Mariam Omar AI Visibility — face lift in Berlin | AnswerMonk
Analyzed on May 23, 2026 · Engines: ChatGPT, Claude, Gemini, Perplexity · Methodology
This report analyzes AI search visibility for Mariam Omar (mariam-omar.de) in the face lift in Berlin category — measuring how often the brand appears in AI-generated answers across all major LLMs.
AI Visibility Score
Mariam Omar has an AI share-of-voice score of 5% for the query category "face lift in Berlin".
Share of voice measures how often a brand appears in AI-generated answers, weighted by rank position and engine market share (ChatGPT 35%, Gemini 35%, Claude 20%, Perplexity 10%). A score of 100% means the brand appeared first in every prompt on every engine. A score of 0% means it did not appear in any response.
Engine-by-Engine Breakdown
Appearance rate is the percentage of intent prompts for the face lift in Berlin category in which Mariam Omar was named by each AI engine.
| AI Engine | Mariam Omar Appearance Rate | Composite Score Weight |
|---|---|---|
| Claude | 0% | 20% |
| Gemini | 14% | 35% |
| ChatGPT | 0% | 35% |
Competitor Rankings in AI Search
The following brands were most frequently cited by AI engines in response to "face lift in Berlin" queries. Citation share represents weighted appearance rate across all engines for this category.
| Rank | Brand | AI Citation Share |
|---|---|---|
| 1 | Sinis Klinik Berlin | 35% |
| 2 | MEOCLINIC | 35% |
| 3 | Helios Berlin-Buch Hospital | 30% |
| 4 | Schlosspark Hospital Berlin | 26% |
| 5 | Klinik am Wittenbergplatz | 26% |
How this report was generated
AnswerMonk builds a network of 25–30 intent-based prompts for the face lift in Berlin category — the natural-language queries real buyers send to ChatGPT, Claude, Gemini, and Perplexity. Each prompt is fired against all four engines. Responses are parsed, brand appearances recorded, and results aggregated into the share-of-voice score above using a market-share weighted formula.
Data reflects AI engine outputs as of May 23, 2026. AI outputs change as models are updated and as new content enters training and retrieval indexes. Scores should be interpreted as a point-in-time snapshot. Full methodology →
Sample prompts used in this analysis
The following are representative examples of the buyer queries run across AI engines for the face lift in Berlin category. These reflect how real buyers phrase requests to ChatGPT, Gemini, Claude, and Perplexity when seeking recommendations.
- Find the best face lift in Berlin
- What are the most trusted face lift in Berlin?
- Which face lift has the highest customer ratings in Berlin?
- Compare the top face lift available
- Who are the most reputable face lift near Berlin?
- What face lift do industry experts recommend?
Brand appearance in responses to these prompts is what the share-of-voice score above measures. A brand that appears across all prompt types scores higher than one that only appears for a narrow query variant.
What this audit found: engine-level breakdown for Mariam Omar
Mariam Omar appeared in responses from Gemini but was absent from Claude and Chatgpt for the face lift in Berlin category. This engine-split pattern typically indicates that the sources Claude and Chatgpt retrieve for this category — which differ from those used by Gemini — do not yet include Mariam Omar. Competitors found in the gap engines: Sinis Klinik Berlin, MEOCLINIC, Helios Berlin-Buch Hospital.
- Claude: 0% appearance rate across tested prompts — brand not cited in any response
- Gemini: 14% appearance rate across tested prompts — partial coverage
- Chatgpt: 0% appearance rate across tested prompts — brand not cited in any response
The engine-level gap is the most actionable finding. Each AI engine retrieves from different source layers — ChatGPT prioritises web-browsed reviews and editorial content, Gemini pulls heavily from Google's indexed data, Claude retrieves from its training corpus plus browsed sources, and Perplexity surfaces real-time web results. A brand absent from one engine is typically under-represented in that engine's primary source type, not absent from the web entirely.
Improve AI search visibility for Mariam Omar
The primary levers for improving AI citation share in the "face lift in Berlin" category are: citation source coverage (appearing on the platforms AI engines retrieve most frequently), entity consistency across the web, and content that directly answers the buyer prompts run in this analysis.