ChatGPT’s Product Finder and Its Integration With Commerce
In early 2025, OpenAI introduced the Product Finder feature in ChatGPT, marking a significant evolution in how consumers search for, discover, and purchase products. Rather than relying on traditional search engines or browsing retailer websites, users can now describe their needs within ChatGPT and receive personalized product recommendations. This includes detailed comparisons, user reviews, and direct purchase links, streamlining the shopping experience from discovery to checkout without leaving the chat interface.
Subsequent advancements enabled users to purchase items directly from selected retailers, such as Etsy, through ChatGPT. Payment integration with platforms like PayPal and Stripe facilitated secure transactions. This approach effectively abridges the conventional, multi-step customer journey into a conversational flow where product discovery and conversion occur in one place. As of April 2025, ChatGPT drove over 243 million visits to media sites—a 98% increase since January 2025—demonstrating rapid consumer adoption as a discovery channel. OpenAI has not yet disclosed click-through rates, but ChatGPT registers over a billion web interactions daily, suggesting tens of millions of product discovery events each week (Retail Media Age, Digiday).
Disruption of Traditional Retail Media
This shift heralds a potential disruption within the retail media landscape. Historically, retail media strategies have emphasized on-site placements such as sponsored product listings, banners, and category carousels, relying on consumers entering retailer-owned digital environments. ChatGPT’s conversational approach not only bypasses these endemic placements but also positions media and affiliate content—often cited as sources in AI recommendations—as new vectors for influencing purchase decisions.
A practical example highlights this convergence: when searching for baby monitors, ChatGPT surfaced the same Hubble monitor as the top recommended product as the retailer’s paid placement, but its suggestion was powered by a media site’s expert review rather than internal campaign logic. This demonstrates that off-site content now has the potential to outweigh endemic retail media investments in guiding consumer choices. According to InternetRetailing and Adweek, media publishers and affiliates are becoming powerful intermediaries in agentic commerce as their reviews and product breakdowns fuel ChatGPT's recommendations.
The Strategic Imperative for E-commerce Infrastructure
Product Feeds and Data Quality
ChatGPT’s performance relies on ingesting and contextualizing vast volumes of product data. Retailers are under pressure to unify their ERP, inventory, pricing, and fulfillment systems so that AI agents can access up-to-date, structured, and complete data (Fortune). Data quality issues—such as siloed inventory, inconsistent pricing, or outdated delivery estimates—undermine the accuracy and trustworthiness of AI-driven recommendations. Retailers that have invested in seamless integrations, like Walmart, leverage this as a competitive advantage, seeing increasing referral traffic and conversion from AI-initiated shopping sessions.
Cataloging Standards and Card Completeness
The rise of agentic commerce amplifies the need for standardized product catalog formats. Comprehensive and high-resolution product feeds become vital, as missing attributes can cause an item to be omitted from AI-driven discovery or present incomplete information to the end user. Complete product cards—with specifications, visuals, customer reviews, availability, and pricing—facilitate more confident AI recommendations and reduce friction in the instant checkout pathway (eMarketer).
Media content cited in ChatGPT recommendations often includes expert reviews and affiliate links, which means brands must monitor content quality beyond their own domains. Ensuring affiliates and publishers feature up-to-date, accurate product data becomes part of the content infrastructure for maintaining visibility within AI-powered channels.
Speed of Assortment Updates
As consumers increasingly begin their shopping journeys via conversational AI, the agility of assortment updates becomes a differentiating factor. Retailers must be able to rapidly onboard new items and accurately update information across all sales channels, including third-party media and affiliate partners, to maintain relevance in instant checkout recommendations. No-code solutions and AI-enabled automation tools are gaining importance, both for internal catalog management and external partner integrations (Blue Wheel Media).
The Role of No-Code Systems and AI Automation
With agentic commerce accelerating the velocity and complexity of retail data interactions, no-code platforms and AI-driven automation are poised to redefine content operations. These tools allow retailers, brands, and publishers to quickly adjust product feeds and campaign metadata for hundreds or thousands of SKUs without deep technical expertise. By democratizing content management and enabling rapid syndication of product attributes and offers, no-code solutions empower both small brands and large retailers to compete in the AI-powered retail channel.
The agility of assortment updates becomes a differentiating factor. To maintain relevance in instant checkout recommendations retailers must be able to rapidly onboard new items and accurately update information across all sales channels.
AI technologies also help reconcile disparate catalog formats, extract key specifications, and generate enhanced product copy that aligns with discoverability criteria in conversational search environments. Enhanced no-code catalog management improves speed to market and increases the probability of inclusion in AI product recommendations—a now critical dimension for e-commerce visibility.
Changing Dynamics in Affiliate and Media Partnerships
Affiliate marketing is set to expand by 8% CAGR from 2024 to 2031, reflecting the increasing value of high-quality off-site content in AI-driven product discovery (Cognitive Market Research). Integrations between brands and a diverse network of publishers, influencers, and review sites will become more central to retail media strategies. Presence in expert reviews and affiliate lists can determine placement in ChatGPT-generated recommendations, shifting budget priorities from on-site campaign activation to broader content syndication.
The network effect here is substantial: as more brands invest in high-quality off-site content, third-party publishers strengthen their position as arbiters of product visibility in agentic commerce. Brands that neglect this dimension risk losing share in the AI shopping ecosystem, where initial discovery may never visit a retailer’s own site.
Implications for Retailers and Brands
For retailers and brands, the advent of ChatGPT as a shopping assistant and conversion point is both a threat and an opportunity. The main risk lies in diminishing the reach and perceived value of traditional paid placements and on-site ad inventory. If shoppers routinely transact without being exposed to cross-selling or onsite campaign logic, retailers may lose incremental revenue and customer relationship depth (eMarketer).
Conversely, those who adapt their retail media strategy—including investing in off-site content partnerships, upgrading catalog infrastructure, and automating data flows—stand to capture significant value from the rising tide of agentic commerce. Early movers already report surging referral traffic, improved conversion rates, and greater brand visibility among new customer segments.
Looking Forward
The full impact of agentic commerce—where AI and conversational interfaces mediate product discovery and transaction—is only beginning to play out. Surveys indicate that over a third of US consumers would permit an AI assistant to make purchases on their behalf (TechRadar-Omnisend), highlighting rapid shifts in consumer openness to delegated commerce.
The sector now faces two converging challenges: accelerating the quality and completeness of content infrastructure and reconfiguring retail media toward omnichannel, AI-integrated strategies. The next frontier will be integrating product data, reviews, and affiliate relationships to make every SKU discoverable, comparable, and buyable in an instant, wherever the digital shopping conversation begins.
Sources: Retail Media Age, Digiday; Fortune; Adweek; eMarketer.
The emergence of AI-powered product finders like ChatGPT underscores the urgent need for e-commerce businesses to prioritize data quality and catalog efficiency. At NotPIM, we recognize this evolution as a significant shift impacting product visibility and sales. Our platform directly addresses the challenges outlined by providing tools to unify data, standardize product feeds, and automate content updates, ensuring that retailers can compete effectively in this new conversational commerce landscape. This proactive approach helps businesses maintain discoverability and build a robust foundation for future innovation.