A traveller in Paris is planning a trip to Mauritius. Two years ago they opened Google, typed "boutique hotels Mauritius west coast", and worked through a page of blue links. Today a growing number of them open ChatGPT, Claude, Perplexity, Gemini, you name it, instead and ask it properly, in a full sentence, the way you would ask a well-travelled friend. They get back a short answer naming three or four hotels, with reasons.
Your business is either in that answer or it is not. There is no page two.
That is the entire proposition of generative engine optimisation, and it lands harder in Mauritius than in most markets. A large share of what this island sells (hotels, villas, property, financial and offshore services, ICT and BPO capability) is sold to someone who is not standing in front of it. They are in France, the UK, South Africa, India or the Gulf, researching from a distance, and they cannot walk past your building or ask a neighbour. Their entire impression of you is assembled from what they can find online. When the thing assembling it stops being a list of links and becomes a paragraph of prose that names three companies, the stakes of being named go up sharply.
This guide covers what the research actually supports about getting into those answers, which platforms earn citations, where the industry is overselling, and what a GEO partner does that you probably cannot do in-house.
First, the size of the shift
The evidence that generative answers are absorbing clicks is now good, and it no longer rests on vendor blogs.
Pew Research tracked the real browsing behaviour of 900 US adults across nearly 69,000 searches. When an AI summary appeared, people clicked a link on 8% of visits, against 15% without one. Only 1% clicked a link inside the summary itself. That is the honest picture: the summary answers the question, and the visit ends.
Better still, researchers at the Indian School of Business and Carnegie Mellon ran an actual randomised experiment, hiding AI Overviews from a control group of Chrome users. Organic clicks fell 39.8%, and zero-click sessions rose 34.5%. Crucially, they also tested Google's public defence, which is that the lost clicks were low-quality ones nobody wanted anyway. It did not hold: bounce rate, back-button rate and time on page showed no meaningful difference between the groups. The clicks that disappeared were ordinary, useful clicks.
Set against that, the counterweight. Actual AI referral traffic is still small. Conductor data across 3.3 billion sessions put AI referrals at roughly 1.08% on average, though with an eleven-fold spread between industries.
So read the position correctly, because a lot of people are reading it wrong in both directions. AI search is not yet where your traffic comes from. It is already where your reputation gets formed. The visit may never happen; the recommendation happens regardless, and it happens whether or not you have participated.
There is a timing argument here too. Neil Patel's team surveyed 350 marketing leaders on GEO adoption and found small businesses at 8%, mid-market at 21%, enterprise at 16%. Most companies have not started. In a market the size of Mauritius, where a category might hold a dozen serious competitors rather than ten thousand, being early is not a marginal advantage. It is most of the game.
What generative engines actually reward
The term GEO comes from a real academic paper, not a marketing blog. Aggarwal and colleagues at Princeton and Georgia Tech published "GEO: Generative Engine Optimization" at KDD 2024, building a 10,000-query benchmark across 25 domains and testing nine ways of rewriting a page to see which earned more visibility in a generative answer.
The results are quoted badly almost everywhere, so here they are properly.
| What you change | Visibility lift |
|---|---|
| Adding relevant quotations | +40.9% |
| Adding statistics | +30.6% |
| Improving fluency and clarity | +28.0% |
| Citing your sources | +27.5% |
| Adding technical terms | +17.6% |
| Sounding authoritative | +10.4% |
| Keyword stuffing | -8.3% |
Three things matter here.
The winners are all forms of substantiation. Quotations, statistics and citations take the top three places. The model is not rewarding you for saying a thing. It is rewarding you for backing it up in a way that can be lifted, attributed and trusted. When a language model builds an answer, a passage carrying a specific number and a named source is simply more useful to it than a paragraph of confident assertion. That mechanism is more transferable than the exact percentages, which came from 2023-era models in a lab-built engine.
Keyword stuffing actively hurts. The most durable finding in the paper, and it replicated on Perplexity, a real deployed engine, at -9.1%. The tactic search engines learned to ignore, generative engines punish.
Combinations beat single tactics. Fluency plus statistics together reached 35.8%, more than either alone.
One under-quoted finding deserves your attention if you are not the biggest name in your category. When every source optimises, the paper found visibility redistributing downward: the fifth-ranked source gained up to 115% while the top source lost around 30%. A generative engine conditions on your content, not on your backlink profile. Being smaller is less disqualifying than it used to be, which is the best news in this article for most Mauritian businesses.
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Being talked about now beats being linked to
This is the finding that should reorganise your budget.
Ahrefs studied 75,000 brands to see what correlated with being mentioned in Google's AI Overviews. Brand web mentions scored 0.664. Backlinks scored 0.218.
