What is GEO (Generative Engine Optimisation) and why it matters for B2B SaaS in 2026

Your buyers have changed how they search. Have you noticed?

A few years ago, the typical B2B buyer would type a query into Google, scan the first page of results, click through to two or three sites, and eventually end up on your homepage. Today, a growing share of that same buyer opens ChatGPT or Perplexity, asks a direct question, "what's the best GTM tool for a Series A fintech?" or "who are the top fractional CMOs in Europe?", and trusts the answer they get back.

They may never visit your site at all. And if your brand isn't in that answer, you don't exist to them.

This is the shift that Generative Engine Optimisation (GEO) is designed to address.

What is GEO?

GEO, Generative Engine Optimisation, is the practice of structuring your brand, content, and digital presence so that Large Language Models (LLMs) like ChatGPT, Gemini, Perplexity, and Claude cite and recommend you when users ask questions relevant to your product or market.

It sits alongside a related discipline called AEO (Answer Engine Optimisation), which focuses specifically on AI-powered answer surfaces, including Google's AI Overviews, Bing Copilot, and Perplexity's answer blocks. Together, GEO and AEO define the emerging practice of AI Search optimisation.

The goal is simple: when your ideal buyer asks an AI tool a question that your product or service answers, you want to be the brand that gets named.

Why GEO is not just SEO with a new name

This is the misconception I encounter most often. Many companies assume that if their SEO is solid, their AI visibility will take care of itself. It won't, and the reasons are structural.

Search engines rank pages. LLMs synthesise information. These are fundamentally different tasks, and they rely on fundamentally different signals.

Google's algorithm rewards backlinks, on-page keyword density, technical structure, and click-through rates. LLMs are trained on vast corpora of text, and they form associations based on patterns across that text, who gets cited by credible third parties, whose explanations appear most consistently across the web, which brands are mentioned in context with specific problems or outcomes.

A company can rank on page one of Google for "GTM strategy fintech" and be completely absent from ChatGPT's answer to the same question. I've seen it repeatedly.

Why it matters specifically for B2B SaaS

The B2B buying journey has always been longer and more research-intensive than B2C. That's exactly why the shift to AI-assisted research hits B2B harder and faster.

Consider the numbers: 94% of B2B buyers now use LLMs during their decision-making process. 75% prefer to research independently before speaking to a sales rep. And 81% had already formed a vendor preference before making first contact with a sales team.

If your brand isn't present in the research phase, specifically in the AI-generated answers that increasingly define that phase, you are being eliminated from shortlists you never knew you were on.

For SaaS companies in particular, the stakes are compounded by category competition. When a buyer asks "what's the best [category] tool for [use case]", the LLM will name two or three brands. Getting named once builds a pattern. Missing consistently means your competitors own the narrative.

What actually moves the needle in GEO

Based on my work with tech and fintech companies across Europe, the signals that most reliably improve LLM visibility are:

Third-party mentions and citations. LLMs learn from the web. The more credible sources, industry publications, review platforms like G2 or Capterra, analyst reports, expert interviews, mention your brand in context with specific problems, the more likely you are to be cited.

Clear, answer-structured content on your own site. FAQ pages, comparison pages, and explainer content written to directly answer specific buyer questions give LLMs a ready-made answer block to pull from. Vague brand storytelling does not.

Consistent positioning across channels. LLMs aggregate across sources. If your website, your LinkedIn, your PR mentions, and your partner pages all describe you differently, the model has no clear signal to latch onto.

Authority in a specific niche. Generalist positioning is penalised in AI Search. The more precisely you are associated with a specific problem, market, or use case, the more reliably you will be surfaced when that problem is queried.

Where to start

If you've never audited your AI Search visibility, the fastest starting point is to open ChatGPT, Perplexity, and Gemini, and ask them the questions your buyers are asking. Search for your category. Search for your specific use case. Search for comparisons with your competitors.

See who gets named. See how your brand is described, or whether it appears at all.

That snapshot is your baseline. Everything in a GEO programme is built from there: identifying the gaps, restructuring content, earning the right third-party mentions, and tracking citation share over time.

It is not quick work. But it is increasingly the work that determines whether your brand exists in the buyer's consideration set.