Every Black Friday reveals how consumers search, compare, and decide. This year added something new: a real-world test of how AI models interpret commerce under true demand.
So we ran a structured test across major LLMs and analyzed 10,000 responses. The goal was simple: to see how these systems form their internal view of the retail landscape and which signals shape the answers they generate.
As we reviewed the dataset, a clear pattern emerged: Black Friday acts as a natural stress test for AI-driven discovery.
The sheer volume of queries, the range of categories, and the speed of shifting consumer attention expose the sources, structures, and behavioral tendencies that shape how LLMs reason about products, retailers, and intent.
The results offer a preview of how AI search is evolving – and how the broader commerce ecosystem will feel the impact.
TLDR;
- LLMs overwhelmingly rely on a small cluster of external domains with YouTube, big-box retailers, and U.S. review media dominating the landscape.
- Generalist retailers win decisively, capturing nearly half of all retail mentions and becoming the “default funnel” LLMs use to answer shopping questions.
- Social and UGC sources surge during Black Friday, growing +8.1%, while classic retail and media sites lose share.
- Off-page signals matter as much as on-page signals: Reddit, YouTube, Amazon, and Consumer Reports collectively shape the “External Data Sources” LLMs use to compare and recommend products.
- Structured comparison content is disproportionately influential, far more than brand-owned assets.
- LLMs behave differently not only from Google, but from each other, with each Gemini, OpenAI, and Perplexity producing different formats, lengths, and reasoning patterns.
LLMs don’t look at the commerce ecosystem like search
In traditional search, the funnel starts with a query and ends with a ranked list of results, often dressed up with shopping carousels, popular products, and other curated touches. In AI search, the funnel flips.
The model begins with its internal map of the world – a compressed web of relationships, sources, and signals – and then builds an answer. In shopping, an LLM’s goal is to deliver a purposeful response, not a shopping experience.
When we reviewed the top 50 most-cited domains across 10,000 LLM responses – spanning deals, reviews, comparisons, and product recommendations – the distribution was far from neutral:
- YouTube: 1,509 citations
- Best Buy: 950
- Walmart: 885
- Target: 477
- TechRadar: 355
- RTings: 342
- Consumer Reports: 325
This cluster shapes much of the commercial “knowledge” LLMs draw from. It leans toward large retailers, widely cited media outlets, and platforms built around comparisons or reviews. Together, these sources create a collection of resources that lets models deliver direct answers across any vertical, product type, or consumer need.
How LLM behavior…
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