A few years ago the whole game was ten blue links. You wanted to rank on page one, ideally position one, and you built your entire strategy around that.

Now a big chunk of people never see those links. They ask ChatGPT, Perplexity or Google's AI Mode a question and read the answer. No clicking, no scrolling through results. The model reads the web for them and hands back a paragraph.

That shift has a name now: GEO, generative engine optimization. The practice of getting your brand, your product and your content cited inside AI-generated answers.

I run an SEO and GEO consultancy and I built a tool in this space, LLM Pulse, so I have skin in the game. I will be upfront about that throughout. But this piece is not a sales pitch. It is the explainer I wish someone had handed me when clients first started asking "why do we not show up in ChatGPT?"

Let me try to make GEO make sense.

What GEO actually is

GEO is the work of increasing how often, and how favourably, an AI model mentions you when it answers a relevant question.

That is it. Strip away the acronyms and it is that simple.

The "generative engine" is any system that reads a question, pulls from the web or its training, and generates an answer instead of returning a list of links. ChatGPT, Perplexity, Gemini, Claude, Copilot, Google's AI Overviews and AI Mode. Different plumbing, same behaviour: they answer, they sometimes cite sources, and being one of those sources is the prize.

You will also hear "AI search optimization", "answer engine optimization", "LLM optimization" and a few others. They mostly point at the same thing. I use GEO because it has stuck, not because it is a perfect term.

How GEO differs from SEO

GEO grew out of SEO and shares a lot of its DNA. Good technical foundations, crawlable pages, clear content, real authority. None of that goes away. If your site is a mess for Googlebot, it is a mess for GPTBot too.

But the differences are real, and they change how you work.

SEO optimizes for a ranking. GEO optimizes for a mention. In SEO there is a position: you are third, you are seventh, you can measure the exact spot. In GEO there is no position one. Either the model names you in its answer or it does not. It is closer to a yes or no than to a ladder.

SEO gives you one result page. GEO gives you a different answer every time. Ask ChatGPT the same question twice and you can get two different sets of brands cited. The output is probabilistic. That drives SEOs a little mad at first, because it means you are tracking a distribution, not a fixed rank.

In SEO the user clicks through to you. In GEO they often do not. The answer is the destination. Sometimes there is a citation link and you get the visit. Often the user reads the paragraph, gets what they needed, and never lands on your site. That is uncomfortable, and it is the single biggest reason people resist GEO. Your win might be a sentence in someone else's answer rather than a session in your analytics.

SEO rewards the page. GEO rewards the consensus about you. Google ranks a specific URL for a specific query. A model, when it describes your product, is synthesizing everything it has read across the whole web. It is not quoting your homepage. It is summarizing the general sense of what the internet says you are.

That last point is the one most people miss, so let me spend a bit more time on it.

Why off-page matters more than you think

Here is the mental shift. In classic SEO you obsess over your own pages because that is what ranks. In GEO your own pages matter, but what other people say about you might matter more.

When a model answers "what is the best tool for X", it is not reading your carefully optimized landing page and taking your word for it. It is pulling from reviews, comparison articles, Reddit threads, forum posts, listicles, news, documentation and every other place your name appears. It builds a picture of you out of all of that.

So the questions that decide whether you get cited are off-page:

  • Are you mentioned on the pages that already get cited for your topic? The model tends to trust the same sources repeatedly. If the roundup articles and community threads it reads do not include you, you are invisible no matter how good your own site is.
  • Is what people say about you accurate and positive? A model will happily repeat a stale or wrong framing if that is the dominant one online.
  • Are you present where these tools actually look? For a lot of queries that means Reddit, Wikipedia, YouTube, industry publications and structured comparison content, not your blog.

This is why I tell clients GEO is closer to digital PR and reputation work than to on-page SEO. Being a citable source is mostly about existing, accurately and credibly, in the places the model already trusts. You do not win by shouting louder on your own domain. You win by becoming part of the consensus.

Your own content still counts. Clear, factual, well-structured pages that directly answer questions give models something clean to quote, and they help you own the queries about your own brand. But if you only work on-page and ignore the wider web, you will plateau fast.

How you measure GEO

This is where it gets practical, and where a lot of the early hype falls apart. You cannot improve what you cannot see, and for a while GEO was mostly vibes: someone asks ChatGPT about their category, screenshots the answer, panics or celebrates.

That is not measurement. That is one sample of a random process.

Real GEO measurement rests on a few metrics. None of them is perfect, and you want them together, not one in isolation.

Share of voice. Take a set of prompts that represent how real people ask about your category. Run them across the models, repeatedly, and count how often you get mentioned versus your competitors. That share, tracked over time, is the closest thing GEO has to a ranking. It answers the real question: in this conversation, how often does the AI bring me up compared to the others?

Citations. When a model links or names sources, which domains does it lean on for your topic? This tells you where the model actually gets its information, which is your target list for off-page work. If three sites get cited for every query in your niche, those three sites are your priority, full stop.

Sentiment. Being mentioned is not enough if the mention is bad. Sentiment tracks the words the model uses about you. "Reliable and well-supported" and "expensive with poor support" are both mentions. Only one of them helps. This is the metric people forget, and it is often the most actionable, because fixing a wrong or negative framing can move faster than fighting for raw visibility.

A couple of others sit around the edges. AI referral traffic, the actual visits and conversions that ChatGPT, Perplexity and Gemini send you, which you read in GA4 or Plausible. And crawler activity, whether GPTBot, ClaudeBot, PerplexityBot and the rest are actually fetching your pages, which is your leading indicator that you even have a chance of being included.

The honest caveat: none of these is as clean as a Google rank. The outputs move, the models change, and you are always working with a sample. Anyone who sells you GEO as a precise science is overselling. What you can get is a reliable trend, and a trend is enough to make decisions.

Where tools come in

You can do a version of this by hand. Write your prompts, run them across a few models every week, log the answers in a spreadsheet, tag mentions and sentiment yourself. For a single brand and a handful of prompts, that is a legitimate starting point and it teaches you how the models behave. I recommend everyone do it manually at least once.

It falls apart at scale. Running hundreds of prompts across five or more models, repeatedly, to get a stable signal, then tracking citations, sentiment and competitors over time, is not spreadsheet work. That is what the category of AI visibility tools exists to solve.

This is where I disclose it plainly again: I build LLM Pulse, so treat me as biased. It tracks share of voice, citations and sentiment across ChatGPT, Perplexity, Gemini and Google's AI surfaces, connects to GA4 or Plausible so you see the real traffic and sales those tools send, and shows which AI crawlers are hitting which pages. Pricing is public and starts at 49 € a month, which matters to me because a lot of this market hides behind a demo call. There is a 14-day trial if you want to look before deciding.

I am not going to tell you it is the only option, because that would break the one rule that makes any of this worth reading. Profound is deeper if you are a large enterprise with the budget to match. Peec AI is strong for agencies and teams. Otterly.ai is the cheapest honest way in. If you already pay for Ahrefs or Semrush, their AI visibility features are decent and already in your subscription, so start there before you add another tool. Pick what fits your size and your problem. The point is to measure, not to admire a screenshot.

Where to start

If you take one thing from this, make it the mindset, not the tooling.

Stop thinking only about your own pages. Start thinking about what the whole web says about you, because that is what the models read back to your future customers. Find the questions people ask in your category. Find the sources the models trust for those questions. Get yourself accurately and credibly into those sources. Then measure share of voice, citations and sentiment over time so you know whether any of it is working.

SEO was about being findable. GEO is about being repeatable: the thing the machine says when someone asks about your category, without you in the room.

Start showing up in that sentence before your competitor does.