Insights by Stefan von Gagern

What is GEO? Generative Engine Optimization, and how it differs from SEO

2026-09-24T00:00:00Z

Your buyers stopped opening ten browser tabs. They describe their problem to ChatGPT, Perplexity, or Google AI Overviews and get one answer back, naming a handful of companies. If your brand isn't in that answer, you are not in the running, and no analytics dashboard will tell you why.

That is the gap GEO closes.

At a glance

What it is: Generative Engine Optimization (GEO) is the work of getting a brand understood, cited, and recommended by AI answer engines: ChatGPT, Perplexity, Gemini, Copilot, and Google AI Overviews.
How it differs from SEO: SEO competes for a position in a list of links. GEO competes for a mention inside the answer itself.
What it is not: a technical trick or a format hack. Formats that worked in February were worth half as much by August 2026.
How it gets measured: not by rankings, but by whether you are named, how you are described, which sources get cited alongside you, and how that changes over a fixed set of prompts.
What actually works: content that answers the real questions your buyers ask, with specifics on the page, evidence behind it, and a consistent picture of who you are across the web.

What is GEO, exactly?

GEO is the practice of shaping your content, your entity data, and your public footprint so that AI answer engines understand your brand correctly and cite it when someone asks a question you should win.

Three parts of that definition matter.

Understand. Before an AI can recommend you, it has to know what you do, who you serve, and what proves it. That is entity work, and it extends well past your website.

Cite. The goal is a mention in the generated answer, ideally with a link. A page nobody links to and nothing corroborates rarely makes it in.

When someone asks. GEO is scoped to specific questions, not to abstract visibility. The questions that matter are the ones your buyers actually type before they contact you.

How is GEO different from SEO?

SEO optimizes for a ranked list of links. GEO optimizes for being inside a synthesized answer. That difference changes almost everything downstream.

	SEO	GEO
The prize	A position in the results	A mention in the answer
The unit	A page per keyword	A claim that can be quoted
Success looks like	Rank, clicks, impressions	Mentions, how you are described, share of voice against competitors
The click	The point of the exercise	Optional, and often absent
Stability	Rankings move slowly	Answers vary between runs and shift with every model update

Jakob Nielsen put the stakes plainly in his GEO guidelines: "Being ignored by AI is like being on page 5 of a Google SERP in the old days."

GEO does not replace SEO. The two overlap: clean structure, fast pages, and content that deserves to exist help in both. But GEO adds requirements SEO never had, and it drops one SEO can't live without, which is the click.

Why can't I just keep doing SEO?

Because the thing being optimized is no longer a list, it is an explanation. A model does not rank your page. It reads sources, builds an answer, and decides which names belong in it.

That has three consequences.

The research happens before the visit. By the time someone lands on your site, the AI has already framed the category, named some options, and possibly ruled you out. Your website is now the last check, not the first impression.

Being absent is invisible to you. A lost ranking shows up in a report. A missing mention in an AI answer shows up nowhere. You only find it if you go looking.

Your reputation is assembled from other people's pages. Models draw on PR coverage, LinkedIn, directories, reviews, and third-party write-ups, not just on what you publish. Which means GEO is partly off-site work.

Do format tricks work in GEO?

Not for long, and 2026 made that case better than any argument could.

In February 2026, Seer Interactive analyzed more than two million ChatGPT citations and found listicles dropping about 30 percent month over month. The listicles that held up shared traits: kept current, genuinely complete, with disclosed methodology and verifiable data.

Then came August 6, 2026. OpenAI moved Free and Go users to a new model and retuned the paid tiers. Peec AI measured the same day: listicle citations fell from 15.8 to 7.8 percent, comparison pages lost about a third, and vendor product pages rose to 16.4 percent, overtaking the lists. The model had started going straight to the source with the specs and prices.

The pattern is consistent. Every model update pushes the engines closer to what a good advisor would do: skip the third-party ranking, check with the provider who actually knows. Updates don't devalue substance. They devalue shortcuts.

How do you measure AI visibility?

Not with rankings, because there are none. You measure trends across a fixed set of prompts, run repeatedly.

Are you named? In how many of the questions that matter to your business.
How early and how prominently? First recommendation reads very differently from a footnote.
How are you described? Correct positioning matters as much as presence. Being cited as the wrong kind of provider is its own problem.
Which sources are cited? These are the pages doing the work, and often they are not yours.
Who appears next to you? Share of voice against the competitors the engines consider comparable.

