GEO is the practice of getting your brand named inside an AI-generated answer, not just listed on a results page. We build the retrieval access, entity authority, and source credibility that decide which brands a model repeats out loud.
A generative engine doesn't return ten options and let the user choose. It composes an answer and attributes it to a handful of sources — often three, sometimes five. Everyone else in the category simply isn't mentioned. There is no position four, and no consolation click.
That changes what optimization means. Ranking work asks how to move up a list. GEO asks a different question: when a model assembles an answer about this topic, what makes it reach for your page rather than someone else's? The answer turns out to be fairly consistent — the source has to be retrievable, the entity has to be resolvable, the claim has to be corroborated elsewhere, and the passage has to be clean enough to lift.
We work those four conditions deliberately rather than hoping good content is enough. In practice, the biggest wins usually come early and technically: sites that were never retrievable in the first place, which no amount of content investment was ever going to fix.
These terms get used interchangeably, and the distinction is real but narrower than most agencies imply. Here's how we separate them in practice — and why most engagements need both.
Best for: Brands in competitive categories where the assistant is already answering buying questions and naming competitors.
Best for: Brands with clear informational questions in their funnel and content that's good but structurally messy.
Across platforms, source selection comes down to a fairly consistent set of conditions. GEO work is the deliberate construction of all four rather than hoping content quality carries you.
The page has to be reachable and renderable by the crawler feeding the model. Blocked user agents and client-side-only rendering are the two most common silent failures we find.
The model has to connect your page to a known entity with defined attributes. Ambiguous or inconsistent brand identity means your content is read as anonymous rather than authoritative.
Claims that appear only on your own domain carry limited weight. Independent sources repeating the same facts is what converts an assertion into something a model will state confidently.
A passage has to be liftable — self-contained, unambiguous, and not dependent on three paragraphs of context above it to make sense.
GEO is not a content package. It spans technical retrieval work, entity engineering, content restructuring, and earned citation acquisition — because source selection depends on all of them.
We build the prompt set your category actually gets asked, then measure who gets cited today and how often you appear. Everything else is scoped against this baseline.
Crawler access, rendering strategy, and response handling fixed so the systems feeding generative answers can actually read your pages in full.
Schema, sameAs corroboration, consistent naming, and knowledge-graph alignment so models resolve your brand to a specific, credible entity.
Earning independent references from the kinds of sources models actually retrieve — trade publications, industry resources, and authoritative listings.
Rewriting key pages so answers lead, terms are defined, and each section stands alone well enough to be quoted without distortion.
Monthly reporting on where you appear, what moved, which competitors gained, and where the next month's effort should go.
The four pillars are constant; their relative weight is not. Where we spend the first 60 days depends heavily on what kind of business you run.
Software buying questions are exactly what assistants answer well, and review platforms are heavily retrieved. Corroboration usually matters more than on-site work here.
Product answers depend on structured data more than prose. Catalogs with incomplete markup are absent from the surface entirely, regardless of brand strength.
Service categories are won on demonstrated expertise. Models lean toward sources that explain rather than sell, which suits genuine subject-matter depth.
Large organizations usually have the authority already and lose to fragmentation — different regions and business units describing the same entity three different ways.
GEO work runs on the RON Loop, with the emphasis weighted toward corroboration and source credibility rather than on-page structure alone.
We test what generative crawlers actually receive from your site, and benchmark the prompt set your category gets asked so there's a real number to move.
We map how models describe your brand today, where the description is wrong or missing, and which competitors own the citations you want.
Technical fixes and schema go in alongside passage restructuring, while citation outreach begins targeting the sources that actually get retrieved.
Monthly citation share reporting per platform, with the next cycle's priorities set by what actually moved rather than what we assumed would.
Generative engines retrieve from the open web. That means the crawlable, fast, credible site classic SEO has always demanded is the same asset GEO depends on — which is why we don't sell these as opposing disciplines.
