Published on: May 4, 2025 / Updated on: May 4, 2025 – Author: Konrad Wolfenstein
Non-ad-funded e-commerce in AI search: OpenAI publishes ranking factors for products in ChatGPT – Image: Xpert.Digital
ChatGPT transforms online shopping – recommendations without advertising
Product Recommendations 2.0: How OpenAI is setting standards with ChatGPT
At the end of April 2025, OpenAI rolled out a significant update for ChatGPT, enabling the AI system to display product recommendations. Unlike traditional e-commerce platforms, these recommendations are not influenced by advertising but are based on a complex selection algorithm. OpenAI has now published the factors that determine which products appear in the new, visually appealing carousels and how these products are selected.
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The basic selection algorithm
ChatGPT uses a novel approach to product recommendations that differs fundamentally from conventional search engines and e-commerce platforms. “Unlike Google or Amazon, ChatGPT’s product results are ‘selected independently by ChatGPT and are not advertisements,’” as OpenAI emphasizes in its documentation. This non-advertising-funded approach represents a significant departure from traditional e-commerce platforms.
Product selection is based on an intent-driven evaluation process. When a user submits a query with purchase intent (e.g., "I'm looking for costumes for my two dogs"), ChatGPT activates its shopping features and displays relevant product options. The user experience is significantly more direct than with traditional search engines – while Google often displays numerous product reviews and blog posts, ChatGPT immediately presents specific products with relevant information.
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The four key factors in product selection
OpenAI has identified four primary factors to consider when selecting a product:
- Structured metadata from third-party providers – technical specifications, pricing information, and product descriptions – are included in the evaluation
- Third-party content – customer reviews and ratings help assess product quality and customer satisfaction
- Pre-generated model responses – information that ChatGPT generates before including new search results
- OpenAI security standards – filtering mechanisms that ensure recommended products comply with company policies
The relative importance of these factors shifts dynamically depending on user requirements. For example, if a user specifies a budget, the system prioritizes price information. If specific product attributes are mentioned, these characteristics are given greater weight in the selection algorithm.
Influence of user context on product selection
ChatGPT's product recommendations are heavily influenced by contextual signals from user interactions. The system processes:
- Explicit query information – Direct product requirements in the search
- Recall data – When enabled, ChatGPT considers previous conversations to personalize recommendations
- Custom instructions – User-defined preferences that persist across sessions
This contextual awareness creates a personalized shopping experience. For example, if a user had previously expressed a dislike for clowns, ChatGPT would incorporate this information into the product selection and exclude clown costumes from the recommendations for dog costumes. This personalization goes far beyond what conventional search engines offer.
Display of product information
OpenAI has implemented several techniques to optimize the presentation of product information:
- Standardized product descriptions – ChatGPT generates simplified, consistent product titles and descriptions that normalize the inconsistent terminology used by different retailers for identical products
- AI-generated feature labels – products may receive labels such as “good value” or “most popular” based on ChatGPT’s analysis of available data, although these labels are “not guarantees or verified statements”
- Review summaries – The system creates concise summaries that highlight common user opinions about products, drawing on reviews from public websites
- Rating aggregation – Star ratings displayed on the interface may represent aggregated ratings from multiple sources, which “may not match the rating available on a particular website”
Selection methodology for dealers
The current merchant selection system functions primarily as a presentation layer rather than a sophisticated ranking system. When users click on a product, ChatGPT can display a list of merchants offering that item, with placement “predominantly determined by these [third-party] providers” and not by performance metrics such as pricing competence or shipping policies.
OpenAI explicitly states: “We do not reorder merchants based on factors such as price, shipping, or return policies.” However, this could change, as OpenAI notes: “We expect this to evolve as we continue to improve the shopping experience.”
Technical principles of product selection
The technical implementation of ChatGPT's product recommendation system reveals several important aspects:
Rephrasing the query for product search
When users express purchase intent, ChatGPT employs a complex mechanism to rephrase queries and improve search precision. Instead of using the user's exact language, the system transforms natural language queries into structured search parameters.
Location awareness in product selection
Product relevance is further improved through the processing of location data. According to the OpenAI documentation, the system “collects general location information based on your IP address and may share this general location with third-party search providers to improve the accuracy of your results.”.
Roadmap for dealer integration
OpenAI has announced plans to build more direct relationships with retailers. The company is “exploring ways for retailers to provide us with their product feeds directly, which will ensure more accurate and up-to-date offers.” This suggests a future where product selection could rely less on third-party aggregators and more on direct retailer data.
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Impact on marketing and e-commerce
This non-advertising-funded approach represents a significant departure from conventional digital marketing. While search engines and e-commerce platforms traditionally generate revenue through sponsored placements, ChatGPT's model prioritizes relevance and user experience with independently selected results.
The shopping functionality is currently being rolled out to Plus, Pro, Free, and unregistered users worldwide, wherever ChatGPT is available. With over a billion web searches processed in the first week after launch, this new approach could force established players to rethink their reliance on ad-based product recommendations.
Intention-based product recommendations: The end of paid placements?
OpenAI's release of the ranking factors for products in ChatGPT marks a significant shift in product search and recommendation in the digital space. The intent-based, non-advertising-funded approach offers users a personalized shopping experience based on relevance and context, rather than paid placements.
For retailers and marketing professionals, this means that traditional SEO strategies need to be adapted. Factors such as product quality, authentic reviews, and accurate metadata are gaining importance, while paid placements are becoming less prominent. With the planned direct integration of retailer data, this landscape could evolve further, creating new opportunities for retailers who offer high-quality products and customer experiences.
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