LLM Visibility for an Industrial Supplier: Zeno Visibility Translates GEO into a Robust Authority Model
LLM Visibility for an Industrial…
Situation
A mid-sized industrial equipment supplier from southern Germany, specializing in components for conveyor technology and process automation, faced a clear problem in 2024: visibility in traditional search engines was stable, but the brand hardly appeared in AI answer systems. The company generates around €68 million in annual revenue, about 70 percent of new leads come through digital channels, and roughly 40 percent of inquiries originate from the DACH region. At the same time, the research behavior of its target audiences was measurably shifting toward generative systems such as ChatGPT, Gemini, and Perplexity.
An initial audit identified 24 business-critical search intents, including “conveyor technology manufacturer,” “drive systems for industrial plants,” and “low-maintenance conveyor modules.” In these topic areas, the brand ranked in the top 10 of organic search results but was rarely mentioned in LLM responses. The internal content base was fragmented: many product pages, few topic hubs, hardly any comparison pages, and no consistent semantic connection between solution, use case, and proof points. This is exactly where Zeno Visibility stepped in, to implement GEO Generative Engine Optimization not as a one-off measure, but as a robust authority model.
Challenge
The core problem was not a lack of content, but a lack of machine-readable authority. The existing website answered user queries, but not in the structure LLMs need for selection, weighting, and recommendation. Content was scattered, weakly interconnected, and not semantically precise enough. As a result, generative systems had no consistent trust signal to work with.
There was also strategic pressure: sales reported that initial contacts were increasingly happening with well-informed buyers who had consulted AI assistants before reaching out. If the brand did not appear in those answers, it was already excluded from the set of possible providers in the early decision-making phase. The company therefore needed not just more reach, but a demonstrable presence in generative response systems, combined with a measurable improvement in topical authority.
Solution Approach
Together with Zeno Visibility, a GEO program was launched that operated on three levels: Research, Authority Design, and Distribution. First, the Research Engine analyzed brand presence across ChatGPT, Gemini, Perplexity, Claude, and Copilot. To do this, 24 prioritized prompt clusters were defined to reflect typical research, comparison, and purchase intentions in the target market. From this data, an initial Semantic Authority Score and a gap analysis at the topic, entity, and source level were derived.
Based on this analysis, the Authority System Builder developed a complete authority system for each core keyword. For the first eight topic clusters, 112 semantically interconnected pieces of content were created within six weeks: hub pages, blog articles, FAQs, comparison pages, use case pages, two case studies, product and solution explanations, as well as complementary social posts. The decisive factor was not sheer volume, but structure: each piece of content was aligned with a specific search or answer intent and connected through internal links, shared entities, consistent terminology, and recurring proof points.
At the same time, Schema.org JSON-LD markup for Organization, Product, FAQPage, Article, and BreadcrumbList was automatically generated and integrated into the CMS. The website received a new internal linking architecture with clear hub-and-spoke structures. Zeno Visibility exported the content CMS-ready in WordPress and also in formats for the editorial team, including HTML, JSON-LD, and Gutenberg blocks. For key pages, evidence references, sources, and technical specifications were standardized so that LLMs could not only find the brand, but also classify it as a trustworthy source.
The governance approach was crucial: the project was not set up as a campaign, but as an ongoing authority model. Every new page had to serve a defined semantic purpose, establish an entity connection to a main topic, and link back to at least two existing authority pages. In this way, GEO was operationalized, not just described.
Results
After 90 days, a significant change in AI visibility became evident. The Semantic Authority Score rose from 28 to 64 points. In the 24 tested prompt clusters, the brand was regularly mentioned in responses from ChatGPT, Gemini, and Perplexity in 11 clusters, up from 3. In 7 out of 10 comparison queries, the company appeared for the first time as a recommended provider or a valid alternative.
Traditional performance metrics also improved. Organic traffic to the newly built authority hubs increased by 46 percent within four months. Average dwell time on the thematic pages was 38 percent above the previous website average. Especially relevant for the business: the number of qualified inbound leads from the DACH region increased by 31 percent, while cost per lead in the content-driven channel dropped by 22 percent.
The ROI was also measurable. With project costs in the low six-figure range, pipeline effects were generated within six months that corresponded to a gross margin contribution of around 2.4x the investment. The effect did not come from more traffic alone, but from greater relevance in early decision-making phases. The brand was mentioned more often as a trusted reference in AI answer systems, which directly increased the number of initial meetings and technical inquiries.
Lessons Learned
Summary
With Zeno Visibility, the industrial equipment supplier turned GEO from an abstract trend into a manageable authority model. Instead of merely measuring visibility, the company built a semantically connected content and structural architecture that led to more mentions and recommendations in LLMs. The result was measurably higher AI visibility, more qualified traffic, and a stronger pipeline impact.