What a 90-day GEO install actually looks like

"GEO" gets thrown around like it's a setting you toggle. It isn't. Getting an AI engine to consistently name your brand is an install — a sequence of work with dependencies, deliverables, and leading indicators that show up in a predictable order. Here's what the first 90 days actually looks like when we run it, so you know what lands when and what to watch for at each stage.

The system runs in four phases: scan, structure, seed, score. Each depends on the one before it. You can't seed corroboration for claims you haven't structured, and you can't structure pages until the scan tells you which questions and competitors matter.

Weeks 1–2: Scan — establish the baseline

You can't improve a number you've never measured, so we start by measuring.

We build a query set: the real buying questions your customers ask AI engines, not keywords. Forty to a hundred of them, depending on category. Then we run them across the engines your buyers actually use and record, per question, which brands get named, in what order, and described how. That's your baseline share of answer.

Deliverables that land: a scored baseline, a competitor map showing who's winning the answers you're losing, and a gap list — the specific questions where you're invisible and the pages that should be answering them. This is the same output our public scan produces, run at full depth.

What you'll notice: mostly clarity, not results. The value here is seeing, often for the first time, exactly where you stand and who's beating you in the answers that matter. Nothing has moved yet — you've just turned the lights on.

Weeks 3–6: Structure — make your claims legible

Now the building starts. Most brands are invisible to AI engines for a boring reason: their pages state opinions where they should state facts, and the facts they do have are buried where a machine can't extract them.

We rewrite the pages that matter around the decisions buyers are making. Clear identity, specific claims, answered questions. Every "premium quality" becomes a checkable fact. We add the structured data and plain-language specifics that let an engine understand what you are, who you're for, and what you actually do. We fix the pages that should answer your highest-value questions but currently circle them.

Deliverables that land: rewritten and restructured priority pages, a claims layer where every assertion is verifiable, and the technical markup that makes all of it machine-readable.

What you'll notice: by the end of this phase, early movement on the easiest wins — questions where you had the right substance but the wrong structure. These are the low-hanging answers where you deserved to be named and simply weren't legible enough. Don't expect the hard, competitive questions to move yet. They need the next phase.

Weeks 5–10: Seed — build corroboration

This phase overlaps with structure, because it takes the longest to compound. AI engines don't trust a claim that lives only on your own site. They trust claims echoed across independent sources. So we seed corroboration: the same true, specific claims about your brand showing up in reviews, comparisons, credible third-party mentions, and the places your buyers already read.

This is not spam and it's not paid placements dressed up as editorial. It's making the truth about your brand present in more than one place, so that when an engine reasons over the web, it finds your description confirmed instead of unverified. We never run cold outreach to do this — the work is earning legitimate, corroborating presence, not blasting inboxes.

Deliverables that land: a corroboration map showing where your key claims now appear, and a growing base of independent sources that describe you consistently.

What you'll notice: this is the slowest-compounding lever and the one that moves the competitive questions. Expect it to show up later — the hard answers where two or three strong brands were being named start to include you as the corroboration accumulates.

Weeks 8–12: Score — re-measure and tune

Now we run the baseline query set again and compare. Same questions, same engines, apples to apples.

Deliverables that land: a re-scored share of answer against the week-2 baseline, a movement report showing which questions flipped in your favor and which are still contested, and a prioritized next-round plan for the answers that haven't moved yet.

What you'll notice: the full picture. Some questions you now own outright, some you've entered as a named option, some remain stubborn and tell you where the next quarter's work goes.

The leading indicators, by month

Here's what to actually watch, because the headline number moves last.

Month 1: clarity and the easy wins. You have a baseline, a competitor map, and early movement on questions where you had substance but poor structure. Leading indicator: pages becoming machine-legible and the first few "we weren't named, now we are" flips on low-competition questions.

Month 2: structure fully landed, seeding underway. Leading indicator: your claims appearing in more independent places, and mid-difficulty questions starting to include you.

Month 3: corroboration compounding into competitive answers. Leading indicator: measurable share-of-answer gains on the questions that matter most, and a clear map of what's still contested.

Why it's an install, not a campaign

You can't shortcut the order. Seeding corroboration for claims you haven't made legible does nothing. Scoring before you've structured measures noise. The sequence is the point, and each phase's leading indicators tell you it's working before the final number confirms it. That's the difference between running channels and installing a system — and it's why we say channels don't grow brands, systems do.

Want to see your week-2 baseline before committing to anything? That's exactly what a scan gives you. See the full system by audience at /ecommerce, /b2b, and /local, or read more on the blog.