Feature / Agency GEO operations
Check whether client content is structured so AI systems can read, cite, and reuse it. The module is built for agency delivery: connect prompt results to buyer persona, target market, and prompting language so the client sees what AI says in the markets that actually matter.
Operational role
Audit prompts by buyer persona instead of treating every AI answer as one generic user intent.
Segment visibility by target market and language so agencies can explain local AI-market reality.
Connect the score to source, competitor, and extractability gaps that the client can act on.
Package findings into a repeatable baseline-to-remediation workflow for SEO and GEO retainers.
New agency advantage
This is the feature agencies should lead with. A generic AI visibility score is too blunt for local client work. VectorGap lets the agency explain how AI perception changes by buyer persona, target market, and prompting language, which turns the audit into a local market intelligence product instead of a flat dashboard.
Test how executives, buyers, teams, journalists, analysts, and local prospects ask the same market question differently.
Separate Belgium, France, UK, US, or city-level AI perception instead of averaging every client into one global answer.
Compare English, French, Dutch, German, Spanish, and other prompt languages to catch visibility gaps hidden by English-only audits.
Help clients understand not just if they are visible, but how AI describes them to each local buyer segment.
Workflow
Each feature page now uses the same product story: diagnose the AI-market signal, explain the local gap, prioritize the fix, and give the client proof they can understand.
Pick the persona, geography, language, and prompt family that match how the client actually sells. A Belgian agency client, a French buyer, and an English-language analyst prompt should not be averaged into one vague score.
Measure the client against competitors, source evidence, sentiment, factual accuracy, and recommendation behavior across the selected market context.
Separate missing public truth, weak citation sources, poor content structure, and competitor narrative pressure so the agency can prescribe the next concrete work package.
Use follow-up audits to show whether the client improved in the same persona, market, and language context that originally exposed the gap.
Context layer
Persona + market + language
Agency output
Local AI market story
Client proof
Repeatable audit history
Agency outcomes
The client sees where AI perception changes by country, city, audience, or language instead of arguing over one generic visibility number.
The agency can sell market-specific GEO work: local proof pages, localized source building, persona-specific content, and multilingual prompt coverage.
Repeat audits create a before-and-after story around the exact market context the client cares about.
The fastest buying path is clear product value: show the local AI-market gap, inspect the prompts and competitors behind it, and use the feature set as the remediation workflow.
