What is GEO (Generative Engine Optimization) and why your brand needs it

What is GEO (Generative Engine Optimization) and why your brand needs it

Imagine a potential customer asking ChatGPT: "What's the best digital marketing agency in Barcelona?" or "Which management software is most reliable for SMEs?" If your brand doesn't appear in that answer, you've just lost a business opportunity without even knowing it. Welcome to the era of GEO: Generative Engine Optimization.

According to a Gartner prediction from February 2024, the volume of traditional search engine queries will drop by 25% by 2026.

The question is no longer whether your company needs GEO, but how much you're losing by not having it.

What exactly is GEO?

GEO (Generative Engine Optimization) is the process of structuring and optimising your digital presence so that AI-based search engines—ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude—cite, mention, or recommend your brand when users ask questions relevant to your industry.

Unlike traditional search engines, which display a list of links, generative engines analyse information from multiple sources simultaneously, cross-reference, evaluate consistency patterns, and generate a unique, direct answer.

Your content no longer competes for a click in a list of ten blue results; it competes to be the source that AI chooses to cite.

GEO vs. SEO: What's the difference?

Traditional SEO optimises your website to get clicks from Google's search results pages. GEO optimises your content to be cited within AI-generated responses. They are complementary disciplines, not mutually exclusive.

• SEO: measures ranking positions, clicks, and organic traffic from search engines.
• GEO: measures brand mentions, linked citations, and participation in AI responses.
• SEO: relies on Keywords, Backlinks, and technical optimisation.
• GEO: relies on topical authority, content structure, citable data, and brand consistency across the digital ecosystem.

Ranking well on Google does not guarantee that AI will mention you.

How do LLMs decide which brands to mention?

Language models don't choose brands randomly. They follow identifiable patterns that, when systematically worked on, produce cumulative results. These are the key factors:

1. Source authority and trust

LLMs no longer rely on a single source, no matter how well-positioned it is. The sources they cite also include user and community platforms such as Reddit, LinkedIn, Wikipedia or YouTube, and academic repositories like arXiv.

2. Entity recognition

Models don't just look for exact Keyword matches; they infer relationships between your brand, your category, your features, your customers, and the sources that describe you. If these signals are weak, inconsistent, or outdated, your visibility suffers even if your website is technically impeccable.

3. Content structure and freshness

Keep content up to date and use orderly headings and structured data (schema markup), so that the structure of the page is easy to interpret.

4. Content depth

Deep pages of a website, such as practical guides, product comparisons or specialised articles, answer concrete questions. That is what AI looks for, more than generic corporate messages.

5. Dual signals: mention + citation

A brand mention and a linked citation are two different signals, and it pays to work on both.

The pillars of GEO: what to optimise

E-E-A-T enhanced for AI

Google's E-E-A-T framework (Experience, Expertise, Authority, and Trust) gains even greater importance in the context of generative AI. AI engines apply stricter scrutiny to YMYL (Your Money, Your Life) topics: finance, health, security, and professional services. To maximise your visibility:

• Experience: include practical cases, proprietary data, and real testimonials that demonstrate direct experience.
• Expertise: sign your content with identifiable authors who have verifiable professional profiles (LinkedIn, academic publications).
• Authority: get mentions and citations in industry media, professional directories, and reference platforms.
• Trust: always cite primary sources with publication year, link to recognised studies, and keep your information updated.

Structured data (Schema Markup)

Structured data markup in JSON-LD format helps AI systems interpret your content unequivocally. Implement at a minimum:

• Organization Schema: name, logo, location, social media.
• Product/Service Schema: for each product or service, with prices, availability, and features.
• FAQ Schema: mark up the frequently asked questions that are visible on the page. Google stopped showing the FAQ rich result on 7 May 2026, but the markup still describes the content.
• Article Schema: for editorial content, with author, publication date, and update date.
• LocalBusiness Schema: if you have a physical presence, include address, opening hours, and contact details.

Topical Authority

LLMs favour sources that demonstrate deep and consistent mastery of a topic. It's not enough to publish an isolated article: you need a cluster of interconnected content that covers a topic from multiple angles. If your company sells accounting software, you should have content on tax regulations, tool comparisons, implementation guides, and success stories, all coherently linked.

