How AI Decides Which Brands to Recommend
Being named and being endorsed by AI aren’t the same event. Here’s where that line sits, why it matters more than raw citation volume, and how to check which side of it you’re on.
Being named and being endorsed by AI aren’t the same event. Here’s where that line sits, why it matters more than raw citation volume, and how to check which side of it you’re on.
My own guide to getting cited already sketches E-E-A-T in three paragraphs. This is the version with the schema, the worked example, and the honest warning about what happens when you fake it.
What actually earns you a Wikipedia page, why Wikidata is the realistic move for almost everyone else, and the schema work that ties it together.
Real tracked-account data shows the same brand fighting three different competitive battles depending on which AI engine you check.
Most AEO tactics aren’t platform-exclusive, they just work with different intensity. The real evidence, tactic by tactic, including where my own tracked data disagrees with the published studies.
Fan-out mechanics are covered elsewhere. This is the workbook: a repeatable method for mapping your own cluster and building the coverage that actually earns citations.
Most “write for AI” advice repeats the same five bullet points without explaining why they work. Here’s the actual mechanics, plus a worked rewrite so you can see the difference instead of just reading about it.
Most schema guides list every type schema.org offers and call it thorough. Here’s the shorter, more honest version: which types actually help AI engines understand your page, real JSON-LD you can paste in, and which types to stop worrying about.
FAQ sections get treated as an afterthought bolted onto the bottom of an article. For AI citation, they’re one of the highest-leverage formats on the page, if you build them from real questions instead of guessed ones.