Patel's team came at it from a different angle: over 100 consumer questions put to ChatGPT, the results handed to a statistician, 82 possible factors tested. Six correlated strongly. The top two were relevancy at 0.91 and brand mentions at 0.87, then reviews at 0.61 and authority at 0.52. His summary: "the big 2 factors to focus on are brand mentions and relevancy."
Two independent studies, two methods, one answer. Being talked about across the web predicts AI visibility better than being linked to.
That reads like a tactical note. It is closer to a strategic reversal. Link building is a procurement exercise, and plenty of agencies in this market have quietly sold it as one. Being mentioned is a consequence of having done something worth mentioning, and no budget shortcuts that. Both findings are correlational, and reverse causation is live: well-known brands get mentioned and get cited partly because they are well-known. Treat this as strong direction, not physics.
The part every checklist skips
Everything above assumes something most GEO advice never says out loud.
It assumes you have published something.
"Every GEO tactic in circulation is a way of improving how a model reads your content. None of them create the content. If you do not have a content strategy putting real, truthfully helpful material out around the topics people are actually searching, thoroughly enough to be worth quoting, then how will the AI even know you exist, let alone that you are great at anything? The model is not withholding your name. It has nothing to withhold."
Noor Sheriff, Founder, Lean Search
The evidence lines up behind this uncomfortably well.
Patel's team analysed 1,000 prompts to see what type of content actually gets cited. Lists took 48%. Step-by-step guides took 17%. FAQs took 4%. Definitions took 3%. Opinion and editorial content, the format most businesses default to the moment they decide to "do thought leadership", took 3%. His read is worth borrowing: "That is not a content quality problem. It is a format allocation problem."
Domain age says the same thing from another direction. Across 1,000 ChatGPT prompts carrying citations, sites under a year old accounted for 2.1%. Sites over ten years old accounted for 51.4%. You cannot fake tenure, and what tenure mostly represents is a decade of accumulated, indexed, referenced material. That is a content strategy, observed over a long enough window.
And the failure mode is not silence. In that same 82-factor study, 27.41% of ChatGPT's answers were simply wrong, at one point recommending Moz and HubSpot as advertising agencies. When a model lacks good grounding for a question, it does not decline to answer. It reaches for whoever it has heard of. If that is not you, the gap gets filled by a competitor, or by a business that does not even do the thing you do.
Thoroughness is the operative word, and it is not a style preference. The paper's three highest-lift tactics all describe depth: quote real sources, carry real numbers, cite where they came from. None of that is available to a thin page. You cannot add a compelling statistic to an article that had nothing to measure. A three-hundred-word service page written to tick a box gives the model nothing to quote, which means it gives the model no reason to mention you.
:::promo{href="/seo" kicker="SEO copywriting" cta="See our SEO & copywriting approach"} Content thorough enough to be worth quoting. Specialist writers per industry, briefed on the questions your buyers actually ask, writing in your tone. Not a hundred AI-generated articles a model has no reason to cite. :::
Which platforms actually earn citations
Here is the finding most businesses find hardest to accept: your own website is one of the weakest citation sources available to you.
Patel's analysis of 1,000 prompts across ChatGPT, Gemini, Grok and Perplexity rated user-generated content and forums as a Very High citation source, blogs and news as High, and branded sites as Low. His conclusion: "Brands have invested heavily in owned content that AI systems cite infrequently."
Profound's analysis of 680 million citations shows where the models actually go:
| Platform | ChatGPT | AI Overviews | Perplexity |
|---|---|---|---|
| Wikipedia | 7.8% of all citations | high | high |
| 1.8% | 2.2% | 6.6% | |
| YouTube | present | 1.9% | 2.0% |
Read those as shares of every citation across the whole web, which is why they look small. Within each platform's ten most-cited domains, Wikipedia takes 47.9% of ChatGPT's and Reddit takes 46.7% of Perplexity's. A handful of platforms carry an enormous share of the world's AI answers.
So a serious GEO programme publishes in more than one place. The channel data is blunt about this. Patel tracked 15 brands and found those publishing to one channel per month earned 10 to 15 AI citations monthly; three to four channels earned 18 to 25; six channels earned 45 to 50; nine channels earned around 70. Roughly linear, and roughly a five-fold difference between doing one thing and doing many.
Where that points for a Mauritian business:
- Third-party media and digital PR. When Patel scored trust signals across six AI platforms, third-party citations scored 4.5 to 4.8 out of 5 on every single one. It was the only universal signal in the dataset. Nothing else works everywhere. For an operator here that means the local and regional business press, the trade titles your category reads, and the publications your source markets read, which for tourism and property means French, British and South African outlets far more than Mauritian ones.
