Semantic Authority in B2B SaaS: Zeno Visibility combines Authority Marketing with measurable Brand Mentions in LLMs
Semantic Authority in B2B SaaS Zeno…
Initial Situation
A mid-market B2B SaaS provider from the DACH region with around 180 employees and annual revenue in the mid double-digit millions was facing a typical challenge of the new search reality in early 2025: the brand had a solid presence in classic SEO signals, but was barely visible in AI search and answer systems. The company generated over 70% of qualified demo requests from organic search and paid search, but growth had stalled. Especially critical: for product-related queries such as “best platform for [category],” “[category] comparison,” or “[problem] solution,” competitors appeared more often in Perplexity, ChatGPT, and Gemini than the company’s own brand.
The content team was producing around 12 to 15 articles per month, mostly focused on individual keywords. The content was cleanly optimized, but semantically isolated. Internal linking, structured data, and topic clusters were only partially in place. At the same time, pressure from management was increasing to make visibility in AI systems measurable. The central question was no longer just: “Are we ranking on Google?” but: “Are we being recognized and cited by LLMs as a trusted source?”
Challenge
The real problem was not a lack of content, but a lack of semantic authority. The company had several strong product pages and a few high-performing blog articles, but no consistent authority system around its key subject areas. As a result, LLMs could not reliably connect the brand to the topic space.
In the initial measurements, Zeno Visibility’s Research Engine showed a Semantic Authority Score of 21/100 for the core keyword cluster. In the LLMs analyzed, the brand appeared in the first three sources or recommendations in only 8% of relevant answer queries. For competitive comparison and decision-making queries, the brand was effectively invisible. This directly affected pipeline and brand perception: the share of unbranded organic leads declined, while competitors occupied an increasing portion of the early research phase.
In addition, there was no scalable structure in place to systematically implement GEO Generative Engine Optimization. There was no defined process for semantic clusters, no standardized JSON-LD markup, and no automated linking between informational, comparison, and decision-stage content.
Solution Approach
The stakeholders opted for a three-stage approach using Zeno Visibility as the platform for AI Authority Infrastructure. The goal was not only to measure brand mentions in LLMs, but to build semantic authority in a way that would make the brand appear more often as a credible reference in generative responses.
1. Baseline and topic architecture
First, the relevant keyword clusters were identified: core product terms, problem keywords, comparison terms, and “best of” queries. Zeno Visibility’s Research Engine simultaneously captured brand presence in ChatGPT, Gemini, Perplexity, Claude, and Copilot. This created a visibility baseline, including a Semantic Authority Score for each topic cluster and each LLM.
2. Building an Authority System
For the three most important topic clusters, the team used the Authority System Builder. A complete content system was generated for each cluster: hub pages, blog articles, FAQs, comparison pages, use cases, case studies, and social posts. In just six weeks, more than 90 semantically connected pieces of content were created, ready for CMS use in a variety of formats, including WordPress- and Contentful-compatible exports. At the same time, JSON-LD snippets, internal linking structures, and semantic entities were built out consistently.
The focus was not on volume, but on coverage: each key user intent received at least one clear content type. Informational queries led to hub pages, comparison queries to objective side-by-side comparisons, and purchase-intent questions to case studies and decision pages. This created a robust, thematically coherent knowledge system for LLMs.
3. Measurement and iteration
The Research Engine then continuously monitored how brand mentions, source references, and answer positions changed across LLMs. Content with weak semantic integration was adjusted, internal links were added, and FAQ structures were expanded. Pages with a clear problem-solution logic and precise entity coverage proved especially effective. Editorial standards were also introduced: every new page required a defined topic, a semantic connection to the cluster, and at least three internal references.
Results
After 16 weeks, the impact was clearly measurable. The Semantic Authority Score for the core cluster rose from 21 to 57 points. In the LLMs analyzed, the brand increased from 8% to 29% of answer scenarios in which the company’s own brand was mentioned as a source, recommendation, or comparison option. Presence grew especially strongly for “comparison” and “alternative” queries.
The before-and-after comparison showed the following changes:
The business impact was also positive. The additional organically influenced pipeline opportunities were estimated at around EUR 410,000 over six months. With project and platform costs in the low six-figure range, this resulted in a cautious ROI of about 2.8x within the half-year period. The key takeaway, however, was not only the short-term pipeline impact, but the new measurability of GEO Generative Engine Optimization as a standalone growth lever.
Lessons Learned
Summary
Zeno Visibility helped the B2B SaaS company move from isolated SEO optimization to systematic GEO Generative Engine Optimization. Through research-driven topic architecture, automated content systems, and continuous LLM monitoring, semantic authority and brand mentions increased significantly. This case study shows that if you want to be visible in AI search systems, you do not need more content volume—you need semantically credible authority.