The Six Signals ClickRadius Scores
A single number — a 0-to-100 AI Readiness Score — is a convenient thing to put at the top of a report, but it is only useful if you understand what feeds it. ClickRadius does not treat AI-citation readiness as one undifferentiated quality. It decomposes it into six categories, each measuring a distinct thing an answer engine cares about when it decides whether to name, quote, or cite a business. Three of those categories live on your own website; two live out on the wider web where you have less direct control; and the sixth measures what is actually happening in AI answers right now. This article walks through all six at a conceptual level — what each one represents, why it belongs in the model, and how they combine into a picture of whether the machines that increasingly answer your customers' questions are ready to cite you.
Why a score, and why six categories
The reason to score readiness at all is that "are we visible in AI search?" is not a yes-or-no question. Visibility in a generative engine is the cumulative result of many independent factors, and a business can be excellent at some and absent from others. A law firm might publish beautifully evidenced articles and still be invisible because its entity is inconsistent across directories. An e-commerce brand might have flawless product schema and no original statistics anywhere on the site. A single grade hides those imbalances; six category grades expose them, which is the point — you cannot fix what a number won't show you.
The six categories are chosen so that each maps to a different mechanism of citation. Answer engines assemble responses by retrieving candidate sources, judging which contain trustworthy, quotable material, attributing claims to entities they recognize, and preferring sources they have seen corroborated elsewhere. The categories mirror that pipeline. Grouped, they fall into three tiers: the on-site foundation, the off-site majority, and the live measurement that tells you whether the first two are working.
An answer engine is, functionally, a journalist on deadline: it cites the sources that hand it verifiable material and that it already trusts. A readiness score has to measure both halves of that sentence.
— ClickRadius Institute, research summary
The on-site foundation: three signals you fully control
The first three categories cover everything on your own domain. They are where a business has the most direct control and where the fastest improvements usually come from. They do not, on their own, guarantee citation — more on that below — but they are the prerequisite. A page that gives an engine nothing citable and nothing machine-readable will not be cited no matter how strong the entity behind it.
Signal 1 — On-page evidence: the Princeton triad
The first category measures whether your content contains the kinds of evidence generative engines preferentially cite: statistics, attributed quotations, and source citations. This is not a stylistic preference; it is the most research-grounded signal in the entire model. According to Princeton's "GEO: Generative Engine Optimization" study (KDD 2024) — the foundational academic work on generative-engine citation — adding those three elements raised source visibility in generative engines by up to 40% in the study's benchmarks. Each of the three gives the model something it cannot safely generate on its own: a number it can quote, a named human it can attribute, a reference it can stand behind. ClickRadius weights this triad because the evidence for it is unusually strong, and it looks for the signals where they matter most — on the cornerstone pages that answer real customer questions, not buried in a blog archive.
Signal 2 — Structured data and schema
The second category measures machine-readability: whether your pages carry the structured data that lets an engine parse what they are without guessing. Article, FAQPage, Organization, and related schema types translate a human page into explicit statements — this is the author, this is the publish date, this is the organization, these are the questions and answers. Answer engines can read unstructured HTML, but schema removes ambiguity, and ambiguity is friction. This category checks that the right schema types are present, valid, and honestly matched to the visible content. Schema is one of the few places in the whole model where a fix is nearly binary: either the markup is there and correct, or it isn't.
Signal 3 — Content structure and answerability
The third category measures how easily an engine can extract a clean answer from your page. A generative engine lifts self-contained passages: a question-form heading followed by a direct, complete answer; a comparison presented as a table; a definition stated plainly in the first sentence rather than buried three paragraphs down. This category rewards structure that makes extraction effortless — clear headings, short answer-first paragraphs, lists and tables where they fit — and penalizes the opposite: walls of undifferentiated prose where the answer is present but not liftable. Where the first category asks "is there citable evidence here?", this one asks "can the machine actually get it out cleanly?"
The off-site majority: two signals earned across the web
Here is the honest part that a lot of AI-visibility marketing skips. A perfect on-site score does not win the citation on its own. According to industry data, the majority of what drives AI citations is off-site — it lives in whether models recognize your organization as a consistent, authoritative entity across the wider web. The on-site foundation makes a page citable; the off-site categories are what make an engine trust and choose you over an equally well-formatted competitor. This is why two of the six categories deliberately sit off your own domain.
Signal 4 — Entity authority and consistency
The fourth category measures whether you exist, to the machines, as one coherent, recognized entity. Answer engines attribute claims to entities they trust, and trust starts with basic recognition: is your business name, address, phone, and identity consistent everywhere it appears? Are the people who author your content recognizable entities in their own right? Is there a clean, corroborated knowledge-graph-style picture of who you are and what you are authoritative about? Inconsistency — three slightly different business names, a phone number that varies by directory, an author with no verifiable identity — fragments the entity and dilutes authority. This category scores that coherence, because an engine that cannot confidently resolve who you are will not confidently cite you.
