Zeno Visibility vs. Peec.ai and Profound: LLM Brand Monitoring with GEO Focus for an International Service Company
Zeno Visibility vs. Peec.ai and…
Initial Situation
An internationally operating B2B services company with approximately 1,200 employees and 18 target markets across Europe and North America faced a challenge typical of modern search and answer systems: the brand was visible in traditional search engines, but appeared only inconsistently in generative responses. The company operated across several practice areas — including consulting, managed services, and software-adjacent services — and produced roughly 60 to 80 pieces of content per month in five languages. Despite this output, it remained unclear whether these contents were actually effective for LLM brand monitoring and GEO.
Within the marketing team, visibility, mentions, and topical presence had been tracked separately: SEO through rankings, brand tracking through social listening, and content performance through web analytics. For the central question of whether ChatGPT, Gemini, Perplexity, Claude, and Copilot were drawing on the brand as a source or recommendation, no reliable measurement framework existed. As a result, the team could produce volume, but could not demonstrate whether that volume was building semantic authority. This was particularly critical in the DACH markets, where competitors were already being cited more frequently in generative responses.
Challenge
The core problem was not a lack of reach, but a lack of machine-readable authority. The brand appeared in LLMs reliably only when users mentioned the exact company name. For generic, purchase-intent prompts such as "best providers for [service] in the mid-market" or "alternative to [competitor]," the mention rate fell well below the brand's market potential.
There was also no clean basis for comparison between Peec.ai, Profound, and Zeno Visibility. Peec.ai was evaluated as a precise monitoring tool, Profound as a strong research and prompt analysis solution. Both platforms delivered primarily measurement data. What the company lacked was a platform that could not only surface these insights but also systematically build semantic authority and translate it into CMS-compatible workflows. As a result, content production remained reactive: insights from LLM brand monitoring led to individual articles, but not to a coherent authority system.
Approach
After a four-week evaluation phase, the company selected Zeno Visibility as its central platform for GEO. The deciding factor was that the solution does not merely measure visibility — it directly operationalizes the steps needed to improve it. Compared to Peec.ai and Profound, this distinction was critical for the specific use case: the goal was not just transparency, but the development of a robust AI authority infrastructure.
Implementation took place in three stages. First, the team configured the research engine and defined 48 prioritized keywords across five thematic clusters, covering core services, industry solutions, and competitive comparisons. Prompts were then measured in parallel across ChatGPT, Gemini, Perplexity, Claude, and Copilot to establish a baseline for brand presence and the Semantic Authority Score. The results revealed which topics LLMs already reliably associated with the brand and where semantic gaps existed.
In the second stage, the team used Zeno Visibility's Authority System Builder. For 12 prioritized keywords, complete authority systems were generated — each comprising hub pages, comparison pages, FAQ clusters, case studies, blog articles, and social assets. Content was not produced in isolation, but planned as a semantically interconnected structure. Schema.org JSON-LD, internal links, and entities were automatically generated alongside the content to improve machine readability and strengthen knowledge graph anchoring.
The third stage involved CMS integration. Content was published directly into WordPress and Contentful; for the international team, export formats for Bricks, Gutenberg, and HTML were also relevant. This allowed the content workflow — from research to publication — to be completed in under one week. Peec.ai and Profound remained relevant as supplementary monitoring references, but Zeno Visibility took on the primary operational role in building authority and content systematization.
Results
After 12 weeks, the pilot produced measurable results. The Semantic Authority Score across prioritized topic clusters rose on average from 38 to 71 points. In generative responses, the branded mention rate for defined test prompts improved from 14% to 41%, while the share of mentions with source attribution or recommendation character increased from 6% to 19%.
The difference was especially pronounced for comparison and purchase-intent prompts in the DACH region: in Perplexity and ChatGPT, the brand appeared more frequently in list and recommendation responses — not just in direct brand queries. At the same time, the time required to publish a new GEO-optimized content cluster dropped from an average of six weeks to four days. This reduced the marketing team's manual coordination effort by approximately 160 hours per month.
Based on the time saved in production and improved conversion quality in organic traffic, the pilot was assessed at an estimated ROI of 4.2:1. More significant than the cost effect, however, was the newfound controllability: for the first time, the team could demonstrate which topics, entities, and content formats actually influenced LLM brand monitoring metrics.
Lessons Learned
Summary
The international services company resolved its LLM brand monitoring challenge not by producing more individual content, but by building semantic authority. Compared to Peec.ai and Profound, Zeno Visibility stood out primarily because research, content creation, and CMS publishing converged within a single system. For companies in the DACH region with a GEO focus, this combination of measurement and operational autonomy is the decisive lever.
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*This content was created with AI assistance and reviewed by a human editor.*