Your GEO questions answered

Hey, I’m Isaac 👋 I founded Pistachio, a growth agency working with B2B brands like Atono and Clay to build trust, relationships and loyalty with their current and future customers.

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Search used to be simple… You wrote content. You optimized it. Google sent you traffic. And that’s it.

That model worked for a long time. Long enough that many brands still plan around it.

But the way people search has changed. And more importantly, the way answers are delivered has changed with it. Discovery is no longer only about ranking, it’s about being used as a source by LLMs (such as ChatGPT, Perplexity, and more).

So the question everyone is asking is: Is GEO the new SEO? Let me share more about it.

Traditional SEO was all about navigation.

With tools like ChatGPT, Claude, Gemini, and Perplexity, search behavior is no longer centered around links and ranking. Users are no longer navigating through search results. They're receiving answers directly. And those answers are constructed by systems that evaluate sources differently than traditional search engines ever did.

Actually, AI search is becoming a preference for the audience compared to traditional search, according to Innovating with AI research:

Where Google's algorithm assessed relevance through signals like backlinks, keyword optimization, and user behavior, generative systems assess usefulness through interpretability. LLMs favor content that explains concepts clearly, demonstrates expertise authentically, and presents information in ways that can be reliably extracted and reused.

This changes what effective content looks like. Keyword density becomes less relevant than conceptual clarity. Backlink profiles matter less than whether your explanation is distinctive enough to be worth citing. The mechanics of ranking give way to the mechanics of being understood and trusted by systems designed to compress and redistribute information.

GEO is the practice of optimizing how your brand’s ideas are interpreted, retained, and reused by generative AI systems. It’s about designing content so that when answers are generated, your brand’s perspective can also be included in these LLMs’ answers.

Generative engines don’t scan for keywords in the same way search engines do. They interpret logical ideas and content.

When a model generates a response, it's synthesizing information from multiple inputs. The content that surfaces isn't necessarily the highest-ranking page for a given keyword. It's the content that presented the idea most clearly, most credibly, and in a format the system could extract and repackage without distortion.

This creates a different type of optimization challenge. You're no longer competing to be the top result on a page only. You're competing to be the most interpretable source when an answer is being constructed.

Several factors influence this selection. Clarity matters more than comprehensiveness. Content that explains a concept in straightforward terms is easier for a model to parse and reuse than content that hedges, overcomplicates, or buries the insight beneath jargon. Distinctiveness also plays a role. Generic explanations that mirror what's already widely published offer generative systems nothing new to work with. Original perspectives, proprietary data, or unique frameworks are harder to replace and more likely to be referenced.

Authority has become more critical. Generative systems are trained to prioritize credible sources. Content that clearly establishes who wrote it, why they're qualified, and what evidence supports their claims carries more weight than anonymous or poorly attributed material. This aligns with Google's EEAT framework, but the stakes are higher. If a generative engine can't verify credibility, it simply won't use the source.

Structure also influences selection. Content organized logically with clear headers, concise explanations, and minimal ambiguity is easier for models to process. Dense paragraphs, unclear transitions, and vague conclusions create friction that generative systems avoid.

The result is that brands optimized purely for traditional SEO mechanics find themselves invisible in generative responses, even when their pages still rank in traditional search. Meanwhile, brands that focused on clear, credible, distinctive content are being cited and referenced, even when their direct traffic hasn't increased proportionally.

GEO doesn’t replace SEO. It builds on top of it.

If your site doesn’t rank today, it’s unlikely to be referenced tomorrow. Generative systems still rely heavily on the open web, and they still learn from indexed, crawlable, and credible sources. Technical SEO remains a foundation because both search engines and generative engines are ultimately optimizing for user experience and trust.

Site speed, clear structure, visible authorship, and strong EEAT signals all contribute to whether a brand is a strong source or not. A website that’s slow, unclear, or untrustworthy gives AI systems very little to work with.

But you can have a technically perfect site that ranks well for your target keywords and still be irrelevant in a generative context if your content isn't designed to be understood, extracted, and reused by systems that synthesize information rather than simply linking to it.

This is why the most effective approach treats SEO as the foundation and GEO as the layer that determines whether that foundation translates into actual influence. You need both. SEO gets you into the conversation. GEO determines whether you're quoted.

Now, you’re probably wondering what happens to your traffic?

Traffic hasn’t disappeared. Some queries still drive clicks, especially when users want and need to deep dive into a topic. This means that yes, we have fewer visits for certain types of content, but a stronger influence for brands whose ideas are consistently referenced.

The mistake is measuring this shift only through traffic metrics.

When your brand shows up inside an AI response, it may not generate an immediate click. But it does shape perception. It introduces you, it associates your name with a problem, a category, or a point of view. In many cases, that influence shows up later, in brand recall, in trust, in downstream decisions.

This chart illustrates how the total value driven by AI and LLM-based search is projected to surpass traditional organic search over time.

Don’t get me wrong, traffic still matters for your brand. It’s just no longer the only signal of impact. It’s actually a signal of brand authority.

Here you can see that while GEO drives a relatively small share of traffic, it is highly effective at generating conversions.

Search is no longer something you “go to.” It’s becoming something that shows up wherever you’re already working, planning, or thinking. And when answers start appearing there, the clicks matter less. You’re not staring at a results page anymore. You’re just being told something.

In these environments, brands aren’t discovered through search only. They’re introduced through how an idea is explained, which names feel familiar and credible in the moment an answer is given.

This changes how brands compete for attention. You're not trying to be the best result on a page someone scrolls through. And the brands that succeed here won't be the ones saying more.

Looking ahead, the advantage belongs to brands whose ideas travel well. Clear enough to be extracted. Distinctive enough to be attributed. Simple enough to be repeated without losing meaning.

That's not a writing problem. It's a strategic one.

The shift from SEO to GEO isn’t just a content problem. It’s an organizational one.

As generative systems increasingly shape how brands are discovered, referenced, and trusted, the real challenge for enterprise teams is execution. Turning GEO from a concept into an operating capability requires people who understand how content, technology, and distribution intersect across markets.

This is where execution speed matters. Some companies will spend the next year debating frameworks and waiting for clearer playbooks. Others will move faster by embedding the right expertise directly into their teams.

If you are interested in hiring, Athyna helps companies by connecting them with senior, globally distributed specialists who already operate at the intersection of SEO, GEO, content strategy, and AI-native growth. These are practitioners who don’t just understand how generative engines work in theory, but how to design, structure, and scale content that travels well across them in practice.

As search continues to evolve in 2026, the brands that win won’t necessarily be the loudest or the most optimized by old standards. They’ll be the ones with teams capable of adapting how visibility is earned, not just measured.

And that’s a capability worth building sooner rather than later.

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