David Pawlan(@DavidPawlan):I feel like AI has broken search recommendations as we know it. A new research paper analyzed 38,400 rankings across 4 AI models. The general conclusion is that AI search favors popular brands & merchants. How did they perform this test? Researchers kept a product page word for word the same and only swapped the real brand name for a new, made-up brand. The page dropped in the rankings in every model they tested. They rewrote the copy for GEO, according to today's best practices, and there was little to no impact. TLDR: the same product loses when it comes from a brand the model doesn't remember. The bias shows up everywhere: the most popular brands get cited 1.4x to 2.8x more than the average brand. So what does this mean? For merchants, new brands need to figure out how to fight for real estate. Traditional GEO strategies to increase visibility, and thus conversions, may not deliver the short-term wins they hoped for. For consumers, we're naturally biased toward name brands because of social proof, but I'd argue we also want to be exposed to higher-quality, emerging products. I'm not sure how we fix existing search, but I do think we can make a real effort to solve this on new surfaces, like agentic commerce. In the short run, I think agentic search will also be biased toward popularity. I.e. if you search for paper towels on Instinct or Muse, Bounty will show up more often than an off-brand. This makes sense as people today prefer name brands, so agentic search is incentivized to serve those brands. However, agents can learn far more about you than a search box can, so I think they'll get better at balancing three key variables: taste, quality & price. When an agent knows you intimately, it knows your taste profile, your quality preference, and your price appetite. As agents build this knowledge, we'll trust their recommendations more, and agents will get the chance to surface products on fit instead of popularity (unless popularity is the user's preference!) It's the same reason ads work so well: they know you, deeply. Your agent will know you even better, which will in turn create a more tailored user experience that benefits you, the user, but also creates a more even playing field for the merchants. Source:

2026.11.13 16:39

I feel like AI has broken search recommendations as we know it. A new research paper analyzed 38,400 rankings across 4 AI models. The general conclusion is that AI search favors popular brands & merchants. How did they perform this test? Researchers kept a product page word for word the same and only swapped the real brand name for a new, made-up brand. The page dropped in the rankings in every model they tested. They rewrote the copy for GEO, according to today's best practices, and there was little to no impact. TLDR: the same product loses when it comes from a brand the model doesn't remember. The bias shows up everywhere: the most popular brands get cited 1.4x to 2.8x more than the average brand. So what does this mean? For merchants, new brands need to figure out how to fight for real estate. Traditional GEO strategies to increase visibility, and thus conversions, may not deliver the short-term wins they hoped for. For consumers, we're naturally biased toward name brands because of social proof, but I'd argue we also want to be exposed to higher-quality, emerging products. I'm not sure how we fix existing search, but I do think we can make a real effort to solve this on new surfaces, like agentic commerce. In the short run, I think agentic search will also be biased toward popularity. I.e. if you search for paper towels on Instinct or Muse, Bounty will show up more often than an off-brand. This makes sense as people today prefer name brands, so agentic search is incentivized to serve those brands. However, agents can learn far more about you than a search box can, so I think they'll get better at balancing three key variables: taste, quality & price. When an agent knows you intimately, it knows your taste profile, your quality preference, and your price appetite. As agents build this knowledge, we'll trust their recommendations more, and agents will get the chance to surface products on fit instead of popularity (unless popularity is the user's preference!) It's the same reason ads work so well: they know you, deeply. Your agent will know you even better, which will in turn create a more tailored user experience that benefits you, the user, but also creates a more even playing field for the merchants. Source:

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