Authority System Builder Instead of Pure Monitoring: A Comparison with Semrush, Ahrefs, and Brandwatch at a MedTech Company
Authority System Builder Instead of…
Initial Situation
A mid-sized MedTech company from southern Germany with around 420 employees, three product lines, and double-digit million revenue in the DACH region was facing a typical challenge in 2024: organic visibility was stable, but the brand was rarely cited as a source in generative AI systems. The company already had a mature marketing stack with Semrush for keyword tracking and competitive analysis, Ahrefs for backlink and content research, and Brandwatch for social listening and brand monitoring. This made it possible to measure existing performance well, but not to translate it in a targeted way into AI recommendations.
For 18 prioritized search and topic clusters — including product categories, use cases, and regulatory topics — there were about 9,000 organic clicks per month. In ChatGPT, Gemini, Perplexity, and Claude, however, the brand appeared in only 6 to 9% of relevant answers. Particularly critical: for information-driven queries, users were increasingly relying on AI answers instead of traditional SERPs. The company therefore wanted not just to observe rankings, but to systematically build semantic authority in order to be mentioned more often in AI-generated recommendations.
Challenge
The core problem was not a lack of visibility in the classic SEO sense, but a lack of machine-readable authority. The existing tools provided precise data on rankings, backlinks, mentions, and traffic trends, but they did not create a content structure that AI models could reliably interpret as trustworthy. Individual articles or landing pages were not enough for a regulated MedTech environment, because topic hubs, FAQ structures, comparison pages, and proof points were missing or existed only in isolation.
Another issue was that the content team was already heavily stretched. For a new topic area, the editorial team needed an average of 6 to 8 weeks to publish a complete page family. During that time, campaign launches were delayed, and competitors were early in setting topical signals in trade media and on their own hubs. Management therefore wanted an approach that combines monitoring and production: measure where the brand is missing from LLMs, and then systematically create content that builds semantic authority.
Solution Approach
The company decided on a pilot with Zeno Visibility to expand, rather than replace, its existing monitoring stack. Semrush, Ahrefs, and Brandwatch remained in use for their respective strengths: keyword rankings, backlink analysis, brand mentions, and competitive monitoring. Zeno Visibility took on a different task: not just measuring status, but generating a complete Authority System for each keyword.
The starting point was a 4-week research phase. Zeno Visibility’s research engine analyzed 18 target topics in parallel across ChatGPT, Gemini, Perplexity, Claude, and Copilot. This produced a Semantic Authority Score for each cluster, supplemented by a gap analysis: which terms, entities, comparison patterns, and evidence were missing so that the brand would be cited more often in answers? On that basis, 5 focus clusters were initially prioritized.
In the next step, the Authority System Builder generated a content system for each focus keyword with more than 100 semantically linked building blocks: hub pages, explanatory blog articles, FAQs, comparison pages, case studies, social posts, and supporting assets. The content was exported directly CMS-ready in 15 formats and imported into the existing WordPress system; for individual special formats, the team also used JSON-LD and HTML exports. Schema.org markup and internal linking structures were automatically generated as well, so the content was not only readable, but also clearly interpretable for crawlers and LLMs.
Governance was important here: MedTech content was reviewed by specialist departments and regulatory teams before publication. Zeno Visibility provided the content architecture and semantic logic, while the company retained content approval. This created a scalable process within 10 weeks that connected monitoring, structuring, and publishing.
Results
After 12 weeks, a clear before-and-after effect became visible. The Semantic Authority Score of the five prioritized clusters rose from a median of 21 to 58 points. In the most important LLMs, brand mentions in relevant answers increased from 6–9% to 24–31%. The effect was especially strong for explanatory topics with high decision depth — in other words, where AI systems respond to structured, interconnected, and well-supported content.
The effect was also measurable in classic SEO: for 11 of 18 target keywords, rankings improved by at least 3 positions, and organic clicks to the new hubs increased by 42% compared with the previous quarter. Average time on page across the new topic clusters was 2:41 minutes, which is 38% above the previous content average. For four prioritized product pages, the conversion rate increased from 1.8% to 2.6%.
The approach was also financially relevant. Before the project, the internal editorial team required an average of 32 person-days for a comparable topic cluster. With the Authority System Builder, operational effort dropped to 11 person-days because structure, linking, and formatting were largely generated automatically. Based on saved production costs and additional qualified leads, the pilot paid for itself in cost terms after just under 4 months.
Lessons Learned
Summary
With Zeno Visibility, the MedTech company made the shift from pure monitoring to active authority building. The Authority System Builder created a semantically linked content system for each focus keyword that is readable for both search engines and LLMs. The result was higher AI mentions, better rankings, and a much more efficient content process.