What is AI visibility and why does it matter?

AI visibility measures how prominently your brand appears in AI-generated answers from systems like ChatGPT, Claude, and Gemini. As more users rely on AI assistants for information, being cited by these systems becomes crucial for brand awareness and traffic.

Which AI systems does ZagosaIQ track?

ZagosaIQ tracks your brand's visibility across 5 major AI systems: ChatGPT (OpenAI), Claude (Anthropic), Gemini (Google), Bing Copilot (Microsoft), and Perplexity AI.

How does Answer Engine Optimization (AEO) differ from traditional SEO?

Answer Engine Optimization (AEO) focuses on making your content citable by AI systems, while traditional SEO focuses on search engine rankings. AEO emphasizes structured content, FAQ schemas, authoritative citations, and clear step-by-step guidance that AI systems prefer to cite.

What is the AI Visibility Score?

The AI Visibility Score is a 0-100 metric that measures how prominently your brand appears in AI-generated answers for your tracked keywords. It factors in mention frequency, citation likelihood, and competitor comparison across all tracked LLMs.

What is AI searchability?

AI searchability is the degree to which your content can be found, understood, and cited by AI-powered search and answer systems like ChatGPT, Claude, Gemini, and Perplexity. Unlike traditional searchability which focuses on keyword matching and indexing, AI searchability measures how effectively your content is structured for extraction by large language models. Content with high AI searchability uses clear definitions, step-by-step formats, FAQ structures, and consistent entity signals.

What is LLM visibility and how is it measured?

LLM visibility refers to how prominently and frequently a brand is referenced by large language models such as ChatGPT, Claude, Gemini, Bing Copilot, and Perplexity when generating responses. LLM visibility is measured by scanning AI responses for brand mentions, citation frequency, sentiment, and positioning. ZagosaIQ tracks LLM visibility across all major models in real time.

How do I improve my AI searchability?

To improve AI searchability: 1) Audit your current visibility across LLMs, 2) Structure content with question-based headings and clear definitions, 3) Implement FAQ and HowTo schema markup, 4) Build consistent brand entity signals across all platforms, 5) Allow AI crawler access (GPTBot, ClaudeBot, PerplexityBot), and 6) Monitor and iterate using a tool like ZagosaIQ.

How does ZagosaIQ's AI content generation work?

ZagosaIQ uses a 4-stage AI content engine: 1) Strategic Planning - two independent AI strategists analyse your data and existing actions to build a comprehensive plan, 2) Content Creation - a specialist AI creates ready-to-implement content that labels what to update versus what is new, 3) Fact-Checking - an independent AI verifies every claim and checks for duplication with existing work, 4) Humanisation - an editor AI refines the tone to read naturally, targeting 95%+ humanisation scores. The system reviews your existing completed actions before generating to avoid duplication.

What is citation drop analysis?

Citation drop analysis is a feature that automatically detects when your brand's likelihood of being cited by AI systems decreases. ZagosaIQ compares recent citation data against previous periods, identifies which AI models dropped your brand, detects rising competitors, classifies root causes (such as competitor displacement, source loss, or LLM-specific shifts), and generates AI-assisted recommendations for recovering your citation position.

Ethical Policy | ZagosaIQ

ZagosaIQ is committed to responsible AI usage, data transparency, and fair business practices. This ethical policy outlines the principles that guide how we build, operate, and improve our AI visibility tracking platform.

Responsible AI Usage

We query AI systems using authentic prompts that reflect real user behaviour. We do not manipulate AI responses, inject misleading data, or engage in practices that could deceive AI systems or distort the visibility data we provide. Our scanning methodology is designed to provide honest, accurate results that reflect genuine AI behaviour.

Data Transparency

We are transparent about how our platform works and how we use your data. Our visibility scores are based on real AI responses, not estimates or projections. We clearly explain our scoring methodology and provide the underlying data so you can verify results independently. We do not cherry-pick favourable data points or hide unfavourable results.

Fair Business Practices

We provide honest, accurate visibility data even when the results are not favourable. We respect the intellectual property and privacy of all parties involved. Our comparison pages present factual information without misleading claims. We price our services fairly and transparently, and we honour all commitments made to our customers.