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 — a mechanism called 'web search' or 'grounding' depending on the provider, 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 a client's web presence (content, structured data, authority) directly improves web-mode 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 in web mode)
• 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.