- Reddit and forums. Uncomfortable for most boards, and unavoidable. Perplexity draws 6.6% of all its citations from Reddit. Travellers ask r/travel about Mauritius constantly, and those threads are being read back to your future guests. You cannot astroturf this; it gets detected and it deserves to. You can participate honestly, answer questions in your actual area of expertise, and be a useful presence under your real name.
- YouTube. Ahrefs' late-2025 work found YouTube mentions among the strongest correlations with AI visibility across ChatGPT, AI Overviews and AI Mode. For a hotel, a villa estate or a development, this is also the format where the product is the argument.
- Wikipedia, indirectly. The single most-cited source on the internet for ChatGPT, and you may not write your own entry. What you can do is become notable enough, and sourced well enough in independent press, that someone else does.
- Reviews. Reviews were the third strongest factor in the 82-factor study at 0.61. In hospitality this is already your operational reality; the change is that it now feeds the recommendation engine as well as the booking decision.
- Your own site. Still the foundation, because it is where the substance lives and what everything else points at. Just not sufficient on its own, which is the part the "Low" rating is telling you.
One warning. Citation shares are wildly unstable. Patel tracked 75,000 ChatGPT prompts and watched Reddit collapse from roughly 8% of responses in early September to under 2% by mid-month, inside a week, never recovering. Any strategy resting on a single platform's current behaviour has an expiry date on it. Spread is not just upside. It is insurance.
Not every engine works the same way
Treating "AI search" as one channel is a mistake. Semrush analysed 5,000 keywords and 150,000 citations to measure how far each engine's sources overlapped with Google's top 10 organic results.
- Perplexity: 91% domain overlap. Effectively re-skinned organic search. If you rank, you are in the running.
- AI Overviews: 86% domain overlap, though URL-level overlap drops to 67%.
- AI Mode: 51%. Meaningfully divergent.
- ChatGPT: the weakest of the four, and Bing-leaning rather than Google-leaning.
The practical read: strong organic rankings buy you most of Perplexity and most of AI Overviews almost for free. This is why GEO is not a replacement for SEO and why anyone selling it as a separate product is selling you something. ChatGPT is the one that needs its own thinking, and it happens to be the one with the users.
llms.txt: worth doing, worth understanding
llms.txt is a plain text file at the root of your site offering a clean, structured map of your content for large language models. Jeremy Howard proposed it in September 2024. The industry has spent the time since selling it as a way to get cited by AI.
That claim does not survive contact with the data, and you should hear this from your own agency rather than find out later.
Ahrefs examined 137,210 domains. 97% of valid llms.txt files received zero requests. AI retrieval bots made up 1.1% of the requests that did arrive, while SEO audit tools made up 21.7%. In their words, Slackbot fetched these files more often than PerplexityBot did. Most damning: no AI bot ever requested an llms.txt URL that returned a 404, which means nothing out there is looking for one. An independent CDN audit across 4,685 hosts found the same 1%. Google's documentation now states plainly that "you don't need to create new machine readable files, AI text files, or markup to appear in these features", and John Mueller compared llms.txt to the keywords meta tag, which is about as dismissive as Google gets.
So why does it belong in this guide at all?
Because the file was never designed for the job the SEO industry gave it, and it is rather good at the job it was designed for. Howard's proposal targets inference-time and agent use cases: an AI agent that needs to read and act on your content right now, rather than a search index deciding who to cite. That world is arriving quickly. Chrome's Lighthouse now ships an "Agentic Browsing" audit that checks for llms.txt. Adoption among the top 10,000 sites went from 1.04% to 5.61% in twelve months. When your future customer's assistant is booking the room rather than recommending it, the machine-readable version of your site stops being decorative.
The honest verdict, which is the one we give clients: ship it, budget almost nothing for it, and do not let anyone bill you for it as a citation strategy. It is an afternoon of work and a sensible hedge on where agents are going. It is not why you will get cited this year, and an agency quoting you a line item for llms.txt as an AI visibility service is either behind the research or counting on you not to read it.
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What else is being oversold
While we are here, two more.
Schema markup does not appear to lift AI citations. Ahrefs ran a difference-in-differences study on 1,885 pages that added JSON-LD against 4,000 matched controls. AI Mode moved 2.4%, ChatGPT 2.2%, both statistically indistinguishable from zero, and AI Overviews actually declined 4.6%. A separate controlled test placed prices in JSON-LD only, then asked five systems to read them. None could. They read visible HTML. That explains the null result and gives you the rule: if you want a model to know something, put it where a human can see it. Keep your schema, because it still earns rich results in classic search and still helps Bing's index understand you. Just do not buy it as GEO.
