In summary: To rank in ChatGPT, Perplexity, and Claude by 2026, you need GEO (Generative Engine Optimisation), not just traditional SEO. LLMs extract and cite short, self-contained passages from your website, so you must structure content in blocks with direct answers to specific questions. 25-30% of informational searches already use these models, and not appearing in their responses means not existing for those users.
By 2026, you won't just be ranking on a single screen. Google remains relevant, but ChatGPT, Perplexity, and Claude are three new SERPs with different rules. This guide explains what's GEO (Generative Engine Optimisation), why it matters to your SME, and the 9 plays a senior SEO applies to get LLMs to cite your brand.
1. What is GEO and why it's not the same as SEO
Classic SEO optimises for Google: ranking web pages for queries. GEO optimises for LLMs —ChatGPT, Perplexity, Claude, Gemini— with a different goal: getting the models to extract passages from your website and cite your brand when responding to their users.
The technical difference is concrete. Google ranks pages. LLMs extract citable passages: short, self-contained blocks with direct answers to a question. If your website doesn't structure content this way, the models will process it but won't cite it. There's a huge difference between the two.
The argument for an SME is simple: according to Gartner data, 25-30% of informational searches by 2026 will already go through LLMs. When someone asks ChatGPT 'best AI marketing agencies in Valencia,' the answer cites 3-5 brands. If yours doesn't appear, you don't exist for that user. Furthermore, LLMs are updated quarterly, making each improvement a gain that lasts until the next training cycle. And there's still little GEO competition in Spanish: the window won't be open indefinitely.
2. How an LLM decides which brands to cite
LLMs have opaque weightings, but the factors that tip the scales are identifiable:
- Frequency of your brand mention on the open web that forms the training data.
- Category association: ensuring that when your brand is mentioned, it appears alongside keywords relevant to your sector.
- Citable structure of your website: short blocks with direct answers that the LLM can extract without additional context.
- Verifiable data: numbers, dates, real-world cases. These are much easier to cite than generic claims.
- E-E-A-T coverage: expertise, experience, authoritativeness, trustworthiness. The same signals as Google.
- llms.txt in root: a directory that tells the LLM which pages are canonical for each topic.
What are the 9 GEO plays a senior SEO applies?
Play 1 · Self-contained Blocks with Direct Answers
Each section of your website should answer a specific question within the first 1-3 paragraphs. The rest of the block can expand on it, but the LLM must be able to extract the answer without reading the entire thing.
The structure works like this: an H2 with the exact question as the query, the first paragraph with a direct answer in 50-80 words, and the rest dedicated to context, examples, and data. Simple in theory, rarely seen in practice.
Play 2 · FAQs with Real User Questions
LLMs consume FAQPage schema, but only when the questions are genuine, not fabricated merely to fill space.
The most reliable sources: Google's People Also Ask, competitor reviews on G2 or Trustpilot, subreddits like r/Spain or r/empresas, and questions that come directly to sales or support. These latter ones are the most valuable because they're already phrased in natural language.
Play 3 · Verifiable Numerical Data with Source
LLMs prioritise passages with concrete data over vague statements. '67% of Spanish SMEs...' works better than 'many SMEs...'. Citing the source —INE, IDC, Gartner, eMarketer— adds credibility.
Specific dates ('2026 data') outperform expressions like 'recent'. And comparative tables have a double advantage: they're citable and easy to share.
Play 4 · llms.txt in Root
The equivalent of robots.txt but for LLMs. It indicates which pages are canonical for each topic. It's an open spec with growing adoption by 2026. A minimal example:
# Boomatik > Suite of expert AI agents for SME marketing ## Areas - Brand Strategy: /boo-brand - SEO + GEO: /boo-seo - Performance: /boo-performance - Leads B2B: /boo-leads
Play 5 · Consistent Brand Mentions · Semantic NAP
LLMs learn your brand when it appears in many contexts associated with the same keywords. Concrete actions include: guest posts on industry sites with contextual mentions, presence in relevant sectoral directories (G2, Capterra, GetApp if applicable, no spam), citations in industry studies by offering yourself as an expert source, and appearances on podcasts with published transcripts. LLMs consume transcripts.
Play 6 · Extensive Schema · Article, FAQPage, HowTo, Service
LLMs consume schema.org as a structural signal. On every page, it's advisable to implement Article schema with author, datePublished, and image; FAQPage schema if there are frequently asked questions; HowTo schema if there's a tutorial; Service schema on commercial landing pages; and BreadcrumbList always.
It's not optional if you want to maximise the probability of being cited.
Play 7 · Topical Authority · Cluster Strategy
LLMs identify topical authority through content density and interlinking, just like Google.
The structure that works: a pillar hub for each topical area (3,000-4,000 words), between 5 and 8 spokes that delve into specific aspects (1,500-2,500 words each), and an internal linking matrix where each spoke links to the hub and the hub links to all spokes.
Without that network, the cluster doesn't convey authority.