The questions clients ask us most before starting. If yours isn't here, ask us directly on a consultation call.
GEO is the practice of optimizing a brand so generative AI systems cite it as a source when composing answers. Instead of competing for a position in a list of links, you're competing to be one of the three to five sources a model names.
It rests on four conditions: your pages must be retrievable by AI crawlers, your brand must resolve to a recognizable entity, your claims must be corroborated by independent sources, and your content must be structured so passages can be extracted cleanly.
They overlap substantially and the industry uses them loosely. GEO generally emphasizes being cited within a generated answer. AEO emphasizes being the extracted direct answer to a specific question. LLM SEO is usually used as the umbrella term for optimizing toward language-model retrieval generally.
In practice the underlying work is largely shared. We treat the distinction as a matter of emphasis rather than three separate products, and we'll tell you which emphasis your situation actually needs.
Through a benchmarked prompt set. We define 40 to 60 questions your category genuinely gets asked, then track per platform whether your brand appears, how prominently, and against which competitors.
That yields a citation share figure tracked monthly. It's less precise than rank tracking and we're upfront about that — model outputs vary by phrasing and change with updates, so we report ranges and trends rather than false precision.
Retrieval fixes can move within weeks — if a crawler was blocked, unblocking it changes things on the next crawl cycle. Entity and schema work typically shows within four to eight weeks.
Corroboration and citation building is the slow part, usually two to four months, because it depends on third parties publishing and those pages being re-crawled. We plan on a 90-day first-movement window.
No. Model outputs are probabilistic, sensitive to phrasing, and change with every model update. Anyone guaranteeing specific AI citations is misrepresenting how these systems work.
What we guarantee is that the work is measured: a documented baseline, a defined prompt set, monthly reporting, and an honest account of what moved and what didn't.
Usually yes, as a side effect rather than the goal. Most GEO work — fixing crawl access, deploying accurate schema, clarifying entity signals, restructuring content around clear answers, earning credible references — is work classic SEO also rewards.
The reverse isn't equally true. Strong Google rankings don't automatically produce AI citations, which is precisely the gap most brands discover when they first benchmark.
Usually both. Most sites have more usable content than they think, but it's structured for a reader scrolling rather than a model extracting — answers buried mid-page, terms undefined, comparisons implied rather than stated.
We typically restructure existing high-value pages first, since that's faster and cheaper than net-new production, then identify genuine content gaps where the category is being asked questions you've never addressed.
ChatGPT, Perplexity, Google Gemini, Claude, Microsoft Copilot, and Google AI Overviews as standard. Perplexity and AI Overviews tend to show movement earliest because they lean most heavily on live retrieval.
Platform-specific tactics matter at the margin, but roughly 80% of the work is shared across all of them. Our individual platform pages cover the differences in detail.
Standalone audits typically run in the low five figures. Ongoing GEO retainers generally start around $4,000–$10,000 monthly, rising to $10,000–$25,000+ for competitive categories or enterprise scope.
Cost is driven mainly by how much technical remediation is required, catalog or site size, and how much citation-building the competitive landscape demands. Detail is on our pricing page.
It can happen, and we plan for it rather than pretending otherwise. Model updates reshuffle source selection, sometimes significantly, which is exactly why we run monthly rather than delivering a one-time project.
The durable assets — entity clarity, schema accuracy, genuine third-party corroboration — tend to survive updates better than tactical wins, which is where we weight the work deliberately.
We'll benchmark your category's real prompt set, show you the competitors currently named in those answers, and map what it takes to displace them.
No commitment · 45 minutes · Immediate value
We’ll run your category’s real questions live on the call and tell you honestly whether this is worth your budget. No pitch deck.
Two fields. We’ll crawl your site as GPTBot, ClaudeBot and PerplexityBot, benchmark a sample of your category’s prompts, and send you what we find.
No commitment, no sales sequence. If we’re not a fit, we’ll say so.