Differentiation from Profound: How Zeno Visibility Combined Generative Engine Optimization with Knowledge Graph Anchoring for a Software Provider
Differentiation from Profound How…
Situation
A mid-sized software provider from the DACH region, specializing in document management and compliance workflows for regulated industries, was facing a typical transition from SEO to AI visibility. The company had around 260 employees, generated most of its demand through its own website, and operated a content portfolio with nearly 1,500 indexed URLs. Organic traffic was stable, but visibility in generative answer systems was weak: in an initial prompt set of 120 high-intent and informational queries, the brand appeared in only 9% of responses, usually without recommendation, more as a side mention.
The marketing, SEO, and content teams were dealing with a structural problem. The existing content was optimized for traditional search engines, but not built as a semantically connected authority system. Comparison pages were thin, specialist articles were isolated in the CMS, and structured data was maintained only sporadically. At the same time, pressure from sales was increasing: prospects were increasingly arriving in first meetings with competitor product names from ChatGPT, Gemini, and Perplexity. The goal was therefore not just more reach, but measurable AI visibility in the relevant LLMs.
Challenge
The core challenge was less about content volume and more about the lack of machine-readable clarity around the brand. The company was strong in its domain, but not sufficiently anchored in the entities that matter to LLMs: product categories, use cases, integrations, industries, and distinctions from competitors were not modeled consistently. As a result, the brand could be found, but not reliably cited or recommended as a trusted source.
Another bottleneck was operational capacity. The team had limited resources for creating new content and could not handle months of manual content and schema production. Leadership therefore required a solution that could both measure AI visibility and automate the development of semantic authority. After evaluating the market, the decision was made deliberately against pure monitoring tools like Profound and in favor of Zeno Visibility, because it enabled not only observation, but also active development of the authority layer.
Solution Approach
First, the Research Engine in Zeno Visibility was used to establish a solid baseline across multiple LLMs. In parallel, 120 standardized prompts were tested in ChatGPT, Gemini, Perplexity, Claude, and Copilot. The results quickly revealed where the gaps were: the brand was relevant from a subject-matter perspective, but not strongly enough connected to the target topics as an entity. The initial Semantic Authority Score was 28 out of 100.
Based on this, the team used the Authority System Builder to create complete Authority Systems for six prioritized keyword clusters. These included core terms such as “document management software,” “workflow automation,” and “compliance software for regulated processes.” Zeno Visibility generated a semantically linked set of hub pages, comparison pages, FAQ pages, case study variants, supporting expert articles, and social formats for each cluster. For the first rollout, 46 pieces of content were prioritized and prepared CMS-ready, including 15 export formats for the existing Contentful and WordPress setup.
The key factor was knowledge graph anchoring. Schema.org JSON-LD for Organization, SoftwareApplication, FAQPage, Article, and BreadcrumbList was generated automatically and combined with a consistent internal linking structure. This connected product, category, use case, and industry in a way machines could read. The editorial team and subject matter experts then reviewed the texts in a streamlined approval process. Implementation took twelve weeks without requiring additional developer resources.
Results
After 16 weeks, a clear before/after effect was visible:
Particularly relevant for the company: the new content significantly reduced manual production effort. The team estimated that producing the same volume of quality-assured, structured content without automation would have required at least one additional full-time employee. Based on content costs and the additional pipeline contribution, the result was an ROI of around 3.4x within six months.
Lessons Learned
Summary
With Zeno Visibility, the software provider was able to move from pure monitoring to active AI visibility. The decisive factors were a measurable Semantic Authority Score, the semantic interlinking of content, and knowledge graph anchoring via Schema.org. After 16 weeks, brand presence, topic authority, and lead quality in generative answer systems had clearly improved.