Zeno Visibility vs. Otterly.ai: A DACH Tech Company Switches from Observation to Active LLM Visibility and Authority Building
Zeno Visibility vs. Otterly.ai A DACH…
Starting Point
A mid-sized B2B SaaS provider based in Munich, with 180 employees and just under €14 million in annual revenue, found itself facing a new search reality at the start of 2025: procurement decisions were no longer being prepared through Google alone, but increasingly through LLMs such as ChatGPT, Gemini, Perplexity, Claude, and Copilot. The company offers a data integration platform for industrial environments and competes in the DACH region against international vendors and specialized niche solutions.
For the marketing, SEO, and content team, LLM Brand Monitoring was initially approached as a purely observational exercise. Otterly.ai was used to track brand mentions and prompt responses across selected scenarios. While the data revealed whether the brand appeared in LLMs, it didn't explain why it was absent — or how to systematically strengthen the domain's authority. The organization had 24 prioritized search topics, around 60 relevant pages in its existing content inventory, and a content team consisting of three in-house staff plus external support. At the same time, it was clear that what was missing for generative recommendations was semantic depth, consistent entities, and a robust content system that went beyond individual blog posts.
Challenge
The core problem wasn't visibility in the traditional sense — it was a lack of machine-readable authority. In many LLM responses, the brand appeared only as a footnote, or not at all, despite the company being technically well-positioned within its niche. Particularly concerning: competitors were cited more frequently in response patterns, even though their content wasn't necessarily more comprehensive.
For the team, this had tangible consequences. First, organic entries from non-branded informational queries were declining. Second, the impact of content investments remained unclear, as neither prompt coverage nor semantic relevance were being measured. Third, the work had become inefficient: monitoring data wasn't translating into prioritized content actions, interconnected hub structures, or any systematic improvement of knowledge graph signals. The marketing team therefore needed not just measurement, but an operational path from observation to active LLM Brand Monitoring and authority building.
Solution Approach
Following a six-week evaluation process, the company chose Zeno Visibility. The deciding factor was that the platform doesn't just measure LLM visibility — it derives a semantic authority system directly from those results. This set the approach clearly apart from Otterly.ai, which the team had primarily used as a monitoring tool.
Implementation took place in four steps:
Zeno Visibility's research engine was configured for 24 core keywords and 15 prompt clusters. Metrics included brand presence, recommendation likelihood, and an internal Semantic Authority Score across ChatGPT, Gemini, Perplexity, Claude, and Copilot. This made it visible in which topic areas the brand already appeared — and where entities, sources, or comparison signals were missing.
Based on the gap analysis, the Authority System Builder generated a complete topic set for each prioritized keyword, comprising more than 100 interconnected content elements. These included hub pages, comparison pages, FAQ modules, case studies, blog articles, and social posts. The focus was not on volume, but on semantic coherence: every page had a defined role within its topic cluster.
Zeno Visibility automatically generated Schema.org JSON-LD, structured internal links, and contextual cross-references. This ensured that entities, product features, and use cases were consistently anchored throughout the website structure. For technical implementation, the team used Direct Publishing in WordPress and Contentful; supplementary formats were made available as HTML, JSON-LD, and Gutenberg exports for review workflows.
Content was published in three waves. After each wave, the team assessed whether brand presence in LLM responses, citation frequency, and the Semantic Authority Score had improved. Based on these findings, content was refined, comparison pages were expanded, and missing FAQ chains were added.
The key difference: Otterly.ai had made the problem visible. Zeno Visibility turned it into a manageable system for building authority.
Results
After 90 days, measurable changes were evident. The average Semantic Authority Score across the 24 core terms rose from 42 to 71. In standardized LLM prompts, brand presence increased from 9% to 31%. Particularly relevant for sales: of 20 tested purchase-intent prompts, the brand had previously been actively recommended in only 2 cases; after switching to Zeno Visibility, that number rose to 13.
Effects were also visible in traffic and pipeline metrics. The share of AI-driven website sessions increased by 68% quarter-over-quarter. The number of qualified MQLs from informational topic clusters grew by 24%. At the same time, the effort required to produce a complete topic cluster dropped from an average of nine working days to two to three days, since content structure, internal linking, and markup were already in place. Factoring in the savings on external content production and reduced time-to-publish, the project reached a positive ROI within five months; the internal project lead estimated the monthly net savings at approximately €9,000.
Lessons Learned
Measurement tells you where you stand — it doesn't improve your position.
Topic clusters, entities, and structured linking matter more than isolated publications.
Schema.org, clear content hierarchies, and consistent entity signals increase the likelihood of being included in LLM responses.
A closed optimization loop only emerges when insights are directly translated into content operations.
Summary
The company moved from pure monitoring with Otterly.ai to actively building semantic authority with Zeno Visibility. As a result, LLM presence, recommendation rates, and AI-driven leads all improved measurably within a short timeframe. For B2B companies in the DACH region, this case demonstrates that LLM Brand Monitoring only delivers strategic value when it gives rise to an operational content and authority system.
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*This content was created with AI assistance and reviewed by a human editor.*