u/Gary_Ko_

I’ve been thinking about how AI systems decide what to cite or summarize when answering brand/product questions.

Traditional SEO was heavily shaped by keywords, backlinks, and page structure. But with GEO, it feels like the reusable parts are often more specific: clear claims, numbers, comparisons, use cases, and third-party mentions.

For example, “we help teams save time” feels much weaker than “we reduced support response time by 32% for a 20-person SaaS team.”

Do you think structured claims will become more important than keyword targeting for GEO, or will both still matter equally?

i’ve been doing more GEO checks lately, and one pattern keeps bugging me: pages that define a term perfectly still feel hard for an LLM to cite. the pages that seem more useful are the ones with a tiny worked example, numbers, and a boundary condition.

for example, instead of a service page saying “we improve local visibility,” i’d rather add a 5-line section: “for a 3-location clinic, we’d track 12 buyer questions, compare mentions against 5 competitors, and update the page when answers cite outdated info.” that gives the model a cleaner fact pattern to reuse.

my current hypothesis: GEO content needs fewer definitions and more quotable mini-scenarios. what kinds of examples are you seeing get picked up most often?