Inside ChatGPT’s new shopping feature and why it matters for brand discovery
OpenAI introduces a buyer's guide engine to simplify product research. Here's what this means for ecommerce and marketing pros.
OpenAI has quietly rolled out shopping research, a new feature in ChatGPT designed to help users find the right products through personalized buyer’s guides instead of endless Google searches.
With AI now playing product expert, the launch may shift how customers explore categories like electronics, beauty, home, and outdoor gear.
This article explores what the feature does, how it works, and why it could be a game changer for ecommerce brands, affiliate marketers, and B2B product discovery.
Short on time?
Here is a table of content for quick access:
- What just launched? A buyer's guide engine built into ChatGPT
- How it works: from question to curated product picks
- Why this matters for marketers and ecommerce pros
- A few limitations to watch
Patrecia Meliana
A buyer's guide engine built into ChatGPT
OpenAI’s new shopping research feature lets ChatGPT users ask complex shopping questions such as comparing bikes or choosing a gift, and receive curated product recommendations in minutes.
Rather than sifting through dozens of tabs, users can describe what they are looking for, interact with follow-up questions, and get a detailed guide outlining key differences, tradeoffs, and links to purchase.
The feature pulls from high-quality online sources and adapts based on your preferences or past ChatGPT conversations if memory is on. It also allows real-time feedback like “not interested” or “more like this” to refine results as the AI shops on your behalf.
How it works
Shopping research is powered by a mini GPT-5 model fine-tuned specifically for ecommerce tasks. OpenAI says this version was trained to synthesize across trusted product sites, cite sources, and handle constraints like price, size, specs, and availability.
Here is the user flow:
- Ask a shopping question in ChatGPT
- Tap to enter shopping research mode
- Chat with the AI about budget, needs, and preferences
- Get product options along with detailed reasoning
- Click through to retailers (coming soon: Instant Checkout through ChatGPT)
This model performs especially well in detail-heavy verticals such as tech gadgets, home and kitchen, and sports gear, where the research phase is long, messy, and often frustrating.
Why this matters for marketers and ecommerce pros
OpenAI’s shopping research feature is not just another AI experiment. It represents a shift in how consumers interact with products online—and that has real implications for how brands get discovered, compared, and chosen. Whether you're in ecommerce, content marketing, or B2B lead gen, this update demands attention.
1. Product discovery is shifting from search to chat
This rollout signals a major behavioral shift, from Google-style self-research to AI-assisted exploration. As users grow more comfortable describing needs to ChatGPT instead of Googling for reviews or listicles, traditional SEO strategies may lose visibility.
Marketers should rethink how product content is structured and optimized for AI summarization. If ChatGPT becomes the new product advisor, brands need to ensure their content is scannable, trustworthy, and accessible to AI models.
2. Personalization is becoming the default expectation
With ChatGPT tailoring suggestions based on memory or past conversations, expectations around personalization are rising. Generic product pages or broad-targeting ad campaigns will not be enough.
To stay competitive, marketers must invest in audience segmentation, first-party data, and content formats that AI can easily interpret. The closer your messaging aligns with user context, the more likely your products will show up.
3. Affiliate and B2B strategies could evolve
Shopping research is not just for Amazon picks. It applies to B2B software, office gear, and subscription tools too. That creates new opportunities for affiliate marketers, SaaS vendors, and B2B brands to treat ChatGPT as a product discovery engine.
By ensuring your product specs, reviews, and data are publicly available and structured cleanly, you improve your chances of being included in these AI-generated buyer’s guides. OpenAI is also offering an allowlisting process for merchants.
A few limitations to watch
OpenAI notes that while the model performs well on internal benchmarks, it may still surface incorrect pricing or availability. Users are encouraged to verify details on merchant sites before purchasing.
Transparency remains a priority. OpenAI states that user chats are not shared with retailers and results are based only on publicly available web data.
Shopping research may still be rolling out, but its impact is already clear. Whether you are in ecommerce, DTC, or B2B, this is another sign that AI is becoming a key part of the buyer journey.
Marketers should audit their product data, prioritize AI-accessible content, and prepare for a future where the path to purchase begins with a conversation.
