Foundation & roadmap
- Buying questions and search intent
- Competitors and AI mentions
- Keyword and intent mapping
- Technical SEO and crawl audit
- Prioritised SEO and AI search roadmap
By month end
A clear roadmap with firm priorities.
Method
Demand, engines, gaps, evidence, counter-check. Five steps in a fixed order that we run for every engagement. AI does not name the best provider, it names the one it can evidence.
Selected brands we support with visibility, demand and systems
Starting point
Most visibility projects do not fail during delivery. They fail on the order. Pages get written before anyone checks whether the question is asked. Things get optimised before anyone measures who is named today. And in the end the comparison is missing that would show whether the work had an effect.
BELEG turns that around. First it is settled which question stays unanswered and which source answers it today. Only then does it become clear whether the gap is closed by a page, an article, a product data set or an external source.
That substance beats style is well researched. The Princeton study on Generative Engine Optimization (KDD 2024) measures a 115% higher citation probability for source citations, +41% for expert quotes with attribution and +40% for concrete statistics. Pure language polishing yields roughly +3%.
The fifth step is the one almost everybody leaves out. Without a comparison group every change looks like success. So we measure treated pages against untouched pages from the same period.
BELEG
We start with the questions where AI systems recommend providers, products or service companies, not with a keyword list. Search volume comes exclusively from the Google Ads API — never from tool estimates and never from a number a language model produced. If the check shows nobody searches for a service, we say so, even when that makes the engagement smaller.
Done when: You know which questions your market asks — and which service is not worth a page.
ChatGPT, Perplexity, Claude and Google AI are measured separately, because they select differently and cite different sources. Perplexity searches live on every query, Google AI Mode splits one question into eight to twelve sub-questions, Claude favours specialist publications. Looking at one system alone turns noise into a trend.
Done when: You see per system who gets recommended and which sources carry the answer.
Demand and measurement produce a gap list, not an overall score. Every gap gets a type: is a page missing, is evidence missing on an existing page, or is an external source missing? The order comes from your data — revenue, margin and effort decide, not a standard package.
Done when: It is settled what gets built first and why — traceable, not by gut feel.
Now the missing pieces get built: service and product pages, articles with evidenced claims, comparisons, product data, schema, press placements and entries on the sources that shape your category. What gets cited is well researched — the Princeton study (KDD 2024) measures +115% citation probability for source citations, +41% for expert quotes with attribution and +40% for concrete statistics. Pure language polishing yields roughly +3%.
Done when: Every claim on your pages is evidenced — and every gap has a visible answer.
We measure the same questions again and compare treated pages against untouched ones. Without that comparison an improvement cannot be separated from market movement. Presence and citation are reported separately: being named and being cited as a source are two different outcomes with two different levers.
Done when: You know which measure worked — and which did not, which matters just as much.
Evidence
AI needs clear information on your website and trustworthy sources outside it. If one of the three layers is missing, the recommendation does not hold.
Service pages, product pages, internal links, schema and the evidence behind a decision.
Articles, comparisons, guides, FAQs and cases for concrete buying questions.
Listings, partner sites, trade media, reviews and the sources AI already uses.
SEO is the core. AI search, content, technology, authority and conversion work around it. This is what the first 90 days with us look like.
By month end
A clear roadmap with firm priorities.
By month end
The first new evidence is live.
By month end
A measurable before-and-after baseline.
Why this works
We check Google, AI answers and sources together. That produces clear tasks which are measured again afterwards.
Results
Figure, period and the work behind it. Each project ran over several months.
May to July 2026 · 3 months
+761 %
more impressions
Shopify & e-commerce
View caseApril to July 2026 · 4 months
+115 %
more impressions
Healthcare IT
View caseMay to July 2026 · 3 months
+191 %
more clicks
Dental practice
View caseWe did not invent BELEG to have an acronym. It is the order we work in anyway — and the last step is the one almost everybody leaves out. Without a comparison against untouched pages you cannot tell whether your work moved something or whether the market moved. That is the only question anyone pays us for.
Felix Ament, Founder, getSichtbar GmbH
Testimonials
Quotes from founders and managing directors we work with. Where a case exists, the number sits next to it.
“No fuckin way, Felix Ament is the GOAT. Within weeks, NICCOS was #1 on ChatGPT and Claude. Our organic inbound leads have exploded thanks to getSichtbar.”
+761 %
more impressions
May to July 2026 · 3 months
“In the first month, the first request came in with the line: 'ChatGPT recommended you to me.' That is exactly why we use getSichtbar.”
+980 %
more organic conversions
May to July 2026 · 3 months
For Bedarf, Engines, Lücken, Evidenz and Gegenprobe — demand, engines, gaps, evidence and counter-check, the five steps we work in. The German word also names the principle: AI systems do not name the best provider, they name the one they can evidence.
The technical basis is the same, the selection is not. According to Ahrefs (January 2026) only 38% of the pages cited in AI Overviews still appeared in Google's top 10 — a year earlier it was 76%. We treat both channels separately and explain rankings with ranking factors and citations with citation factors.
Because without a comparison group every change looks explainable. We compare treated pages against untouched pages from the same period. That is not a laboratory experiment, but it separates effect from market movement far better than a plain before-and-after view.
Demand and engines take two to three weeks. The evidence work then runs continuously, gap by gap. We usually see first measurable movement after four to eight weeks; Perplexity reacts fastest because it searches live on every query.
No, and nobody can do that credibly. AI answers vary by query and model version — according to Ahrefs the move to Gemini 3 replaced 42% of the cited domains. We show where you are missing today, build the evidence and measure again afterwards.
Then we say so and do not build the page. Some offers are not searched for but recommended or actively sold — in that case press work, AI answers or sales are the better channels than a service page. That honesty saves the most expensive SEO of all: SEO for pages nobody searches.
Rarely. Most of the leverage sits on existing URLs: structure, evidence, schema, internal linking. A relaunch without a prior demand check is the most expensive way to carry the same problem into a new design.
An unclear offer, missing internal decisions and everything that happens outside your domain. Mentions on third-party sites can be prepared but not forced — editors decide themselves. And visibility does not replace sales.
First call
15 minutes, straight from the calendar. Before the call we check which providers AI names in your category and bring the result.
What happens in the call