Run the same prompt set on a schedule, and the movement becomes visible. Run it once, and you have an anecdote. This is what a GEO audit establishes before any optimization starts, because without a baseline you cannot prove that anything you did worked.

What actually gets a brand cited?

Start with the questions, not the format.

Write the answers your buyers are actually looking for. "Is this worth it for a 50-person company?" "What does it cost, realistically?" "How is A different from B?" Each of those deserves a page that answers it completely, in plain language, with the specifics on the page. Prices, limits, prerequisites, real examples. The pages that won in August were the ones with the facts on them. That is what GEO-ready content looks like.

Make your entity unambiguous. Same name, same role, same specialization, same location, everywhere you appear. Models assemble an identity from scattered mentions, and inconsistency costs you.

Date it, source it, maintain it. Publication dates, disclosed methodology, named sources, regular updates. This is exactly what separated the surviving listicles from the dead ones, and it happens to be what a skeptical human needs in order to believe you.

Work the channels beyond your site. PR, LinkedIn, customer stories, industry press. Third-party corroboration is often what tips a model toward naming you.

Build the habit in your team. GEO is not a project that finishes. The engines keep changing, so the work is a routine, not a launch. That is why enablement usually outlasts consulting alone.

Frequently asked questions

Is GEO the same as AEO or LLMO?

Effectively yes. Generative Engine Optimization, answer engine optimization, and LLM optimization describe the same work with different labels: getting understood and cited by AI systems that answer questions directly. GEO is the term that has stuck in most of the industry.

How long does GEO take to show results?

First movement often appears within weeks, usually on specific questions where a clear, well-evidenced page was missing. Durable results take months, because authority and consistency accumulate slowly and the engines keep shifting.

Does GEO still require SEO?

Yes, in the sense that both reward a well-structured, crawlable, genuinely useful site. What changes is the target: SEO aims at a ranked list, GEO aims at being quoted in an answer. Dropping SEO to chase GEO would be a mistake.

Can small companies compete in AI answers?

Often better than in classic search. Depth beats budget here: a specialist with real, specific, well-documented expertise on a narrow question can be the best available source, and models reward that. Broad, generic pages from large brands frequently lose to it.

Where does GEO work start?

With measurement. Which questions matter to your business, where do you stand on them today, who gets named instead of you, and why. Everything else is guesswork until that baseline exists.

What actually works in GEO: two hacks died this summer, but one lever survives every update

2026-09-15T00:00:00Z

I hear one question in almost every conversation, in some form or other: "What's the most important GEO lever right now?"

I get why people ask. People want the one trick that works today. Build lists. Show up on Reddit. Add tables. Something they can kick off on Monday.

The problem is that the answer to that question has a shelf life of a few months, sometimes a few days. August 2026 proved that more clearly than almost anything before it. So here is a look at both sides: what just broke, and what doesn't.

At a glance

What happened: Two of the year's most popular GEO tips, listicles and a Reddit presence, lost most of their effect within a few days in August 2026.
Listicles: After the ChatGPT update on August 6, their share of citations fell from 15.8 to 7.8 percent, according to Peec AI. Vendor product pages overtook them.
Reddit: In mid-August, Reddit's share of ChatGPT citations dropped from 3.83 to 0.52 percent, according to Promptwatch. That is a decline of 86 percent. Nobody knows the cause.
What survived: Content that is current, complete, and backed by evidence, and pages that actually contain the answer.
The lever: Content that answers real customer questions. Formats and platforms are a thermometer, not a strategy.

Why don't listicles work in ChatGPT anymore?

Because the new ChatGPT model would rather get facts straight from the vendor than from third-party rankings. Early this year, the advice was simple: if you want ChatGPT to cite you, build listicles. "The 10 best tools for...," "7 vendors compared." For a long time, the citation data backed that up.

Then came August 6, 2026. That day, OpenAI moved Free and Go users to its new GPT-5.6 model and retuned the Plus and Pro models. Peec AI measured what happened to citations the same day:

Listicles fell from 15.8 to 7.8 percent of all citations. More than half gone, in a single day.
Comparison pages lost about a third, dropping from 9.1 to 6.2 percent.
Vendor product pages reached 16.4 percent, which put them ahead of the lists.

If you rebuilt your content plan around lists this spring, you now have six months of work sunk into a format that one model update devalued overnight.

The lesson: a format is not a lever. It is a snapshot of what a model happens to prefer right now.

What happened to Reddit in ChatGPT?

Reddit practically vanished as a ChatGPT source in mid-August, and nobody knows exactly why. Building a forum presence, seeding threads, joining discussions: that was the second big GEO tip of the spring.

