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Capability 02

Fetched from the engines.
Nothing estimated.

Most tools tell you what your content looks like. Prism goes out to the answer surfaces on every scan and brings back what is actually happening there — AI Overviews, People Also Ask, rankings, query variants, long-tail intents and verified demand.

New pages per monthTrailing 12 mo
Competitor A You
0255075100 Sep '25OctNovDecJan '26FebMarAprMayJunJulAug
Illustrative sample — dated URLs only, fetched live.
01The principle

An estimate is a guess wearing a number.

Plenty of platforms will show you a confident figure for how visible you are. Ask where it came from and the answer is often a model, a sample, or a number bought from someone else and rounded. Prism fetches live, every scan, and labels anything that is not directly measured.

If we did not go and look, we do not claim it.
  • Fetched per scan. Not cached from last quarter and not carried between clients. Each scan is a fresh look at the surfaces as they stand that day.
  • Keyword-level demand. Verified volume per term rather than an inflated grouped total, so the numbers behind a recommendation hold up when someone checks them.
  • Labeled when derived. Anything the platform calculates rather than observes is marked as modeled, everywhere it appears.
Answer surfaces · this scanLive
AI Overviews triggered
PAA boxes held
Keywords in top 10
Illustrative sample — refreshed on every scan.
02What gets fetched

Optimize content with live data.

Each one is pulled fresh and scored into the Prism Score — and competitor scores and publishing velocity are fetched live alongside them.

01

AI Overviews

Which of your keywords trigger an AI Overview, who is quoted inside it, and whether that citation is yours or a competitor’s.

02

People Also Ask

Question-level ownership — the PAA boxes your pages hold today and the open questions still available to claim.

03

SERP rankings

Where each page actually sits, refreshed per scan, so movement in the score can be read against movement in the results.

04

Fan-out queries

An engine expands one question into many. Prism fetches those variants and maps the ones your page has to answer to stay in the result.

05

Edge cases

The unusual phrasings and long-tail intents where answers swing — fetched rather than guessed at, so wins there are deliberate.

06

Verified search demand

Keyword-level volume behind every recommendation, never an inflated grouped total.

Dimension scores & insights10 dimensions
Core IntentContent Quality22
Edge CasesContent QualityFetch live data14
Implied QuestionsContent QualityFetch live data9
Fan-out QueriesContent QualityFetch live data41
RetrievableAI Accessibility26
ExtractableAI Accessibility12
CitableAI AccessibilityFetch live data71
ReusableAI Accessibility9
AIO ReadinessSearch Visibility16
PAA CoverageSearch VisibilityFetch live data7
AI Rewrite — 10 dimensions

Rewrites the checked dimensions using the fetched research, then simulates the score.

Illustrative sample — live fetch shown on the dimensions that carry it.
03Why it matters

Optimizing web content against stale data is worse than not optimizing.

What changed since last scanSample
Pages improved54
Pages declined51
Unchanged94
Illustrative sample — movement separated from noise.

Answer surfaces move week to week. A recommendation built on a three-month-old export can send a writer to rework a page that is already winning, or leave one that quietly lost its citation.

  • Scheduled scans. Re-scan on your cadence and get a what-changed report after every run.
  • Real movement, isolated. Because scoring is deterministic, a change in the number means something changed in the world — not in the measurement.
  • Change you can attribute. See which pages moved, in which direction, and on which dimension.
04Common questions

Questions people ask.

Where does the data come from?

It is fetched directly from the answer surfaces on each scan — AI Overviews, People Also Ask, search results and the query variants those surfaces expose — alongside verified keyword-level demand.

How often is it refreshed?

On every scan. You set the cadence, and each run produces a what-changed report against the previous one.

Is any of it estimated?

Anything the platform derives rather than observes is labeled as modeled wherever it appears. The distinction is visible in the app and carried through into the audit report.

Why keyword-level demand instead of grouped totals?

Grouped totals inflate the apparent opportunity. Keyword-level volume is smaller, less flattering and defensible when someone checks it.

See your Prism Score.

A live walkthrough on your own site — your pages, your citations, your gaps across every AI surface.

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