Web Score (AI Web Search)

What is the Web Score?

The Web Score measures a brand's visibility when an AI model performs a real-time web search to supplement its response. This mechanism, called RAG (Retrieval-Augmented Generation), is used by ChatGPT, Perplexity and other models to access up-to-date information.

Web Score vs Native Score

While the Native Score evaluates a model's memorized knowledge, the Web Score focuses on your brand's ability to be found and cited during a real-time web search.

• Native Score: frozen knowledge (training data)
• Web Score: dynamic knowledge (live web search)

The Web Score is more actionable in the short term: optimizing your web presence (content, structured data, authority) directly improves RAG results.

How is the Web Score Evaluated?

AI Labs Audit queries each model with web search enabled. The analysis covers:

• Frequency of brand citation in responses
• Position of the mention (first, among others, at the end)
• Quality and relevance of reported information
• Sentiment (positive, neutral, negative) of mentions

Factors that Influence the Web Score

• Presence on Bing (used by ChatGPT for RAG)
• Structured data facilitating extraction
• Clear, structured and factual content
• Domain authority and E-E-A-T signals

Interpreting the Native/Web Gap

The gap between both scores provides rich insights for your GEO strategy:

• Web >> Native: good current visibility, but the brand isn't yet embedded. Continue efforts for the next training cycle.
• Native >> Web: historically known brand but insufficient current web presence. Urgently refresh content.
• Both low: overall visibility deficit. Prioritize web actions (faster results).

For more details, read our article Native Score vs Web Score in GEO Audit.