According to Promptwatch data reported by Search Engine Land on August 19, Reddit accounted for 3.83 percent of ChatGPT citations between July 18 and August 7. Between August 14 and 17, that share was down to 0.52 percent. An 86 percent drop within days, with no official announcement.

The uncomfortable part is that there is no explanation. Promptwatch itself says the data shows when it happened, not why, and explicitly calls the results provisional. Maybe a change in how sources are selected, maybe a side effect of the new model.

This is what a dying hack feels like from the inside: at some point you see fewer mentions, and you have no idea what is going on.

The lesson: if your visibility depends on one platform, it depends on something OpenAI can change on any given Thursday.

Which content survived the updates?

Content with substance survived: content that is current, complete, and backed by evidence. Not every list crashed, and not every source lost ground.

Back in February 2026, Seer Interactive analyzed more than two million ChatGPT citations and found an early listicle decline of about 30 percent month over month. What stood out was which lists kept getting cited: the ones kept up to date, genuinely complete with 10 to 20 entries instead of a token five, with disclosed methodology and verifiable data.

In August, the winners were the pages that actually contain the answer: vendor pages with real specs, real prices, and real use cases.

The pattern behind it never changes. The models keep getting better at finding the source that truly answers a customer's question. Every update moves them a little closer to what a good advisor would do: skip reciting someone else's ranking and go straight to the vendor who should know.

The lesson: no model update devalues substance. It devalues shortcuts.

What actually works in GEO?

Content that answers real customer questions. I know that sounds unexciting. It is the most boring sentence in all of GEO. It is also the only one I have never had to take back since I started doing this work.

Here is what that means in practice, in three parts.

Start with the questions, not the format

What do your customers ask AI before they contact you? Not your keywords, but the real questions: "Is X worth it for a 50-person company?" "What does Y realistically cost?" "How is A different from B?" Each of those questions deserves a page that answers it completely. You can measure which questions matter for your brand, and that is exactly where a GEO audit starts.

Write the answer down. All of it

Numbers, prices, limits, prerequisites, examples. No "measurably more efficient," no "tailored solutions." The pages that won in August were the ones with the facts on them. That is not a trick. It is the absence of one. I describe what that kind of writing looks like on my SEO and GEO copywriting page.

Keep it current and verifiable

Add a date, disclose your methodology, name your sources, update regularly. That is exactly what separated the lists that survived from the ones that died. And it happens to be exactly what a skeptical human needs before they believe you. To keep it from resting on one person, build it into your team's routines. That is what content enablement is for.

To be fair: watching formats and platforms still makes sense. As a thermometer. Not as a strategy.

Conclusion

Two hacks, one summer, both gone. Anyone who chased them lost more than the time they invested. They also lost the time that never went into content built to last.

What remains is inconvenient and boring: content that genuinely helps your customers decide. Backed by evidence instead of claims, kept current instead of built once and forgotten.

Hacks expire. Answers don't.

Ready for a GEO check?

Wondering whether GEO matters for your business and whether it would pay off? In a free 15-minute GEO quick call, we'll look at what GEO could do for your brand, what role AI search plays in your industry, and where it makes sense to start. This post first appeared in the GEO-Briefing, my LinkedIn newsletter on AI visibility.

→ Subscribe to the GEO-Briefing on LinkedIn (in German)

Frequently asked questions

Do listicles still work for GEO?

Not the way they used to. After the ChatGPT update on August 6, 2026, the listicle share of citations fell from 15.8 to 7.8 percent, according to Peec AI. Lists that stay current, complete, and backed by disclosed methodology still get cited. Thin rankings with only a few entries lose.

Why does ChatGPT barely cite Reddit anymore?

Nobody knows yet. According to Promptwatch, Reddit's share of ChatGPT citations fell from 3.83 to 0.52 percent in mid-August 2026. The data shows when it happened but not why, and Promptwatch considers it provisional. The one certainty: visibility that depends on a single platform can disappear at any time.

What content does ChatGPT prefer to cite?

Pages that actually contain the answer to a specific question. After the August update, vendor product pages reached 16.4 percent of citations, putting them ahead of listicles. What counts are hard facts like specs, prices, and use cases, plus freshness and verifiable sources.

What is the most durable GEO lever?

Content that answers your own customers' real questions completely and with evidence. Formats and platforms change with every model update. Substance doesn't. Watching formats still makes sense, but as a measuring tool, not as a strategy.

