If not even ChatGPT knows about you, how will your customer find out about you?

AI models prefer clearly structured, verifiable and contextually rich content. This includes:

• Headings and subheadings (H2-H4) for a clear structure
• Links to trustworthy sources, statistics and expert citations
• The use of schema.org markup to indicate the type of content (e.g. FAQ, product cards)
• Clear infographics, image captions and video transcripts

Monitoring visibility in AI answers is a new field of analysis. Tools such as Perplexity or ChatGPT can give you a hint as to whether your content is being mentioned. Tracking increased indirect traffic or using tools for monitoring mentions in AI answers will give you a clearer picture. Regular analysis of backlinks and tracking of conversion paths then helps to reveal new sources of traffic.

Start with a technical audit of the website, focused on structured data and readability for AI. Then create content that is comprehensible not only to people but also to generative models — use clear definitions, citations and relevant data. Do not forget to build content outside your own website either (PR articles, external blogs, forums), and keep monitoring the development of AI algorithms so that your content remains visible in the long term.

While traditional SEO (Search Engine Optimization) remains a pillar of digital marketing, the arrival of generative artificial intelligence (AI) has created the need for a new paradigm – GEO (Generative Engine Optimization). This transformation is not merely an update of techniques but a fundamental change in the approach to online visibility, one that redefines the interaction between content and search technologies.

Traditional SEO is oriented towards the algorithms of search engines such as Google or Bing, which work on the principle of indexing and rating web pages using factors such as keywords, backlinks or loading speed. The aim is to achieve a high position in the organic search results (SERP), which typically leads to an increased click-through rate (CTR).

Classic search engines use inverted indexes and PageRank algorithms, whereas generative models rely on transformer architectures (e.g. GPT) capable of understanding context and generating text at the level of semantic relationships. This requires GEO-optimised content to link concepts explicitly and to provide verifiable references, which increases the probability of being included in AI answers by 29%.

Content for LLMs should be factually accurate and citable, structured in a format that is easy for LLMs to digest (e.g. short paragraphs, clear headings, lists, tables), provide explicit answers to questions in natural language and contain relevant contextual metadata and structured data. Great emphasis is placed on E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness). The text should be stylistically direct, use shorter sentences and clear logical connections, express relationships between pieces of information explicitly and provide rich associations and context for key entities.

In SEO, optimisation for specific keywords dominates, with the emphasis on their density and placement in meta tags or headings. For example, an analysis of 10,000 Czech websites showed that pages in the TOP 3 positions have an average keyword density of 1.2%. GEO shifts attention to a broader semantic network. AI models evaluate content on the basis of its ability to answer complex queries, which requires related topics to be covered in depth. Research by Data Club found that content with at least 5 interlinked contextual topics has a 41% higher chance of being mentioned in generated answers.

In the new information ecosystem, where users receive direct, structured answers from generative AI, the way users consume information is changing fundamentally. Correct implementation of GEO strategies can bring several key benefits: an increased chance that your content will be cited in generative AI answers; a stronger position for your brand as an authority in its field; a new type of visibility and reach among users who use traditional search engines less; and a competitive advantage at a time when many companies are not yet paying sufficient attention to this area.

GEO and LLMO are new digital marketing disciplines focused on optimising websites, content and digital presence so that large language models (LLMs) such as ChatGPT, Claude or Gemini find them easily, interpret them correctly and are highly likely to cite them in their answers. Whereas classic SEO concentrates on optimising for search engine algorithms with the aim of achieving the highest possible position in search results (clicks), GEO places the emphasis on making your content as comprehensible and usable as possible for LLMs, which will present it to users in generated answers (citations). It is no longer just about „being found“, but above all about „being cited and recommended“.

E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) is a framework used by Google (and reflected by LLMs) to assess the quality of web content. While Google uses it primarily for quality rating, for LLMs these signals are key to assessing the trustworthiness of a source and the likelihood of citing it. LLMs place extreme emphasis on all aspects of E-E-A-T when selecting sources for their answers, because they need to provide accurate and trustworthy information. Building authority (e.g. through mentions in training data, consistency of information, being first to publish new concepts) and verifiability (accurate citation of sources, research methodology) is essential for GEO.

Testing and measurement are key to understanding how different LLM platforms interpret your content and whether your optimisation is genuinely producing results. Since LLMs are constantly evolving and their behaviour changes, a continuous process of testing and iteration is necessary. By regularly submitting relevant queries to different models, monitoring citations, analysing traffic from AI platforms and experimenting with different content structures, you can identify what works best and optimise your strategy on an ongoing basis. Specialised tools and a systematic approach to testing using various prompts help to make this process more efficient.

GEO does not represent a replacement for traditional SEO but an evolutionary extension of it. While SEO remains key for transactional queries and local search, GEO dominates in informational and complex queries. Successful companies will have to balance their investment in both approaches, with a ratio of 60:40 (SEO:GEO) appearing to be optimal for most sectors. The key is continuous monitoring of developments in AI technologies and flexible adaptation of content strategies to changing search ecosystems

In the age of AI it is not enough to optimise your own website alone. What matters is your overall digital footprint and how the internet as a whole talks about you. LLMs learn from training data that includes a wide range of sources outside your website. Active participation in industry communities, valuable digital PR leading to mentions in authoritative media and building a strong digital presence on relevant platforms can influence the training data of LLMs and help them perceive your brand as an authority. Consistency is key: in how the brand is presented, which topics it is associated with and what value it brings across the entire digital ecosystem.