AnswerMonk — AI Search Visibility Platform

Bella Derma AI Visibility — laser hair removal in Berlin | AnswerMonk

Analyzed on May 22, 2026 · Engines: ChatGPT, Claude, Gemini, Perplexity · Methodology

This report analyzes AI search visibility for Bella Derma (belladerma.de) in the laser hair removal in Berlin category — measuring how often the brand appears in AI-generated answers across all major LLMs.

AI Visibility Score

Bella Derma has an AI share-of-voice score of 33% for the query category "laser hair removal 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 laser hair removal in Berlin category in which Bella Derma was named by each AI engine.

AI EngineBella Derma Appearance RateComposite Score Weight
Claude0%20%
Gemini50%35%
ChatGPT50%35%

Competitor Rankings in AI Search

The following brands were most frequently cited by AI engines in response to "laser hair removal in Berlin" queries. Citation share represents weighted appearance rate across all engines for this category.

RankBrandAI Citation Share
1Laser ONE59%
2S-thetic Derma36%
3Sanft & Schön32%
4Dermatologikum Berlin32%
5LaserAzor27%

How this report was generated

AnswerMonk builds a network of 25–30 intent-based prompts for the laser hair removal 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 22, 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 laser hair removal in Berlin category. These reflect how real buyers phrase requests to ChatGPT, Gemini, Claude, and Perplexity when seeking recommendations.

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 Bella Derma

Bella Derma appeared in responses from Gemini and Chatgpt but was absent from Claude for the laser hair removal in Berlin category. This engine-split pattern typically indicates that the sources Claude retrieve for this category — which differ from those used by Gemini and Chatgpt — do not yet include Bella Derma. Competitors found in the gap engines: Laser ONE, S-thetic Derma, Sanft & Schön.

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 Bella Derma

The primary levers for improving AI citation share in the "laser hair removal 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.

How to improve AI citations →

GEO vs SEO: understanding the difference →

What are ChatGPT citations? →

What is AI share of voice? →

Run a free AI visibility audit for your brand →