Why AI visibility belongs on the leadership agenda, and how to get it right

2026-07-16T00:00:00Z

Sometimes a conference comes down to one sentence. For me it was this one, which Nadine Wolanke, Managing Director of Adobe Central Europe, brought back from a conversation with a CMO: "We're running as fast as we can, but we really don't know where we're going" (translated from German).

She says she hears that from a lot of customers right now, whether they are large enterprises, midsize companies, or startups. I see the same thing in my GEO workshops. Everyone is experimenting, everyone is building pilots, everyone is testing tools. But the strategic question is framed too narrowly. The question is not whether your company uses ChatGPT. It is how AI systems understand, categorize, and recommend your brand. Answer that, and you have a direction. Skip it, and you are just running.

At a glance

What this is about: AI visibility, meaning how visible a brand is in AI answers (ChatGPT, Perplexity, Gemini, Google AI), has become a leadership job, not an add-on to SEO.
The occasion: Adobe Summit 2026 in Munich: a press briefing, the keynote, and interviews with Adobe CTO Hartmut König and AI Evangelist Julian Kramer.
The numbers: AI traffic to retail sites up 393% in Q1 2026, traditional organic traffic declining, and according to Adobe, visitors from AI search convert significantly better.
The core message: Visibility decides relevance, and relevance decides growth. A brand that is invisible in search and discovery stays invisible as a brand.
What to do: Measure first, then act. Substance over AI content mills, machine-readable product facts, quick wins, new KPIs, and a learning loop.

The numbers: is the shift already here?

Yes. The shift is here, not "coming soon." In Munich, Adobe presented data that should end every debate about whether to wait or get started. AI traffic to retail websites grew 393 percent in the first quarter of 2026, while traditional organic search traffic is declining. Adobe also reports that 80 percent of consumers make decisions based on AI-driven recommendations in 40 percent of their searches. And according to Adobe, visitors who arrive at a website from an LLM convert significantly better, because they finished their research long before they clicked. Adobe cited 46 percent on stage at the Summit. Its public report puts the conversion advantage over other sources at about 31 percent.

Hartmut König summed it up in our conversation: "By the time they come to your website, they've basically already been through the awareness and consideration phase, and that's why they convert better" (translated from German).

At the morning briefing, Julian Kramer described the same development from a brand's point of view, and he didn't sugarcoat it: "The traffic that still comes is extremely high-quality, but there's less and less of it" (translated from German). That is the new reality: fewer visitors, and the ones who do arrive have already made up their minds. The interesting question is no longer "How do I get clicks?" It is "What happens in the phase before that, when the AI shapes the opinion?"

How is the customer journey changing?

It is turning inside out. The traditional journey of awareness, consideration, and conversion is falling apart. In our interview, König described what is replacing it: "Today you basically have a journey that goes: I have a problem, I explain the problem to the LLM, the LLM orchestrates the answer, and then I arrive at a solution. That's a completely different journey" (translated from German).

People no longer search for "best running shoes." They describe their injury history and ask for a recommendation for the right shoe. The consideration phase happens inside the AI, before anyone visits a website. The website doesn't disappear, but its role changes. It is no longer where the opinion forms. It is the final proof of trust just before the decision.

König showed how big Adobe thinks this shift is with a comparison I didn't expect to hear so bluntly: he put its impact on par with the arrival of the smartphone.

"It used to be about being found on Google. Today it's about being understood by an AI. And tomorrow, that is exactly what will decide which brands we choose."

Adobe, brand visibility session, Adobe Summit 2026 (translated from German)

Why is this a leadership priority and not an SEO task?

Because AI visibility can't be delegated away. That was the most important thread running through the day, and there are three reasons for it.

It is about brand leadership, not rankings. König talked about "new places where people get advice" (translated from German): AI chatbots that explain, compare, and recommend brands, outside the brand's own control. His core message: "If we're invisible in search and discovery, we'll stay invisible as a brand" (translated from German). A brand that gets categorized wrongly there doesn't lose a ranking. It loses control over how its own story gets told.
The knowledge it takes sits deep inside the company. LLMs need verified, machine-readable facts: product data, differentiators, use cases, prices. Julian Kramer made clear that this is exactly the content traditional brand communication has been missing, and that the bigger the brand, the less information its website often contains. No agency can invent these facts. They come from product management, engineering, sales, and service. Only leadership can bring them together.
AI is an operating model, not a pilot project. König's image for it: "AI is not the one muscle that can suddenly lift something, but the interplay of the whole organism" (translated from German). AI becomes the central nervous system that connects data, content, and processes. Pilots fail one after another because they lack exactly that nervous system. The next step is moving from pilot to transformation, and that decision doesn't get made at the team level.