Play 8 · Long-tail Conversational Queries
Users speak to LLMs in natural language. The real query is 'what AI marketing agency do you recommend for my dental clinic in Valencia?', not 'dental marketing agency Valencia'.
Optimising for this pattern involves H2s in natural question format, descriptive URLs like /dental-clinic-marketing-agency-valencia, and niche industry content that no generalist brand will produce.
Play 9 · Quarterly Refresh with New Data
LLMs are retrained every 3-6 months. Refreshing content with 2026 data, recent case studies, and new internal links maximises the probability of entering the next training round. It's not a one-off task; it's a cycle.
4. How to measure GEO · what tracking works
GEO is harder to measure than classic SEO. There isn't a standard 'Search Console for LLMs'. The proxies that work in practice are:
- Brand mentions tracking with BrandMentions or Mention.com: alerts when your brand appears on the open web.
- Manual prompt testing: weekly, ask ChatGPT, Perplexity, and Claude key queries from your sector and record if they cite you.
- Referrer tracking in GA4: detects traffic coming from Perplexity and ChatGPT search.
- llms.txt analytics: if you have the file implemented, LLM crawlers access it with an identifiable user-agent.
When does it not make sense to invest in GEO yet?
GEO is a real competitive advantage, but it requires a solid foundation first. If your classic SEO is broken —poor indexing, missing schema, non-existent internal linking— fix that first. The same applies if your SME has fewer than 50 indexed pages: without critical mass, LLMs won't learn.
Without a presence in industry directories, there aren't enough brand mentions. And if your niche is very local and small, LLMs don't yet have the data density for those sub-sectors.
The logical order: solid SEO plus consistent brand mentions, and then add the specific GEO layer.
GEO in 2026: Opportunity Before Saturation
GEO today is what SEO was in 2010: a clear opportunity with little competition for those who approach it with discipline. If your Spanish SME relies on organic traffic, neglecting GEO means ceding 25-30% of the market to competitors who are embracing it.
BOO SEO · expert AI agent for SEO + GEO executes this exact methodology on your website. It systematically applies the 9 plays and measures results with real tracking. If you'd like an initial audit of specific GEO + SEO opportunities for your SME, we can provide one within 48 hours.
Frequently Asked Questions
Does GEO replace classic SEO?
No. It's complementary. Classic SEO still accounts for the majority of organic traffic. GEO captures the new 25-30% from LLM searches. The professional strategy involves both, not one or the other.
How long does GEO take to deliver results?
3-6 months to start appearing consistently cited. Faster than classic SEO (which takes 6-12 months) because LLMs are trained more frequently.
What is llms.txt, and is it mandatory?
It's an optional file in your root directory that tells LLMs which pages are canonical for which topic. It's not mandatory, but its adoption is growing · an SME that implements it early gains an advantage.
Can I rank in ChatGPT by paying?
Not directly · ChatGPT doesn't have ads. But you can invest in plays that increase the likelihood of citation: brand mentions, schema, citable content, llms.txt. Measurable ROI within 90 days with discipline.
Does a small SME stand a chance against large brands?
Yes, in specific niches. If your SME has clear specialisation (e.g., a marketing agency for dental clinics in Valencia), a large generic brand will never take that citation from you. Your niche is your advantage.
What is GEO, and how does it differ from traditional SEO?
GEO stands for Generative Engine Optimisation, which is the practice of optimising website content so that AI-powered search engines, such as ChatGPT, Perplexity, or Claude, cite and recommend it in their responses.
Unlike traditional SEO, which aims to appear in a list of Google results, GEO seeks to have the language model use your content as a reliable source and mention it directly to the user.
This involves writing with greater clarity, structuring information well, and demonstrating real authority on the topic, as models prioritise sources that answer questions directly and verifiably.
Does an SME need a lot of resources to appear in ChatGPT or Perplexity responses?
Not necessarily.
An SME with limited resources can improve its visibility in these systems by focusing on three specific aspects: first, publishing content that answers real customer questions with precise data and clear language; second, getting other websites in its sector to mention or link to it, as models track these references; third, keeping company information updated in directories and public listings.
It doesn't require a huge investment, but rather consistency and an approach focused on resolving specific user queries instead of writing for search engines.
How often do models like Claude or Perplexity update their information?
Each model has a different cycle. Perplexity performs real-time searches, so it can retrieve content published just a few hours ago.
Claude and ChatGPT, on the other hand, have a knowledge cut-off date and are updated through new training cycles that occur every few months, although their versions with internet access can consult current pages.
For an SME, this means that publishing fresh, well-structured content on the web has an almost immediate effect on Perplexity, whereas for models without browsing capabilities, the impact comes with the next training cycle.
How does an SME know if AI models are already mentioning it?
The most direct way is to conduct manual tests: type questions related to the company's sector, product, or geographical area into ChatGPT, Perplexity, or Claude and check if it's cited.
It's also advisable to search for the company name in quotation marks to see if any model mentions it as a reference.
Some brand monitoring tools are starting to include tracking of mentions in AI-generated responses, although in 2025, these are still few and not always reliable.
Regular manual review remains the simplest and most accessible method for an SME.
