Premium Intelligence Audits for SEO agencies

Diagnose how AI systems, the web, and your pages shape brand visibility

VectorGap connects the audit families agencies need after AI search enters the client conversation: Perception, Preference, Unbranded Discovery, GEO Audit, Query Explorer, Remediation Center, Mission Control, and reports. You see the answer gap, trace the evidence, ship the fix, retest the same target, and show progress.

Preference verdict

67

Open the exact prompts and evidence
Competitor verdict
Source gaps
Mission queue

The audit loop

Four audit families, one remediation loop

The product promise is blunt: show which brand AI prefers, how each model frames the client, what public evidence supports or weakens the answer, which technical gaps block citation, and which mission should ship next.

Perception

Understand how each provider describes the client for targeted prompts, including sentiment, accuracy, coverage, credibility, hallucinations, recommendation rate, and correctness.

  • 98-prompt perception audit
  • Provider-level answers
  • Market, language, persona, and industry targets
  • Hallucination and correctness signals

Preference

Put the client and competitors in the same buying prompt and see which brand AI chooses across price-value, feature capability, innovation, ease of use, trust, market fit, support, and recommendation.

  • 40 high-context preference prompts
  • Wins, losses, and provider variance
  • Competitor decision drivers
  • Mission-ready preference gaps

Web + GEO evidence

Use Unbranded Discovery and GEO Audit to inspect the public sources, review signals, third-party context, extractability, schema, entity health, and content structure behind the answer.

  • Public evidence layer
  • Extractability and source gaps
  • Entity and citation readiness
  • Remediation priorities

Audit, prioritize, fix, retest, report

1

Load brand truth

2

Audit perception and preference

3

Inspect prompts, answers, and sources

4

Create missions and ship fixes

5

Retest and report movement

Buyer decision layer

What AI can extract from the audit loop

The public page needs to explain how audit families become agency delivery. These rows turn the diagnostic stack into buyer questions, extractable evidence, and the next action an agency can sell.

Buyer question
What AI can extract
Agency action
Which audit family should an agency run first?
AI can extract whether the client is losing because models do not mention them, prefer competitors, distrust source evidence, or cannot parse the site.
Start with the baseline audit, choose the weakest family as the first fix lane, and keep the same target context for the next retest.
What turns audit evidence into client work?
The useful output is not a score by itself; it is prompt evidence, competitor context, source gaps, extractability blockers, and the exact remediation mission that should ship next.
Convert the strongest gap into Mission Control work, document what shipped, and show the client the before-state, fix, and same-target retest evidence.
How does an agency report progress without overclaiming?
AI can compare whether the same provider, market, language, persona, prompt set, and competitor frame moved after remediation.
Package prompt excerpts, source evidence, shipped actions, retest movement, and remaining risks into a client-ready report.

Product evidence

Exact answers beat noisy metric walls

Each audit keeps the evidence trail close: prompt, provider, answer, score, citation/source context, competitor implication, missing proof, recommended mission, and retest path.

Latest evidence drawerTraceable evidence references
Preference decision drivers
Perception answers
Unbranded and GEO evidence
Mission Control action path

Built for agency proof, not static scoreboards

Every audit is built to be repeated and explained: targeted context, direct prompt and evidence links, provider-level answers, competitor comparisons, source gaps, prioritized missions, trend history, and client-ready reporting without unsupported performance claims.

FAQ

Intelligence audit questions

Are these audits separate products?

They are separate diagnostic lenses inside one operating loop. Perception, Preference, Unbranded Discovery, GEO Audit, Query Explorer, Mission Control, retests, and reports work together to explain the gap and the fix path.

What should an agency show after the first audit?

Show the client where AI answers fail, why competitors win, which source or extractability gaps matter, which remediation mission ships first, and what the same-target retest will measure.

Why does target context matter?

A report is only useful when market, language, persona, provider set, competitor frame, and prompt intent stay explicit. Otherwise the agency cannot prove that remediation changed the same buying context.