Signal 5 — Off-site footprint and multi-platform presence
The fifth category measures the breadth and quality of your presence beyond your own site: authoritative directory profiles, third-party coverage, reviews, databases, and the external signals that corroborate your expertise. Where category four asks whether your entity is consistent, category five asks whether it is present and corroborated across the places engines look. A business that appears only on its own website is a single unverified source; a business whose claims are echoed and confirmed across many trusted platforms is one the engine can rely on. This is the category most businesses score lowest on and the one that, per industry data, carries the largest share of the citation outcome.
The live measurement: are the first five working?
Signal 6 — Live AI visibility across five engines
The sixth category is different in kind from the other five. Rather than measuring an input — something on or off your site — it measures the output: whether you are actually being mentioned or cited in AI answers right now. ClickRadius monitors visibility across five live AI engines — ChatGPT, Gemini, Perplexity, Claude, and Grok (with Copilot in development) — asking the questions your customers ask and recording whether, and how, you appear. This is the reality check on the whole model. You can improve every input category and still need to confirm the engines noticed. And the baseline this category establishes is sobering: industry estimates suggest a large majority of brands currently have zero AI-search mentions, which means for most businesses this category starts near the floor — and every point of improvement is territory that was genuinely unclaimed.
You do not get to declare victory on inputs. The only honest measure of AI visibility is whether the engines are citing you when a real customer asks a real question — measured, repeatedly, across every engine that matters.
— Douglas Brown, founder, ClickRadius
How the six combine
The categories are not independent silos; they reinforce one another, which is why the model treats them as one score rather than six unrelated grades. Strong on-page evidence (category one) is wasted if the entity is too fragmented for an engine to attribute it to anyone (category four). A pristine entity (category four) with corroboration everywhere (category five) still needs a page that answers the question cleanly (category three) before it can be cited for a specific query. Schema (category two) accelerates everything by removing parsing friction. And category six tells you whether the combination is landing. The practical reading of a ClickRadius report is therefore not just the headline number but the shape of the six — where the peaks and troughs are, because the trough is usually where the next real gain hides.
A useful way to hold the model in mind is as a sequence of questions an answer engine effectively asks about your business:
- Is there anything citable here? — evidence signals.
- Can I read this page unambiguously? — structured data.
- Can I extract a clean answer? — content structure.
- Do I know who this is? — entity authority and consistency.
- Is this entity corroborated elsewhere? — off-site footprint.
- Am I actually citing them yet? — live AI visibility.
Answer all six affirmatively and you are, in the terms that matter in 2026, ready to be cited. Score them honestly and you know exactly which of the six is holding you back.
What the score is not
Two honest caveats keep the number useful. First, ClickRadius does not publish exact internal weightings, and no responsible reader should treat the composite as a precise physical constant — it is a considered, research-informed model of a moving target, not a law of nature. The engines change; the model is maintained against them. Second, a high score is a strong readiness indicator, not a citation guarantee. There are no guarantees in generative-engine visibility, and any tool that promises one should be distrusted. What the six-signal score does is tell you, concretely and category by category, where you stand and what to fix next — which is exactly what the guesswork-driven alternative cannot.
Frequently asked questions
What are the six signals ClickRadius scores?
ClickRadius groups AI-citation readiness into six categories: on-page evidence signals (the Princeton triad of statistics, quotations, and source citations), structured data and schema, content structure and answerability, entity authority and consistency, off-site footprint across directories and platforms, and live AI visibility measured across five engines. The first three are the on-site foundation; the next two are the off-site majority; the sixth closes the loop by measuring what is actually happening in AI answers today.
Why does the score weight quotations, statistics, and citations?
Because those three signals are the ones with the strongest research support. Princeton's GEO: Generative Engine Optimization study (KDD 2024) found that adding quotations, statistics, and source citations raised generative-engine visibility by up to 40% in its benchmarks. Answer engines cite material they can quote and stand behind, and those three signals give the model exactly that kind of verifiable, attributable evidence, so ClickRadius weights them in the on-page evidence category.
Is a high on-site score enough to get cited by AI?
No. On-site work is necessary but not sufficient. Industry data indicates the majority of what drives AI citations is off-site: whether models recognize your organization as a consistent, authoritative entity across directories, databases, reviews, and third-party coverage. A strong on-site foundation makes a page citable, but entity authority earned across the wider web is what makes an engine trust and name you. That is why ClickRadius scores both, and why several of the six categories sit off your own domain.
Curious where your six land? Get your free AI Readiness Score — a 6-category, 0-to-100 audit of your citability — or see ClickRadius plans for automated fixes and citation monitoring across five live AI engines.