GEO stands for generative engine optimisation. It makes sure a brand appears in the answers of generative AI systems such as ChatGPT and Perplexity. The same applies to Google AI Overviews. The terms AIO and AI visibility describe the same goal: your brand is named and cited as a source when someone asks an AI for a solution. For industrial companies this matters because a growing share of supplier research now starts with such a question.

SEO optimises a page for a ranking position. GEO works on getting your brand into a generated answer. That answer is built from many sources at once: your own website, trade publications, YouTube, LinkedIn and industry directories. GEO is therefore a holistic approach that reaches far beyond your own website. The aim is to occupy the semantic space around your topic so that AI models classify your brand as relevant.

A GEO agency first establishes where your brand needs to appear in the buying decision. That means the questions your target group really asks an AI. It then analyses how the brand performs there today and who is recommended in its place. The outreach strategy follows from both. It runs through trade press relations, the company website, LinkedIn and platforms like YouTube, because these are the sources AI systems draw on. additiv combines this with almost 30 years of B2B communication in logistics, robotics, mechanical engineering and the process industry.

Your company gets into AI answers by being relevant in the sources those answers are built from. Query fan-out breaks a single user question into many sub-queries. Retrieval-augmented generation (RAG) then fetches material for each sub-query and assembles the answer from it. One question quickly becomes dozens of retrievals across very different sources. Anyone who only looks at their own website covers a fraction of them.

You become visible in ChatGPT through the sources that already rank for your topics: trade media, industry directories, LinkedIn and your own website. When answering, ChatGPT retrieves pages with its own crawler and relies on a conventional search engine in the background. One requirement comes first: your robots.txt has to let the AI crawlers in. That needs checking before anyone works on content.

You get into Perplexity answers with content that fits the question well, because that is how Perplexity selects its sources. Domain size alone does not decide. That helps mid-sized manufacturers competing against large corporations. Perplexity lists the sources it used beneath every answer. That makes the work verifiable, because you can see which pages are pulled and which competitors appear next to you.

You appear in Google AI Overviews through the same search index that drives classic rankings. The Overviews build on it more directly than the pure chat assistants. If you already rank on Google for a topic, you start with an advantage. The difference lies in the result: the answer sits above the search results. Some users read it without opening a single page. Exactly those users no longer show up in your click statistics.

Yes, if your buyers search in German. An AI system answers a German question from the sources it finds for that question. For industrial topics these are mostly German trade journals. German directories and German company websites also feed in. An English website alone rarely reaches those answers. additiv writes for German-language trade media such as DVZ, Logistik Heute, MM MaschinenMarkt and CHEManager. International clients work with additiv in English.

Yes, provided the agency knows the German market and can work across languages. additiv is based in Montabaur and has specialised in B2B industrial communication for almost 30 years. The team works with clients in German and English. For markets beyond the German-speaking region, additiv draws on Thenetworkone, an international agency network. The German trade press and German-language AI answers remain the core of what we do.

The fastest lever is an inventory. It shows which questions matter for your business and how often you are named. It also shows who is recommended instead. Without this measurement you are optimising blind. After that come measures that need no relaunch: a citable answer paragraph near the top of your key pages, an FAQ section built on real questions, structured data, and bylined articles where your target group already reads.

Write so that a single paragraph stands on its own. AI systems rarely read a whole page. They take the section that answers the question and reuse it. A paragraph therefore opens with the answer and explains afterwards. Figures and names sit in the same sentence as the statement they support. Technical terms are explained once, because otherwise the system cannot be sure what it is dealing with.

The formats that work in AI answers are those that answer a question completely. FAQ sections, glossaries, definition pages and customer case studies with verified figures are cited more often than product pages, because a product page is written to sell. For industrial companies the case study is the underrated format. It puts verified figures in context and shows a traceable chain of cause and effect. That is exactly what an AI system needs to build a reliable answer.

Schema markup that helps AI systems includes FAQPage for genuine question-and-answer sections and ProfessionalService for classifying the company. Markup only works on text that already carries meaning. It makes that text unambiguous. More important than the choice of types is consistency: what the schema says must appear word for word on the visible page. If it differs, the markup loses its value.

You measure AI visibility with repeated, consistent prompts. You define the questions that are really asked in the buying process and send them regularly to several systems. Every answer is logged. The key metric is share of voice: the proportion of answers in which your brand appears. It also matters whether your website is linked as a source and which competitors are recommended in your place. That last figure is the uncomfortable one. It says the most. Single queries are useless for this, because the same question returns different answers on different days.

The time to visibility in AI answers depends on where your brand stands today and which sources carry your topic. Corrections to your own website and structured data can take effect within weeks, because AI systems retrieve pages live. Trade media coverage takes longer, as German trade journals plan their issues months ahead. additiv therefore measures a baseline first and repeats the measurement with the same prompts, so that progress shows up in the numbers.

The sensible route is to keep your existing SEO foundation and make your content citable on top of it. An either-or framing gets the question the wrong way round. Classic search remains. Yet a growing share of research now ends in an AI answer without anyone opening a website. If you only optimise for clicks, you lose sight of that share. The second step builds on what is already there.

You correct false statements in AI answers with evidence, not objections. AI systems have no editorial desk you can write to. They answer from what they find online and repeat an error for as long as it remains the most findable version. The way forward is a corporate grounding page: a machine-readable page with your company’s verified core data that serves as the reference. This version is then mirrored consistently in trade media, directories, on LinkedIn and on your own website. As long as a company tells three stories in three places, chance decides which one ends up in the answer.