Practical guide: 8 steps to improve your AI visibility

Step 1: Audit your current visibility

Before optimising, you need to know where you stand. Ask questions relevant to your business on ChatGPT, Perplexity, Gemini, and Claude. Record whether your brand appears, in what position, with what sentiment, and if it includes a link. Do this for at least 20-30 representative queries in your sector.

Step 2: Answer directly in the first 50 words

AI systems using real-time retrieval (Perplexity, Google AI Overviews) primarily evaluate a page's relevance by its initial content. The first 200 words of any article should directly answer the main query, without circumlocution or empty introductions.

Step 3: Use question-format headings

AI systems match headings with queries. A heading "How much does a CRM for SMEs cost?" is much more likely to be cited than "CRM Prices." Rephrase your H2s and H3s as questions that reflect how your customers actually speak.

Step 4: Include specific, citable data

AI models favour content with concrete data. The statement "according to BrightEdge's 2019 channel report, organic search drove 53.3% of trackable web traffic" can be cited as a fact; "organic search matters" cannot. Include statistics, percentages, figures, and measurable results in your content, always with their source.

Step 5: Implement comprehensive structured data

Ensure all your main pages have the appropriate schema markup. Validate your JSON-LD with tools like Google's Rich Results Test and ensure the structured information is consistent with the visible content.

Step 6: Build presence in community sources

With almost half of AI citations coming from community sources, your strategy cannot be limited to your website. Actively participate in specialised forums in your sector, answer questions on platforms like Reddit or Quora, publish valuable content on LinkedIn, and gain presence in directories and reference listings.

Step 7: Update your content quarterly

Outdated content loses citations. Establish a quarterly review schedule for your most important pages. Update data, add new information, and modify the update date in the schema markup.

Step 8: Monitor and adjust continuously

GEO is not a one-off project but an ongoing process. Monitor your AI visibility monthly, identify which queries you've gained or lost, and adjust your strategy accordingly.

How is AI visibility measured?

Measuring visibility in generative engines requires different metrics and tools than traditional SEO. These are the fundamental metrics you should track:

• AI Visibility Score: a composite score that aggregates appearance frequency, sentiment of mentions, prominence (first mention vs. secondary appearance), and breadth of query categories where you appear.
• Share of Voice in AI: percentage of AI responses that mention your brand compared to the total responses for your target queries.
• Mentions vs. Citations: mentions indicate that AI knows your brand; citations (with a link) indicate that it trusts your content as a source. Both metrics are important but reflect different levels of authority.
• Answer Inclusion Rate: the percentage of times your brand is included in the AI's response for a given set of queries. This is the primary KPI for GEO.

Specialised tools like Otterly, AIclicks, LLMrefs, or Sistrix (which already incorporates an AI visibility index) allow for automated tracking. However, many companies start with manual audits before investing in paid platforms.

What research says about GEO

The term GEO comes from an academic study by Pranjal Aggarwal and co-authors, posted on arXiv in November 2023 and accepted at the KDD 2024 conference. The authors tested several optimisation methods on their own benchmark of queries and found that they can boost a source's visibility in generative engine responses by up to 40%, with results varying by domain.

The practical conclusion is a strategy that combines quality content, clear structure, citable data and a consistent presence across several channels.

The future is now: the window of opportunity

ChatGPT, Perplexity, Gemini and Claude already answer questions that used to go to a search engine.

But here's the good news: most companies are not yet optimising for AI. This means there's a real window of opportunity for brands that act now. Just as companies that adopted SEO in its early years gained a lasting competitive advantage, those who invest in GEO today will be positioned to dominate AI visibility for years to come.

There is no fixed timeframe for changes in citations: it depends on each platform and on whether it retrieves content in real time or relies on its training data.

Take the first step: measure your AI visibility

At ZDS, we have been helping companies position themselves in the digital environment for years, and AI visibility is the natural evolution of that mission. That's why we have developed our own AI Visibility Tracker: a tool that automatically monitors how your brand appears in responses from ChatGPT, Gemini, Perplexity, and Claude, measures your Share of Voice against competitors, and tracks the evolution of your mentions and citations over time.

If you want to know how AI engines perceive you today—and what you can do to improve that perception—contact our team. We will show you exactly where your brand stands in the AI ecosystem and design a GEO strategy tailored to your industry and objectives. Because in a world where AI answers your customers' questions, what matters is not just being on Google: it's being in the answer.