Source metrics

Definitions and formulas for citation count, used %, avg citations, and source authority — computed at both domain and URL granularity.

Overview

Source metrics track how AI models use and cite content sources when generating responses. These metrics reveal which domains have content authority — the ability to influence what AI search engines say.

Sources are analyzed at two levels:

• Domain level — aggregated across all URLs from a domain (e.g., all pages on techcrunch.com)
• URL level — individual page performance (e.g., techcrunch.com/article-1)

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Citation count: total references to a source

Definition: Total number of times a source is explicitly referenced in AI responses.

Formula

Citation count = Total citations of the domain (or URL)

Each citation in a response counts separately. If one response cites two different URLs from the same domain, that’s two citations for the domain.

Worked example: citation count

Domain: techcrunch.com
Time period: Last 7 days

Response 1: Cited techcrunch.com/article-1, techcrunch.com/article-2 (2 citations)
Response 2: Cited techcrunch.com/article-1 (1 citation)
Response 3: Cited techcrunch.com/article-3 (1 citation)
Response 4: No citations from techcrunch.com

Citation count = 2 + 1 + 1 = 4

Content from techcrunch.com was explicitly cited 4 times across 3 responses.

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Average citations per response

Definition: The average number of times a source is cited per AI response where it appears.

Formula

Average citations = Total citations of source / Responses where source was cited

Higher values indicate deeper trust — when an AI model uses the source, it tends to cite multiple pages or cite it multiple times.

Worked example: average citations

Domain: techcrunch.com
Time period: Last 7 days

Response 1: 2 citations from techcrunch.com
Response 2: 1 citation from techcrunch.com
Response 3: 1 citation from techcrunch.com

Total: 4 citations across 3 responses

Average citations = 4 / 3 = 1.33

When AI uses techcrunch.com, it cites an average of 1.33 unique URLs from the domain per response.

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Used: how often a source appears

Definition: The share of AI responses that cited this source within the selected time window. The same definition applies at both domain and URL level.

Formula

Used (%) = (Responses that cited the source / Total responses analyzed) x 100

Citation depth — how many URLs from the same domain show up when it’s cited — is reported separately as average citations per response (defined above).

Worked example (domain level)

Domain: techcrunch.com
Time period: Last 7 days

Response 1: Cited 2 URLs from techcrunch.com
Response 2: Cited 1 URL from techcrunch.com
Response 3-100: No citations from techcrunch.com

Responses citing techcrunch.com = 2
Total responses analyzed = 100

Used = (2 / 100) x 100 = 2%

techcrunch.com appeared as a source in 2% of AI responses for this project. Across those 2 responses, it averaged 1.5 unique URLs cited per response (reported separately as avg citations).

Worked example (URL level)

URL: techcrunch.com/article-1
Time period: Last 7 days

Response 1: Cited this URL
Response 2: Cited this URL
Responses 3-100: Did not cite this URL

Used = (2 / 100) x 100 = 2%

This specific article was cited in 2% of responses, regardless of how many times it was cited within each one.

The “used” metric is your share-of-voice equivalent for sources: it tells you how often AI reaches for this source when answering questions in your space.

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Source categories

Topify.ai classifies cited domains into categories to help you understand the source landscape:

Category	Examples	Description
Corporate	apple.com, tesla.com	Official brand and company websites
Editorial	nytimes.com, techcrunch.com	News outlets and journalism
Institutional	.gov, .edu, who.int	Government, academic, and institutional sites
Reference	wikipedia.org, stackoverflow.com	Knowledge bases and reference platforms
UGC	reddit.com, youtube.com, medium.com	User-generated content platforms
Other	Edge cases, parked domains	Everything that doesn’t fit the above

These categories help you understand whether AI providers are citing authoritative sources, user-generated content, or your competitors’ sites when answering prompts related to your brand.

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Using sources data to improve your strategy

Sources data helps you answer questions like:

• Which of your pages are already being cited? Look for your domain in the top domains list. High citation counts mean AI providers trust your content.
• Where are the gaps? If competitor domains are cited frequently but yours isn’t, you need content that covers those topics.
• What content types perform best? Compare citation rates across source categories to understand what AI providers prefer to cite.
• Which pages should you optimize? URLs with high “used” counts are already influencing AI responses — improving them could increase your visibility further.

FAQ

How do I get my own pages cited more often?

Look at the domains AI currently cites most for your prompts and study what they have in common: structured headings that match the question, statistics and named numbers, citations to authoritative sources, and a confident tone. Then write content that does those things better. The AI agent’s geo_optimize skill applies these techniques to existing pages automatically — see Using the AI agent.

My domain isn’t in the source list — why?

Either AI providers haven’t picked up your pages yet, or they have but cite other sources first when answering your tracked prompts. Both are content problems, not data problems: you can fix them by publishing pages targeted at the prompts where your domain is missing, or by improving the pages you already have so they’re more citable.