AI Picks Favorites. Here's How to Be One.

The one thing you need to know in AI today | AI-Ready CMO

When someone asks an AI for a product recommendation, the model doesn’t test anything. It doesn’t open boxes, compare specs hands-on, or read every review on the internet. It gets a shortlist of already-relevant products from a search engine—typically around ten—and decides how to rank them based on the information attached to each one. A new research paper studied how that ranking decision works exactly.

Here’s the experiment. Researchers took real products across 15 Amazon categories, collected the top 10 search results for each, and fed those shortlists to four major LLMs. Then they tried to influence which product the AI would recommend first, using content changes only.

It worked, and the success rates are very encouraging. By appending well-crafted content to a product’s description—either structured reasoning explaining why the product is the best fit, or realistic review-style narratives—the researchers moved the #10 product to #1 around 80% of the time.

They also found that diff…