Methodology

The math behind the score.

The AI Visibility Score is a composite 0 to 100 metric. Four signals, weighted, normalized across every engine you track. Here is exactly what goes in and what does not.

Signals4
Engines9 normalized
RefreshDaily
The four signals

What goes into the score.

Each signal answers a different question a CMO would ask. The composite blends them so a single number captures presence, prominence, and authority.

Signal 0135%

Mention rate

How often your brand is named in AI responses to the queries you track. Computed per engine, then averaged. The baseline question: are you even in the answer.

RANGE · 0 – 100% per engine
Signal 0230%

Share of voice

Of the answers that mention any brand in your category, how often is yours the lead, also-mentioned, or absent. Lead beats also-mentioned. Also-mentioned beats absent.

RANGE · 0 – 100% per cohort
Signal 0320%

Average position

When you are cited, where do you appear in the answer. First-listed brands carry more weight in buyer recall than mid-list ones. Position scores normalize across answer length.

RANGE · Ordinal 1 – n
Signal 0415%

Citation share

Of the cited answers in your category, what fraction include a citation to your domain. Citation share separates being talked about from being authoritative.

RANGE · 0 – 100% per query
Worked example

A score, line by line.

Composite signals roll up to a single number. Here is what that looks like for one engine, one week, mid-market SaaS observability category.

Inputs · ChatGPT · Week 12

SignalValueWeight
Mention rate54%35%
Share of voice41%30%
Avg position3 of 520%
Citation share22%15%

Roll-up · weighted composite

StepValue
0.35 × 5418.9
0.30 × 4112.3
0.20 × (position-normalized 60)12.0
0.15 × 223.3
ChatGPT score, week 1246.5
Across every engine

One score, nine surfaces.

Each engine produces its own composite. The unified AI Visibility Score blends them, weighted by the share of category traffic each engine carries for your geography.

ChatGPT
Reweighted by category share · GPT-5
Gemini
Reweighted by category share · 2.5 Pro
Perplexity
Reweighted by category share · Sonar
Claude
Reweighted by category share · 4.7 Sonnet
Copilot
Reweighted by category share · GPT-5
Grok
Reweighted by category share · Grok-4
AI Overviews
Google AI Overviews surface
AI Mode
Google AI Mode surface
DeepSeek
Reweighted by category share · v3.2
What the score does not measure

Honest about the edges.

A composite score is useful because it simplifies. It is also useful to be clear about what it leaves out, so the number you report is the one you can defend.

Not in scope

Sentiment of the mention. The score measures presence and prominence, not whether the model framed you positively. Sentiment is reported separately, not folded in.

Not in scope

Click-through or downstream conversion. The score measures what the answer says about you, not what the buyer does next. Pipeline attribution lives in your CRM, not in Zumi.

Not in scope

Paid placement or sponsored mentions. Where an engine surfaces paid units alongside organic answers, only the organic answer is scored.

Caveat

Model updates change behavior. When an engine ships a new model version, the score can shift even with no change in your content. Zumi flags these events inline on the trend chart.

The window is now

Your competitors are already paying attention.

Zumi shows you exactly where your brand stands in AI-generated answers, across every engine, against every competitor. Book a 30-minute working session and we'll show you live data for your brand. No deck. No pitch.