Generative Engine Optimization (GEO) ensures your brand is discoverable across AI-driven search platforms.

Because a growing share of search now ends without a click. When someone asks ChatGPT, Perplexity, or Google’s AI Overviews a question, they get a synthesized answer citing a handful of sources. If you are not among those sources, you are invisible for that query no matter where you rank in the traditional results below.

The two disciplines share a foundation, and SEO work like crawlability, structured data, and topical authority benefits both. Where they diverge is that AI systems reward content that answers a question directly and can be extracted cleanly, and they weight source credibility and factual consistency differently than a ranking algorithm does. We run them as one program with two sets of success metrics rather than selling GEO as a separate product you have to justify twice.

Partly, and anyone claiming otherwise is overselling. A large share of GEO work is SEO fundamentals done well: clean technical foundations, structured data, clear information architecture, and authoritative content. If those are missing, no amount of GEO tactics will help.

The genuinely distinct part is optimizing for retrieval and synthesis rather than ranking. Language models pull passages, reconcile sources, and decide what to cite, which places weight on factual precision, entity consistency across the web, content structured so a specific claim can be extracted without surrounding context, and being referenced by sources those models already trust. It also means measuring something entirely different, since there is no rank position to report.

Faster than traditional SEO in some respects and less predictable in others. Technical and structural improvements can affect how AI systems retrieve your content within weeks, since these systems re-crawl and update more frequently than a ranking algorithm reshuffles positions.

What takes longer is authority and citation building, because being cited by AI systems depends heavily on being referenced by sources those systems already trust, and that is earned rather than configured. Expect early movement on retrieval and citation for queries where you already have strong content, with the harder competitive queries taking a quarter or more. We also flag that these systems change frequently, so we monitor continuously rather than optimizing once and reporting quarterly.

Help, in almost every case. Structured data, semantic clarity, clean information architecture, factual precision, and content that answers questions directly all improve traditional rankings as well as AI retrieval. There is very little tension between the two.

The one area requiring judgment is content format. Content optimized for clean extraction is often more concise and more directly structured than content built to hold a position on a competitive commercial term, where depth and comprehensiveness still matter. We handle that at the page level rather than applying one format across a whole site, which is why running SEO and GEO as a single program produces better outcomes than running them as two engagements with different owners.

An audit of your current visibility across AI platforms, technical work covering structured data, schema, crawlability for AI agents, and content extractability, content optimization and creation built for retrieval, entity and brand consistency work across the web, digital PR to build citations from sources AI systems trust, and ongoing measurement of AI visibility.

The mix depends on where you are weakest. Brands with strong SEO foundations usually need content restructuring and citation building. Brands with technical debt need that addressed first, because AI systems cannot cite content they cannot reliably access and parse.

Yes, though not with the precision of rank tracking. We monitor whether your brand appears and is cited in AI-generated answers across a defined set of queries relevant to your category, tracked on a recurring basis across platforms including ChatGPT, Perplexity, Google AI Overviews, and Gemini. That gives you a citation share, a competitive comparison, and movement over time.

The caveats are real and we would rather state them upfront. AI responses vary between users and sessions, which means measurement is sampled rather than absolute, and none of these platforms provides a Search Console equivalent. Anyone offering exact AI ranking positions is describing something that does not exist. What we can show reliably is directional visibility, competitive standing, and whether the work is moving those numbers.

ChatGPT, Google AI Overviews and AI Mode, Perplexity, Gemini, Claude, and Copilot, plus emerging AI-native search surfaces as they gain meaningful usage.

The practical reality is that optimizing well for one improves performance across most, because they draw on overlapping signals: crawlable and well-structured content, factual consistency, and citation from credible sources. Where they differ is in source preference and how heavily each weights recency, so we monitor per platform rather than assuming a single approach covers all of them.

Often, yes, and it is one of the more common reasons brands contact us about GEO. Language models synthesize from what exists across the web, so incorrect answers usually trace back to outdated pages, inconsistent information across directories and profiles, unclear or missing information on your own site, or a third-party source stating something wrong that the model has picked up.

The fix is source-level: correct and clarify your own content, align entity information across your web presence, and where an external source is the origin, pursue correction. This is slower than editing a page, because these systems update on their own schedule rather than yours, but it is tractable. What cannot be done is editing the model directly, and any provider suggesting otherwise is misrepresenting how this works.

CPG and ecommerce, fashion, consumer services, healthcare, and B2B.

Some categories have more at stake than others. B2B and considered-purchase categories are where GEO matters most right now, because buyers use AI assistants heavily during research and a vendor absent from that stage may never enter the consideration set. Healthcare and other regulated categories carry the opposite risk, where being cited inaccurately is worse than not being cited, so factual precision and claims governance take priority over visibility volume.

Pricing is scoped to the work, and the main variables are the state of your technical foundation, how much content needs restructuring or creating, and how much citation building is required to compete in your category.

For most brands GEO is scoped alongside SEO rather than as a separate line item, because a meaningful share of the work serves both and splitting them creates duplicate effort and duplicate cost. If a provider is quoting GEO as a standalone premium service with no overlap acknowledged, it is worth asking what specifically is being done that SEO would not already cover.

Technical changes covering schema and structured data implementation, crawlability and access for AI agents, page speed and rendering so content is reliably parseable, and clean semantic HTML. Content changes covering restructuring pages so specific claims can be extracted without surrounding context, adding direct answers to the questions your buyers ask, improving factual precision and citation of your own sources, and building topical depth around the entities you want to be associated with.

We also work outside your site, since a substantial share of whether AI systems cite you depends on how you are represented elsewhere: third-party profiles, directories, reviews, editorial coverage, and industry sources. Consistency across those is a major input.

You can, but for most brands it is inefficient. GEO built on a weak technical foundation is optimizing retrieval for content that is hard to retrieve, and the fixes required are the same fixes SEO would prescribe.

The stronger argument for running both is that traditional search has not gone away. Click-through on informational queries is compressing, but commercial and transactional search still drives substantial volume, and the sites AI systems cite most are overwhelmingly sites that already rank well. We would rather scope one program covering both than sell you the newer one and leave the foundation unaddressed.

A fair question, and the test is what changes in the actual work. If a provider’s GEO offering is the same audit with different terminology, it is repackaging. Legitimate GEO work has distinguishing features you can check for: measurement of AI citation and visibility rather than only rankings, content restructured for extraction rather than only for keyword coverage, entity consistency work across your broader web presence, and citation building targeted at the sources these models draw from.

We would also rather tell you when you do not need it. If your technical foundation is broken or you have no content depth in your category, that work comes first and calling it GEO does not change what it is.

A strategist leads the program with technical SEO, content, and digital PR specialists supporting, since GEO draws on all three rather than being a discipline unto itself. The visibility audit is the starting point and can begin quickly, since it requires site access and a defined query set rather than a lengthy discovery process.

Implementation timing depends on how much sits in your CMS versus your engineering backlog. We handle what we can execute directly and write developer-ready specifications for the rest rather than handing over a document and hoping it gets prioritized.