Check the source on any number you are quoted. This field has a circular sourcing problem, with AI-written stat roundups citing each other. The popular "GEO boosts visibility 40%" is routinely credited to Neil Patel; it is from the academic paper and appears nowhere on his site. "Wikipedia is 47.9% of ChatGPT's citations" is a denominator misread, as covered above: 7.8% is the real figure. And the claim that AI traffic converts many times better than organic is genuinely unsettled. Patel's 60-campaign dataset shows 5.97% against 0.72%, but a larger working paper covering 973 ecommerce sites and more than 50,000 ChatGPT transactions found organic converting 13% higher. Nobody knows yet. Anyone who tells you they do is selling.
What a GEO partner actually does
Most of what you have just read is not executable by a marketing manager with a content calendar and a spare afternoon, which is the honest case for a partner rather than a pitch for one. The work splits into two halves that have to be done by the same people, and usually are not.
Producing content worth citing. This is the larger half and the one that gets skipped, because it is the expensive one. It means finding the questions your buyers actually put to the models, rather than the keywords a tool suggests. It means building material with enough depth to be quotable, which in practice means original numbers, named sources, real quotations and genuine specificity, because those are the three highest-lift tactics in the founding research and none of them are available to a thin page. It means allocating format deliberately, since lists and step-by-step guides take 65% of citations between them while the opinion piece your CEO wants to write takes 3%. And it means someone with actual subject knowledge in the room, because thoroughness is not a word count. Generating a hundred articles with AI is the single most common GEO mistake in Patel's survey of 500 marketers, and it fails for a reason that should be obvious: a model has no reason to cite another model's output back to itself.
Getting that content in front of the engines. The distribution half. Digital PR and third-party placement, because third-party citations are the only signal that scores highly on every platform. Multi-channel publishing, because nine channels earn roughly five times the citations of one. Technical and organic foundations, because 86% to 91% domain overlap means your Perplexity and AI Overviews visibility is mostly bought by ranking. And measurement, which barely exists yet: only 12% of marketers say they are confident they can measure AI visibility at all, and 26% have no measurement in place. You cannot manage what you are not tracking, and tracking this requires tooling most businesses will not buy for themselves.
The last thing a partner is for is patience, which sounds soft until you see the numbers. Patel tracked 20 sites running SEO and GEO together and found no movement in LLM citations through week three, then steep acceleration from week four, overtaking the SEO curve by week six. Most teams check at four weeks, see a flat line, and cut the budget one week before it moves. Part of what you are paying for is someone who knows the curve and will hold the line on it.
The point of all of it
GEO is not a new discipline that replaced SEO. It is the same discipline judged by a new reader, and that reader has different taste. It wants substantiation over assertion, mentions over links, depth over keyword coverage, and visible prose over technical markup. Keyword stuffing, which search engines learned to ignore, generative engines actively punish.
But every tactic here is downstream of something none of them supply. A model cannot cite a page you never wrote. It cannot verify expertise you never demonstrated in public. It cannot recommend a business it has never encountered. Strip out the acronym and GEO asks a question that would have been fair in 2010: is there anything here worth repeating? The difference is that the thing deciding now reads everything, forgets nothing, and answers your buyer directly.
For Mauritius, that is an opening rather than a threat. Our categories are small, adoption is at 8% among small businesses, and generative engines reward the quality of what you publish rather than the size of your link budget. The businesses on this island that start publishing seriously now will be the ones the models name in three years, and the ones who wait will be explaining to their board why a competitor is the answer to every question in their category.
If you want to know how your business currently reads to the citation layer, what your buyers are asking the models today, and what would have to exist for you to be the answer, that is the work we do. Read more about our approach to SEO for AI engines and SEO, or book a strategy call and we will show you what the models say about you right now.
Sources. Aggarwal et al., GEO: Generative Engine Optimization, KDD 2024. Ahrefs: brand mentions and AI Overviews (75,000 brands, May 2025), AI brand visibility correlations (December 2025), llms.txt request analysis (137,210 domains, June 2026), and their JSON-LD difference-in-differences study (May 2026). Neil Patel / NP Digital: ChatGPT recommendation ranking factors, AI citation frequency by content type, top sources AI tools pull citations from, website age and ChatGPT citations, trust signals AI engines reward most, multi-channel publishing and AI mentions, SEO vs LLM citation timing, GEO adoption by company size, most common AI search mistakes, and Reddit citation analysis. Semrush, AI Mode comparison study (July 2025). Pew Research Center, Google users are less likely to click on links when an AI summary appears (July 2025). Agarwal & Sen, randomised field experiment on AI Overviews (SSRN working paper, 2026). Profound, AI platform citation patterns (680M citations). Google Search Central, AI features and your website.