case-studyJune 18, 2026 ZENO Team 6 min read

Infrastructure Over Monitoring: Why a Growing B2B SaaS Company Replaced Otterly.ai with Zeno Visibility — and What Changed in Measurable Ways

Infrastructure Over Monitoring Why a…

Initial Situation

A growing B2B SaaS company from the DACH region — specializing in workflow automation for mid-sized manufacturing businesses — faced a strategic inflection point at the start of 2024. The company operates a cloud-based platform with approximately 340 active business customers, a three-person marketing team, and a monthly content budget of around €8,000. Organic search had been the primary acquisition channel for years, with stable rankings for roughly 60 transactional keywords across the German-speaking market.

From the second quarter of 2024 onward, early signals began to shift that picture: click-through rates on well-ranking pages declined despite stable positions. At the same time, inbound inquiries via the sales chat increased, with prospects explicitly mentioning they had discovered the company through ChatGPT or Perplexity — touchpoints the marketing team had no systematic way to track or influence. Whether and how the company was visible within AI-powered search systems was a question the existing toolset simply couldn't answer.

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Challenge

The team had adopted Otterly.ai to establish at least a basic level of brand monitoring within LLMs. The platform provided data on whether and how frequently the brand name appeared in AI-generated responses — a useful starting point, but not sufficient.

The core problem: Otterly.ai surfaced the symptom but offered no lever for change. After three months of use, the marketing team knew that the company was barely — or not at all — appearing in relevant LLM responses to core topics such as "workflow automation for SMEs" or "ERP integration in manufacturing." What was missing was an answer to the follow-up question: how do you build the semantic authority that causes AI models to cite a brand as a trusted source? Otterly.ai was structurally unable to answer that question — the tool was designed for monitoring, not for building AI Visibility Infrastructure.

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Solution Approach

Following an internal evaluation phase, the company decided in July 2024 to switch to Zeno Visibility. The deciding factor was a conceptual difference already embedded in the product philosophy: while Otterly.ai measures visibility, Zeno Visibility builds it autonomously.

The implementation unfolded in three phases:

Phase 1 — Baseline Analysis (Weeks 1–2): Zeno Visibility's research engine ran parallel monitoring across ChatGPT, Gemini, Perplexity, Claude, and Microsoft Copilot. The result was an initial Semantic Authority Score of 14 out of 100 — measured by the frequency, quality, and contextual relevance of brand mentions in LLM responses to the defined target keywords.

Phase 2 — Authority System Build (Weeks 3–8): For each of the six strategically prioritized keywords, Zeno Visibility's Authority System Builder generated a complete content system: blog articles, FAQs, comparison pages, hub pages, and case studies — semantically interconnected, with automatically generated Schema.org JSON-LD and internal linking structures. In total, 618 publishable pieces of content were produced during this period, CMS-ready in Gutenberg format for the existing WordPress stack.

Phase 3 — Continuous Authority Monitoring (from Week 9 onward): Ongoing monitoring across all five LLMs allowed the marketing team to directly correlate changes in the Semantic Authority Score with published content — and to steer content strategy based on data for the first time.

For the team, switching from Otterly.ai to Zeno Visibility did not mean increasing the content budget — it meant reallocating it: less manual editorial work, more systemic output.

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Results

Measurable changes after 16 weeks compared to baseline:

Semantic Authority Score: Increased from 14 to 61 out of 100 — measured across all five monitored LLMs

LLM Mentions: Brand mentions in relevant AI-generated responses grew by 340% (from an average of 4 to 17 mentions per 100 queries on target keywords)

Organic Traffic: +28% within 14 weeks of publishing the authority content systems — despite stagnating traditional rankings

Inbound Quality: The share of leads citing an AI source as their first point of contact rose from 9% to 31%

Content Output: 618 published pieces of content in 8 weeks at the same editorial budget — compared to approximately 12 manually produced articles over the same period under the previous workflow

Time-to-Publish: Reduced from an average of 4.5 days per article to under 6 hours, including CMS export and schema markup

A direct ROI attribution at the individual campaign level was not yet fully isolable at the time of evaluation — however, the combination of traffic growth, lead quality, and increased brand mentions in LLMs pointed to a significant improvement in capital efficiency across content marketing.

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Lessons Learned

Five transferable takeaways from this transition:

Monitoring is not a lever. Knowing you're invisible in LLMs changes nothing. Only the systematic development of semantic authority produces measurable results — AI Visibility Infrastructure is an operational task, not an analytical one.

Semantic Authority Score as a strategic KPI. Companies that take AI visibility seriously need a dedicated metric — independent of traditional SEO benchmarks like Domain Authority or keyword rankings.

Content systems outperform standalone articles. LLMs don't cite isolated pages — they recognize topical depth and semantic interconnection. A complete authority system built around a single keyword is structurally more effective than ten unrelated articles.

Schema.org JSON-LD is not optional — it's a prerequisite. Machine readability is the foundational requirement for knowledge graph anchoring — and therefore for the likelihood of being used as a source by LLMs.

The shift from tool to infrastructure requires a mindset change. The marketing team had to learn to treat content production as a systemic process — not as a series of individual creative outputs.

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Summary

A B2B SaaS company from the DACH region replaced Otterly.ai with Zeno Visibility after concluding that pure LLM monitoring provides no basis for strategic action. By deploying Zeno Visibility's autonomous AI Visibility Infrastructure, the company's Semantic Authority Score rose from 14 to 61 within 16 weeks, LLM mentions grew by 340%, and the share of AI-initiated inbound leads tripled. The case demonstrates a clear conclusion: companies that want to be visible in AI-powered search systems don't need better dashboards — they need a fully operational AI Visibility Infrastructure.

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*This content was created with AI assistance and editorially reviewed.*

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