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Metrics & definitions

A SIGNAL metric is a defined measurement, not a decorative score.

This public glossary standardizes how SIGNAL describes AI demand, answer presence, recommendation, citations, machine access, referrals, business outcomes and independent verification. Every value must be interpreted inside a defined platform, market, language, time, prompt/intent and competitor scope.

Why a public metric standard matters

AI visibility becomes meaningless if every vendor defines it differently. SIGNAL publishes definitions so brands, agencies and auditors can compare results consistently and see where direct observation ends and modeling begins.

AI Visibility

Definition: scoped measure of how consistently an entity appears across relevant AI answer opportunities.

Answers: “Does the brand show up where it should?” It is not equivalent to website traffic, search ranking or ad impressions.

AI Share of Voice (ASOV)

Definition: relative AI visibility of an entity versus a defined competitor set. Always publish the competitor set and measurement universe.

Mention Rate

Share of relevant measured answers where the entity is named. A mention can be positive, negative or neutral and does not automatically imply recommendation.

Recommendation Rate

Share of relevant measured answers where the entity is recommended or selected as an appropriate option according to the methodology. A recommendation is stronger than a mention.

Answer Position

Relative prominence or order of an entity within a ranked, comparative or recommendation answer.

Citation Rate

Frequency with which a defined source, domain or entity is cited in measured answers.

Citation Coverage

Share of relevant answer opportunities where eligible sources appear as citations.

Source Influence

A measure or model describing the relationship between information sources and AI answers. Source influence may be modeled; direct citation is not automatically causal influence.

Topic, intent and narrative coverage

Topic Coverage

Share of strategic topics where the entity appears with sufficient relevance.

Intent Coverage

Share of defined intent families — such as learn, compare, buy, switch, troubleshoot, local recommendation or trust/reputation — where the entity appears.

Narrative Frequency

How often a recurring claim or description appears across measured answers.

AI Sentiment / Characterization

How the entity is described along defined dimensions. Prefer dimension scores or classifications over a single simplistic sentiment number.

Estimated AI Demand

Estimated quantity or relative level of demand for a prompt/intent family. It must be labeled estimated unless provided directly by an authorized AI platform.

Prompt Trend

Change in demand or observed frequency for a prompt/intent family over time.

AI Crawler Requests

First-party observed server requests classified as originating from known or likely AI crawlers/agents.

Content Retrievals

Successful machine requests that retrieve a defined page, file, content object or endpoint.

AI Agents Detected

Distinct identified AI crawler/agent identities observed within scope. Identity methodology is documented in Methodology.

AI Referral Sessions

Human sessions attributed to a known AI referral source using first-party or authorized evidence.

AI Referral Conversion Rate

Conversions associated with measured AI referral sessions divided by those sessions under the defined attribution rule.

AI Referral Revenue

Revenue attributed to AI referral sessions under the selected attribution model.

Crawler-to-Referral Ratio

A descriptive comparison of machine access volume to AI-driven human referral volume. It does not prove that crawling caused referrals.

Claimed Uplift

Improvement claimed by a vendor, agency, platform or client before independent verification.

Measured Uplift

Change measured by SIGNAL under a named methodology.

Incremental Lift

Estimated causal effect relative to an appropriate counterfactual or control. Use only when methodology supports a causal conclusion.

Claim Support Status

Verify classifications: Supported, Partially supported, Unsupported, Inconclusive or Not measurable.

Evidence Completeness

Extent to which required data and evidence are present for an audit.

Policy Match

Whether observed crawler/agent access behavior matches the intended access policy.

AI Media Efficiency and candidate indices

AI Media Efficiency is a working concept comparing AI-related media spend to defined business outcomes. Its exact public formula must be approved before use as a standardized index.

Candidate product indices such as AVI, ASOV, ARR, CAS, AAS, AME and IAR should be promoted as standardized indices only after formulas are validated and versioned.

Every metric card needs a scope label.

AI Share of Voice: 31%
Universe: 1,200 sampled answer opportunities
Platforms: selected supported AI systems
Markets: US, UK
Language: English
Competitors: Brand A, B, C, D
Period: Aug 1–31, 2026
Methodology: v1.3
Evidence: controlled external measurement

The values above are an illustrative scope example, not a market benchmark or customer result.

Public measurement standard

Use the definition before using the number.

Pair every SIGNAL result with the relevant scope, evidence class and methodology.