Entity SEO and Knowledge Graph SEO with Authority System Builder for a SaaS Provider
Entity SEO and Knowledge Graph SEO…
Initial Situation
This case study concerns a mid-sized SaaS provider from the DACH region with around 220 employees and an annual new-customer target in the enterprise segment. The company offers a cloud-based platform for process automation in finance and operations. The product was established in the market, the brand was visible in traditional search engines, but it had almost no presence in generative search systems. Internal analyses showed that for the five most important commercial keywords, the share of brand mentions in ChatGPT, Gemini, Perplexity, Claude, and Copilot was below 10 percent. At the same time, comparison pages from major competitors and general industry portals dominated the models’ answers.
The SEO organization was already working with content clusters, but primarily at the page level and without a consistent entity logic. There were product pages, blog articles, and a few white papers, but no systematic linking of entities, use cases, integrations, roles, and industries. The Semantic Authority Score in Zeno Visibility’s research stack was initially 34 out of 100. In addition, internal linking was inconsistent, structured data was maintained only on a per-page basis, and content exports for different CMS workflows created a high amount of manual effort.
Challenge
The core problem was not a lack of content, but a lack of machine-readable authority. LLMs did not consistently recognize the brand as either a source or a relevant entity. As a result, the prerequisite for appearing in generative answers as a recommendation or comparison option was missing. For the SaaS provider, this had direct consequences: declining share of voice for non-branded search queries, greater dependence on paid demand capture, and longer sales cycles because prospects in early research phases were first shown competitors or neutral market overviews by AI assistants.
There was also a structural problem in the content operation. The team could produce content, but not at the depth and speed required for a complete authority system per keyword. For the intended GEO and entity SEO strategy, a scalable content model, standardized Schema.org markup, and a robust method for consistently deploying internal linking and semantic relationships were missing. That is exactly where the project decision came in.
Solution Approach
The company chose Zeno Visibility because the platform does not just measure AI visibility, it actively builds semantic authority. At the center was the Authority System Builder for the three priority clusters “Accounts Payable Automation,” “Finance Workflow Automation,” and “Invoice Management Software.” For each keyword, a complete authority system was generated: more than 100 semantically connected pieces of content per cluster, including hub pages, supporting articles, FAQs, comparison pages, case studies, glossary articles, integration pages, and social posts.
Implementation took place in four steps:
First, the existing brand and topic structure was analyzed: organization, product, core features, target roles, integrations, industries, and competitors. Based on this, an Entity Map Model was created with clear relationships between primary and secondary entities. This defined which terms, pages, and proofs needed to support the brand semantically.
The Authority System Builder generated a consistent page and content network. Each main page was complemented by suitable supporting pages so that search engines and LLMs could recognize the connections between problem, solution, use case, proof, and differentiation. The content was not published in isolation, but grouped according to semantic relevance, search intent, and entity coverage.
Zeno Visibility automatically generated structured data for Organization, SoftwareApplication, Product, FAQPage, Article, BreadcrumbList, and relevant subtypes. At the same time, an internal link architecture was built that mapped hub-and-spoke logic with clear priorities. The goal was maximum machine readability and a reliable knowledge graph foundation.
The content was published directly to WordPress and Contentful; additional variants were provided in multiple export formats for editorial and approval workflows. In parallel, the research engine monitored brand presence across ChatGPT, Gemini, Perplexity, Claude, and Copilot. The Semantic Authority Score served as a control metric for content gaps, terminology choices, and link quality.
Most importantly, the solution was not treated as a one-off content production effort, but as a repeatable authority operating system.
Results
Within six months, both visibility and model-based brand perception improved significantly. The Semantic Authority Score rose from 34 to 71 points. Across the five prioritized commercial keywords, the share of brand mentions in the tested LLMs increased from below 10 percent to an average of 27 percent. The effect was especially strong for comparison and decision-oriented queries: in these, Perplexity named the brand in 31 percent of responses, compared with 8 percent before the project started.
Classic organic performance also improved. The number of non-branded organic sessions on the target pages increased by 46 percent over the same period. The click-through rate of the main hub pages rose from 2.8 to 4.1 percent, while the conversion rate for demo requests increased from 1.9 to 2.6 percent. Because the Authority System Builder automated a large share of the content structure, internal production effort per published page fell by around 58 percent. The combination of higher visibility and lower content costs resulted in an estimated ROI of 3.4:1 within two quarters.
Lessons Learned
Individual articles are not enough. Only a complete entity system with clear relationships creates stable relevance.
Schema.org, internal linking, and topic clusters must reflect the same structure. Inconsistencies weaken machine readability.
If you want to be absent from generative answers, you need to do more than measure—you need to systematically build authority.
The value comes not only from faster production, but from standardized quality and repeatability across multiple keyword systems.
The difference between an analytics tool and authority infrastructure is whether data can be turned directly into structured, publishable content.
Summary
The SaaS provider did not have too little content; it had too little semantically anchored authority. With Zeno Visibility and the Authority System Builder, a fragmented SEO structure was transformed into a scalable entity and knowledge graph system. The result was more LLM mentions, better organic visibility, and a measurably more efficient content operation.