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Per-query recommendation probability

RecommendationProbability

Estimate the probability an AI assistant will recommend your brand for a target query shape. Why this matters →

Recommendation probability
C

59%

Likely to appear as a supporting option

Query ↔ positioning fit

+7

1 matching concept(s) between query and positioning

Organization schema

+12

Machine-readable brand identity on every page

Third-party reviews

+10

G2, Trustpilot or Capterra - assistants pull from these

Press / analyst coverage

+14

External trust transfer from tier-1 sources

Quantified proof point

+10

Assistants lift concrete numbers into 'best X' answers

Competitor density

-12

4 strong competitor(s) for this query shape

"Best X" query shape

+8

Ranked-list queries lift brands with proof points

How it works

Enter the brand, the query you want to be recommended for, and seven supporting facts. The tool computes a recommendation probability by combining query ↔ positioning fit, schema, reviews, press, quantified proof and competitive density. Every input maps to a visible delta so you can see which lever matters.

Why probability, not ranking

  • AI assistants don't rank the way Google does. They probabilistically pick N candidates from a citation graph per query - so your job is to clear the threshold.
  • Crossing the threshold from "passing mention" to "supporting option" is worth 5-10x the click equivalent of a blue-link rank jump.
  • The biggest lever is almost always the proof point - a specific number beats five adjectives.

Improve it

Pair with the Recommendation Simulator and the Brand Authority Builder to plan the fixes. Read how AI assistants choose citations for the underlying model.

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