Visual Product Cards Now Drive Most Shopping Choices in ChatGPT
New York, Tuesday, 6 October 2026.
A new study reveals 84% of ChatGPT shopping decisions stem from visual product cards, with the top-ranked card capturing 43.4% of choices, shifting how brands must optimize for AI search.
ReFiBuy Study Reveals Product Card Dominance
A new behavioral study published on 5 October 2026 by ReFiBuy reveals that 84% of purchasing decisions within ChatGPT are directly driven by product and offer cards rather than text recommendations alone [1]. The study, titled “In AI Shopping, the Product Card Is Your Storefront,” was conducted by Clickstream Solutions and analyzed 40 U.S. participants completing 224 shopping tasks across six product categories [1]. These findings highlight a crucial shift in generative engine optimization (GEO) and digital commerce strategy, signaling to retail executives that securing prime placement within visual product cards is essential for capturing conversational AI-driven revenue [1]. The data indicates that being mapped correctly to a product card and appearing as high as possible in the offer card list are absolutely critical to optimizing for ChatGPT [1].
Positional Bias Drives Consumer Choice
Data from the study indicates a significant “position bias,” with 43.4% of users choosing the first product card when two or more were displayed [1]. Furthermore, 76% of offer choices went to the first offer card, demonstrating a strong preference for top-slot visibility [1]. Eric Van Buskirk, founder of Clickstream Solutions, noted that when an AI assistant showed two or more product cards, shoppers chose the first one 43.4% of the time, whereas chance would put that at about 29% [1]. This suggests that nearly all of the advantage goes to the top slot, as the second card was chosen less often than chance would predict [1].
Surge in AI-Driven Retail Traffic
Broader market data supports this shift, as AI-driven traffic to U.S. retail websites increased 4,700% year-over-year as of July 2025, based on Adobe analysis of over one trillion visits [2]. According to Capital One Shopping’s 2026 AI Shopping Statistics, 58% of shoppers use generative AI instead of traditional search, with 73% of those users citing AI as their primary source for product research [2]. Retailers implementing AI capabilities experienced 14.2% sales growth between 2023 and 2024, significantly outpacing the 6.9% growth observed in retailers without such implementations, a gap of 7.3 percentage points [2]. This performance differential underscores the financial imperative for adopting AI-ready infrastructure [2].
Strategic Outlook for 2026 and Beyond
Looking ahead, AI platforms are expected to account for $20.9 billion, or 1.5%, of U.S. retail e-commerce sales in 2026, a nearly fourfold increase over 2025 figures according to eMarketer [2]. Gartner predicts a 25% reduction in overall search engine volume by 2026 as consumers increasingly shift toward AI chatbots and virtual agents for discovery [2]. ReFiBuy, which coined the term “Agentic Commerce Optimization” (ACO) in 2025, provides a platform to help brands manage product data and pricing consistency across these AI shopping channels [1]. Successful optimization now requires comprehensive product attribute data and accurate inventory information to ensure visibility for AI shopping agents [2].