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Per-query citation prediction

CitationPrediction Tool

Predict which of your pages will be cited for which query shapes using a 7-factor weighted model. Why this matters →

Citation probability

55-75%

B

weighted score 80

Query relevance

w25

Keyword overlap between page summary and target query.

Entity alignment

w20

Is the brand a strong entity in this topic cluster?

Domain authority

w15

External references, press, analyst mentions.

Schema markup

w12

Article + FAQ schema directly raises extraction rate.

Freshness

w10

Last-modified date within 12 months.

External sources in content

w10

Sourced content gets preferred over unsourced.

Answer-shaped content

w8

Does the target query match a content pattern on the page?

How it works

Enter the URL and a one-line summary of your page, plus the query shape you want to be cited for. The tool scores seven weighted factors - query relevance, entity alignment, domain authority, schema markup, freshness, external sources and answer-shape - and returns a composite citation probability.

Why pair prediction with the rewrite loop

  • The big unlock is running this against 10-20 query variants per page to find the angle where the page is already strong.
  • If relevance is high but schema and sources are missing, that's a 60-second fix for a 20-point score lift.
  • If relevance is low, the page probably needs to be rewritten around the target query or the query belongs on a different page entirely.

Then

Ship the fixes the prediction surfaces. Use the Citation Probability Calculator for sentence-level scoring, and the Article schema generator if schema is the gap. Read how AI assistants choose citations for the full model.

Want this done for you?

Ship the full GEO playbook in 14 days

Geolify GEO packages bundle every tool on this site into a 14-day done-for-you build - llms.txt, schema, entity strength, content overhaul, citations and the measurement stack. From $499.

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