Guides

AI Visibility Score

One score that captures how visible your brand is across the major AI engines — so you can act on a single number, not a dashboard you can't read.

What is this?

The Findable AI Visibility Score is a composite metric calculated from real-prompt runs across ChatGPT, Perplexity, Gemini and Claude. It combines mention frequency, citation strength and recommendation quality into a single 0–100 number.

Why this matters for AI search

Buyers don't see a dashboard. They see one answer. A single composite score is the only way to know whether that answer includes you.

The insight

"One score matters because buyers see one answer."

How it works

From question to citation, in four steps.

  1. 1
    Run
    Findable runs hundreds of representative prompts.
  2. 2
    Detect
    Presence, Coverage and Sentiment signals are extracted.
  3. 3
    Weight
    Signals are weighted 60 / 25 / 15.
  4. 4
    Score
    A composite 0–100 score is produced per engine and overall.

Core concepts

Presence
Whether your brand appears in the AI's answer at all (weight 60%).
Coverage
The share of tested prompts where you show up (weight 25%).
Sentiment
How positively you're framed when you do appear (weight 15%).
Per-engine score
Same formula, computed separately for each AI engine.
Benchmarks
Industry median and competitor scores for context.
Trend
How the score moves over time as you act.
findable.app / ai visibility score
Composite
64Score
Presence (60%)71%
Coverage (25%)58%
Sentiment (15%)49%

How the score is calculated

We measure Presence, Coverage and Sentiment across a fixed prompt set per brand. Each signal is normalized 0–100 and weighted 60/25/15 respectively. The result is a composite that rewards brands who show up consistently and are described positively — the two factors that most directly shape whether AI engines recommend you.

findable.app / score over time
64 +9
vs last 30 days
Driven by +18 new citations across 7 sources.
findable.app / benchmarks
Your brand64
Competitor A58
Competitor B49
Industry median41

How to interpret the score

0–30 means buyers don't see you in AI answers. 30–55 means you appear but rarely lead. 55–75 is competitive — you are part of the answer but not the answer. 75+ means you are consistently the recommended brand on your buyer questions. Move from one tier to the next by closing the lowest-weighted gap first.

Common misconceptions

Higher always means better
Not in isolation. A 60 in a saturated category can be stronger than a 75 in a niche one. Benchmark vs your competitors.
The score is the same as Google rank
It isn't. AI visibility and Google rank correlate weakly. You can rank #1 and still score low.
One run is enough
AI engines are non-deterministic. Findable averages across runs to produce a stable score.
A small drop means something broke
Some noise is expected. Drops of less than 5 points in 30 days are usually within normal variance.

Best practices

  • Track score per engine, not just overall — different engines tell different stories.
  • Pair the score with competitor and industry benchmarks before reacting.
  • Investigate large drops by inspecting the underlying prompt-level data.
  • Use the 60/25/15 weights to prioritize where to invest next.
  • Re-run at a consistent cadence so trend data stays comparable.
  • Treat the score as a directional metric, not an absolute one.

Industry examples

Illustrative public examples — not customer data.

Composite scoring in finance

Credit scores combine many weak signals into one comparable number — the AI Visibility Score follows the same pattern for AI search.

Net Promoter Score

NPS distils thousands of survey answers into a single number to enable benchmarking across teams and time.

Domain authority indices

SEO platforms publish authority scores aggregating link, content, and entity signals into one comparable metric.

How AI systems contribute to a visibility score

Each AI engine produces signals that roll up into the score:

  • Mention frequency
    How often the brand appears in answers for relevant prompts.
  • Citation frequency
    How often the brand's domains are explicitly cited as sources.
  • Recommendation share
    How often the brand is selected when buyers ask for the best option.
  • Entity confidence
    How strongly engines associate the brand with the right category.
  • Competitive coverage
    Where the brand stands versus the competitor set across the prompt universe.

Related concepts

Explore the concepts, metrics, and signals that influence AI visibility.

How organizations apply this

Anonymized examples from teams working across industries.

Compare approaches

How Findable compares to other AI-search and SEO tools.

Explore leading brands

Browse representative Top Brands pages showing how AI engines rank category leaders.

Underlying research

What this guide is built on.

36,798
AI answers analyzed
75,295
Brand sentiment observations
175,599
Source citations analyzed

Frequently asked questions

See how visible your brand is in AI search

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