How scoring works

What the AI-visibility score actually measures

Cite Me reads your public pages and rates how easily an AI answer engine — ChatGPT, Perplexity, Google AI Overviews — could quote them. It runs entirely on-page; no orders or customer data are touched.

PREDICTED (heuristic) Every score is a prediction from these eight signals — not a measured citation count and not a ranking.

The eight signals (and how much each counts)

The bar shows the share of the overall predicted score each signal carries.

Citable passages

0.20

Self-contained answers about 130–170 words long — the kind of complete chunk an AI can quote whole.

Improve it: Write one complete answer paragraph per question heading.

Front-loaded answer

0.15

Whether the answer or definition appears in the first ~120 words, not buried at the bottom.

Improve it: Lead with the answer in the first one or two sentences.

Structured data

0.13

AEO-useful JSON-LD on the page (Product, Article, FAQPage, HowTo, BreadcrumbList).

Improve it: Add the right schema for the page type. (Ratings/reviews only when real on-page reviews exist.)

Question headings

0.12

How many headings are phrased as the real questions customers ask.

Improve it: “How long does it last?” works better than “Durability.”

Evidence density

0.12

Concrete numbers, units and figures that make claims quotable rather than vague.

Improve it: Replace “long-lasting” with specifics — hours, ml, %, named attributes.

Freshness

0.10

A visible or structured “last updated” date.

Improve it: Show an Updated date and set dateModified in JSON-LD.

Entity sameAs

0.10

Organization sameAs links so AI can confidently identify your brand.

Improve it: Add Organization/Brand JSON-LD with sameAs links to your official profiles.

AI crawler access

0.08

Whether AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended…) are allowed to read your store.

Improve it: Allow them in robots.txt and per-bot directives.

How the overall score is built

Each signal is scored 0–100 on a page, then combined with the weights above into one 0–100 page score. The dashboard shows your store average, the eight signals, and a prioritized list of fixes — ordered by predicted impact (a signal’s weight × how far below target it is), so the biggest wins come first.

What this score is — and isn’t

  • It is a heuristic prediction of how quotable your pages are to AI answer engines, based on what those engines tend to reward.
  • It is not a measured citation count, a search ranking, a “rich result”, or a guarantee that any AI will cite you. Acting on the fixes is expected to help; outcomes in real AI answers are never guaranteed.
  • llms.txt is treated as hygiene only — its presence does not boost the score.