Why are hidden champions sitting on a huge opportunity?

Because AI answers can give them a reach they never built through marketing. This was my favorite moment of the day. König talked about German mechanical engineering companies that lead their global markets that never learned how to be visible on Google, and never had to. His scenario: a researcher in Hong Kong or Kuala Lumpur asks an AI for a highly specialized solution. If the global market leader from the Black Forest doesn't come up, she buys from a competitor, without a single website visit ever taking place.

The flip side is an enormous opportunity, which König called "a gigantic opportunity, especially for our market" (translated from German): "If they get it right, these brands will gain a visibility they never would have gotten through branding" (translated from German).

Instead of pouring millions into ads, niche suppliers can "inoculate" the models with the expertise of their engineers: describe their competitive advantages so that an AI understands them and recommends them, the way a good advisor would. For Germany's midsize companies, this may be the biggest marketing opportunity in years.

How do you get it right? Five steps

1. Measure first, then act

König quoted a management classic at the Summit: "You can manage what you can measure" (translated from German). Where does your brand show up in AI answers today, for which questions, and next to which competitors? You can start with a small Semrush subscription. Larger setups use tools like Adobe LLM Optimizer to test prompts against the models dynamically.

2. Substance over AI content mills

Generic AI-generated content doesn't solve the visibility problem, because generic content gets filtered out. König in our interview: "You can't shortcut the work of developing the content itself" (translated from German). The workflow that works: interview your experts and engineers, write it up the way a journalist would, publish it, and only then have AI turn it into 15 versions for LinkedIn, trade publications, and other channels.

3. Make product facts machine-readable

Sizes, weights, specs, prices, use cases: get them out of the PDF behind the login and away from pure marketing speak. The advice I give more often than any other fits here perfectly: say on your website what you actually do. "Pure passion" in the hero section helps neither people nor machines.

4. Grab the quick wins

Maintain your Wikipedia article, pull existing white papers out of the hidden corners of your website and make them accessible to LLMs, and check your presence on the platforms that matter. It costs little and works fast.

5. Set new KPIs

Julian Kramer's farewell to the old way of measuring: "This whole number-go-up thing is basically over" (translated from German). Qualitative metrics replace traffic, clicks, and likes: mentions and how you are positioned in AI answers, share of voice against competitors, and conversion of pre-qualified traffic.

What ties it all together?

A learning loop. Measure, find the gaps, close them, measure again. That loop needs someone who owns it, which is exactly why this belongs with leadership.

"In the age of agents, visibility determines relevance, and relevance determines growth."

Closing of the brand visibility session, Adobe Summit 2026 (translated from German)

Conclusion

The tools exist, the numbers are clear, and the rules of the game are known. What many companies still lack is the decision to take real ownership of AI visibility instead of treating it as an SEO add-on. The brands that make that decision in 2026 will become tomorrow's default answers.

Ready for an AI visibility check?

Book your free GEO quick call, and let's find and prioritize the moves that matter most for your brand. By the way, this report first appeared in GEO-Briefing, my LinkedIn newsletter on AI visibility, which is published in German.

→ Subscribe to GEO-Briefing on LinkedIn (in German)

Frequently asked questions

What is AI visibility?

AI visibility (often called Generative Engine Optimization, or GEO) describes how visible a brand is in AI answers: whether ChatGPT, Perplexity, Gemini, or Google AI name the brand for relevant questions, categorize it correctly, and recommend it. Unlike SEO, it is not about rankings. It is about being understood and cited by AI systems.

Why is AI visibility a leadership priority and not an SEO project?

Because it is about brand leadership rather than rankings. Because the knowledge it takes (product facts, differentiators, prices) sits deep in product management, engineering, and sales, and only leadership can bring it together. And because AI is a company-wide operating model, not an isolated pilot project. These decisions don't get made at the team level.

Do visitors from AI search really convert better?

Yes. According to Adobe, visitors who reach a website through an LLM convert significantly better, because they have already completed awareness and consideration inside the AI. Adobe cited 46 percent on stage at the Summit. Adobe's public report puts the conversion advantage over other sources at about 31 percent. So the traffic gets smaller, but its quality goes up considerably.

How do you get started with AI visibility?

Measure first, then act: where does your brand show up in AI answers today, for which questions, and next to which competitors? Then produce substance instead of churning out AI content, make product facts machine-readable, grab quick wins like Wikipedia and white papers, and set new, qualitative KPIs. And a learning loop ties it all together: measure, close the gaps, measure again.