Be visible in AI search before your competitors are.

SEO optimizes your content for Google rankings and organic clicks. GEO (Generative Engine Optimization) optimizes for AI systems like ChatGPT, Claude, or Perplexity to recommend your company in buying situations. The decisive difference: SEO gets you on the results page; GEO gets you into the answer. Both overlap on content, structure, and technical foundation, but the optimization goal differs. SEO targets findability in search results; GEO targets recommendation in AI-generated answers. Companies that rely on SEO alone are losing visibility with an audience that increasingly makes purchase decisions through AI assistants.

AI visibility describes how visible and discoverable your brand is in AI-assisted search — when prospects ask ChatGPT, Perplexity, or Google Gemini for solutions in your market. For B2B it is business-critical because a growing share of buyers no longer prepares decisions through classic Google search but through AI assistants. If your product does not appear in those answers, you do not exist for that part of the audience — no matter how strong your Google rankings are. Companies building AI visibility now secure a lead that gets harder to close every month.

This pattern affects most B2B sites right now. The cause: Google's AI Overviews and AI assistants answer more queries directly without users clicking through to your site. Rankings stay stable, but click-through drops because information need is met inside search. Informational content in the awareness phase is hit hardest. Purchase demand does not disappear — it moves to new touchpoints like ChatGPT, Perplexity, and Copilot. The answer is not more SEO alone but a broader strategy: your brand must be present where your audience actually looks for solutions now.

SEO is not dead, but SEO alone is no longer enough. Google still processes billions of queries and organic rankings remain an important acquisition channel. But the share of the buyer journey happening in AI assistants is growing measurably — and that channel follows different rules. GEO does not replace SEO; it extends it. Technical foundations overlap: structured data, clear content, Schema.org markup. Optimization goals differ. SEO asks: do we rank? GEO asks: do we get recommended? Companies running both cover the full journey from Google search to AI recommendation.

Start with systematic prompt testing: phrase your audience's buying situations as prompts and check what ChatGPT, Perplexity, and Gemini recommend. Not once — repeatedly, with variations in context, industry, company size, and budget. You quickly see whether your brand appears, how it is positioned, and who is recommended instead. In the AI visibility audit I do this systematically: analyze your current recommendation rate across relevant prompts, identify gaps, and show which actions work fastest.

GEO does not replace your existing strategy — it builds on it. Most measures also strengthen SEO: better content structure, clearer entities, Schema.org markup, structured comparison pages. The difference is focus. Where SEO asks which keywords have volume, GEO asks in which buying situations AI should recommend your product. In practice: existing content gains recommendation signals, new content is optimized for both channels from day one, and the technical system is built so AI systems can use your information as a reliable fact source.

Both. Most consultancies deliver strategy and hand execution to agencies or your team — and most of the intelligence is lost on the way. I keep both in one hand: we decide together what to build, and I build it with you. For me that is not an add-on service but the only way real systems emerge. Strategy without hands on the code becomes buzzword theater. Code without strategic framing becomes a feature graveyard. For you: no handoff between strategy consultant and implementer, no alignment loops, no information loss.

Three fundamental differences. First: I am not an agency. No account management layer, no junior consultants, no reporting for reporting's sake. You work directly with me. Second: I build two AI products myself — Rawshot.ai and Careertrainer.ai — and use the same systems I build for clients. That is daily practice with measurable outcomes, not theory. Third: I build systems that stay. No dependency on open-ended agency retainers. Everything is built to run without me.

Good news: fundamentals are cross-platform. Clear positioning, structured content, consistent entities, and reliable sources improve visibility across AI systems at once. Differences are in the details: ChatGPT weights web sources differently than Perplexity; Gemini has deep Google integration. In the audit I analyze which platform matters most for your market and where the biggest gaps are. In practice we start with measures that work everywhere, then optimize for the platforms your audience uses most.

Everything starts with a free intro call: 15 minutes where you describe your situation and I say honestly whether and how I can help. If it fits, the AI visibility audit follows: in two weeks I analyze your current AI visibility, map recommendation gaps vs. competitors, and deliver a concrete report with a strategy session. You get a prioritized action plan. Then you choose: execute in-house using the report, or ongoing support where I build systems directly with your team. Communication stays short: Slack or email, no agency layers.

We typically see first changes in AI visibility after 4–6 weeks. Grounding pages and structured data are picked up by AI systems much faster than classic SEO changes by Google. At Rawshot.ai it took 90 days from zero to 3–5 qualified inquiries per day via AI-assisted discovery. Exact timeline depends on starting point, competitive landscape, and execution speed. What I can guarantee: in the audit you see exactly where you stand, and the roadmap shows which levers work fastest.

Good SEO is a strong base but no longer enough for the full buyer journey. AI systems do not choose brands by rankings. They evaluate positioning clarity, entity consistency, comparability, and source quality. A company can rank #1 on Google and still not be recommended in ChatGPT because content does not clearly state who the product is best for. GEO closes that gap — and most measures also strengthen SEO.

That is exactly what the systems are built for. You do not need a ten-person marketing team. The systems I build run largely automated: workflows generate pages from data, grounding pages update themselves, structured data is maintained programmatically. Your team steers and assures quality — it does not run everything manually. At Rawshot I run the same systems with a fraction of the team classic approaches would need. What matters is not team size but willingness to rebuild processes differently.

The entry point is the AI visibility audit: fixed price, clear scope, concrete outcome in two weeks. You get a full report with as-is analysis, competitive comparison, and prioritized action plan plus a strategy session. For ongoing support I work on a retainer. Scope and investment are defined after the audit, when it is clear which systems need to be built. In the free intro call we clarify whether your situation fits the audit and what a realistic range looks like.

It is not too early — it is the optimal moment. Use of AI assistants for business research is growing measurably in DACH: buyers, executives, and specialists increasingly use ChatGPT and Perplexity to research vendors, compare solutions, and build shortlists. Competition for AI visibility in German-speaking B2B is still much lower than in English-speaking markets. Companies building grounding systems now secure a position that will be significantly harder and more expensive in 12 months.

Key metrics: recommendation rate across a defined set of purchase prompts (how often you are recommended when your audience asks AI for solutions), positioning vs. competitors in the same prompts, branded search lift (whether brand searches rise after AI recommendations), qualified inquiries via AI-assisted discovery, and citation quality (which of your sources AI systems use as grounding). In the audit we establish a baseline and set concrete targets for the first 90 days.