Where to start with GEO

The instinct, once a company decides AI visibility matters, is to start changing things: rewrite pages, add markup, chase mentions. Resist it for a few weeks. The first job is not to act but to look, because you cannot fix a description you have not read. Start by asking the major assistants the questions your buyers actually ask, in plain language, and writing down what comes back. That record, unflattering as it often is, is the only honest baseline you have.

What you are looking for in those replies is specific, not vague. Are you named at all when someone asks for a recommendation in your category? When you are described, is it right, or is it a version of you from two years ago? Which competitors keep showing up beside you, including ones you do not think about? Each answer points at a different problem, and the problems rarely need the same fix, so the audit is what stops you spending the first month on the wrong one.

From there the early work sorts itself by cost and leverage. The cheapest wins are usually consistency and clarity: make your core facts match everywhere a machine can read them, and make your most important pages state the point in sentences a model can lift. These are not glamorous and they do not need a big budget, and they move the number more reliably than any clever tactic. The slower, harder work, earning genuine mentions from sources the engines trust, comes after, once the foundation is not actively working against you.

Then you set a cadence and accept that this is ongoing. Re-run the same questions every few weeks, watch share of answer rather than any single reply, and let the trend tell you whether the work is landing. The companies that get somewhere with GEO are not the ones who did the most in the first month. They are the ones who found out where they actually stood, fixed the cheap things first, and kept looking.