asks clarifying questions to better understand the user’s needs, mimicking the approach of a professional shopping assistant.
How the new feature works
When a user submits a request such as “Find the quietest cordless vacuum for a small apartment,” ChatGPT breaks the task into several stages. First, it identifies relevant technical attributes - noise level, battery life, weight, filtration, price and maintenance requirements. It then conducts a structured search across product listings, reviews, independent tests and brand specifications.The assistant evaluates trade-offs between models, ranks potential matches and presents a curated short list, often with alternative recommendations depending on budget or specialized criteria. This process replicates hours of manual research and condenses it into a few conversational messages.
A tool built for complex categories
OpenAI notes that the service excels in product categories with heavy technical differentiation, such as household appliances, audio equipment, laptops, monitors, cameras and smart home devices. These markets typically require users to compare dozens of parameters - something traditional search engines struggle to optimize for casual shoppers.For simpler queries, ChatGPT can provide quick recommendations without running a full research cycle. But for multi-criteria decisions, the model uses structured reasoning, cross-referencing and iterative dialogue to reach the most accurate result.
Personalization based on user context
The feature leverages ChatGPT’s ability to remember contextual preferences such as room size, noise tolerance, preferred brands or past purchases. This allows the model to refine results over time, providing recommendations that better match the user’s lifestyle and constraints.OpenAI emphasizes that personalization does not rely on external tracking. Instead, it uses in-chat signals and user-provided information, keeping the process transparent while still improving relevance.
Why OpenAI is investing in shopping intelligence
AI-driven shopping is emerging as a major frontier in consumer automation. As the number of online products continues to explode - with dozens of nearly identical options in every category - users face decision fatigue. Traditional search tools often surface sponsored results or incomplete comparisons, leaving shoppers to sort through overwhelming data sets.By contrast, ChatGPT’s research capability functions as a neutral analytical layer. It processes multiple sources, weighs evidence and provides a synthesized conclusion. This approach mirrors how experts evaluate products, applying reasoning instead of simple keyword matching.
Implications for e-commerce and search engines
The launch of “Shopping Research” signals a potential shift in how consumers interact with online marketplaces. If users begin relying on AI for discovery, the power dynamics of product search could shift away from traditional search engines and retailer algorithms. E-commerce companies may need to adapt by improving independent testing data, structured specifications and transparent product information.For platforms like Amazon, Walmart and Best Buy, AI-driven research tools could influence how users navigate product catalogs. Retailers may respond by optimizing their listings for machine-readable attributes rather than solely for human browsing.
A new standard for digital shopping assistance
OpenAI’s announcement reflects a broader trend: AI assistants are moving beyond general conversation and becoming highly specialized researchers. Whether users need a quiet vacuum, an affordable laptop or a reliable coffee maker, the system is designed to compress hours of decision-making into a guided, intelligent dialogue.As AI adoption grows, these capabilities are likely to expand into more categories, from travel planning to financial comparison tools. For now, “Shopping Research” stands as one of the clearest examples of how generative AI can streamline everyday decision-making, eliminating the friction of traditional online shopping.
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