Source analytics
Source-read volume
Source analytics shows which domains AI systems read while answering prompts.
It is one of the clearest ways to see where answer support comes from. Before an AI system names a brand, it often reads pages that shape the answer.
Start with source-read volume. It tells you how often sources are being used.
Read-to-named rate
Read-to-named rate shows how often a source that was read also gets named in the answer.
This is a key gap. Being read is not the same as being recommended.
Source mix
Source mix groups reads by type. The dashboard uses types like Your site, UGC, Social, Editorial, Reviews, Reference, Competitor, and Corporate.
Use this to understand what kind of web proof AI systems rely on.
Trusted page patterns
Trusted page patterns show which pages or domains appear again and again.
Do not copy blindly. Look for the proof style and page type.
Source analytics
Source analytics shows which URLs and domains help shape AI answers before mentions happen.
Pages AI systems trust
Pages AI systems trust are pages that repeatedly support answers.
They may be your pages, competitor pages, review pages, or third-party pages.
| Source signal | Simple meaning |
|---|---|
| Unique sources | How many different domains appeared |
| Source reads | How often domains were visited |
| Read to named rate | How often a read source was also named |
| Reads of your site | How often your own domain was read |
Source opportunities
Source opportunities are places where stronger proof could help. This might be an owned page, a third-party page, or a competitor-favored source.
Evidence review loop
Review the source, the prompt answer, and the named competitors together.
Goal: review a source opportunity. Inputs: source domain, prompt answer, competitor mention, page type. Steps: decide whether to improve an owned page, create proof, or watch the pattern. Output: one suggestion card if the action is clear.