Market-specific
Generate prompts that mention the country, city or region, local buyer, and local language instead of generic global SEO wording.
Create a market-specific prompt pack to test how ChatGPT, Claude, Gemini, Perplexity, Grok, Mistral, and DeepSeek describe a brand by country, language, city, buyer persona, and competitor context.
Interactive generator
Configure the brand, market, buyer, and competitors. The prompt pack expands below with no hidden scroll area, so the output is readable enough to use in a client call.
Required fields first, local context second.
Brand
Market and audience
15 prompts across 5 localized AI visibility categories.
Prompt coverage score
48
15 prompts
Market context
Manual testing
Checks whether model answers carry the right brand, category, audience, and local relevance signals.
Tests whether the brand appears when buyers ask for local or market-specific options.
Shows whether AI can position the brand against named alternatives without hallucinating.
Surfaces how pricing, value, alternatives, and buying objections appear in AI answers.
Forces the assistant to reveal whether it has stable sources or only vague source recall.
Why this matters
A brand can appear credible in an English global prompt and still disappear from Belgian, French, German, Dutch, city-level, or buyer-specific recommendations. Localized prompts make that gap visible before the client asks.
Generate prompts that mention the country, city or region, local buyer, and local language instead of generic global SEO wording.
Switch between testing your own brand and producing a client-ready test plan for an agency account.
Use the free prompt pack for first-pass testing, then use VectorGap when you need multi-model proof, competitor context, and prioritized remediation.
From prompt pack to proof
Use the free generator to start the client conversation, then use VectorGap when the account needs repeatable provider evidence, competitor context, remediation priorities, and retest proof.
Enter the brand, website, target market, language, category, persona, city, and competitors.
Generate prompts across discovery, local recommendations, competitor comparisons, commercial intent, and citation checks.
Copy the pack into your manual AI testing workflow or use it as the brief for a client conversation.
Use VectorGap when you need repeatable scoring, citations, provider comparison, remediation missions, retests, and reports.
What should the prompt pack test first?
A market-language-persona prompt set that asks how AI describes, recommends, compares, and cites the brand against named competitors.
Turn the generated prompts into a client-ready audit brief before running the localized baseline.
What does manual testing not prove?
A one-off answer can reveal a gap, but it does not preserve provider variance, source evidence, scoring notes, or comparable retest history.
Run the same target through the full provider panel so the result becomes evidence instead of a screenshot.
How should the fix be retested?
The useful comparison repeats the same provider and competitor target with the same market, language, persona, category, and intent.
Ship the page, proof, schema, entity, or source fix, then retest the same provider and competitor target for the client report.
Manual prompt testing is a good first signal. It is not enough for recurring agency delivery. Localized AI visibility needs repeatable provider coverage, prompt history, competitor evidence, source extraction, and remediation tracking.
Run the full VectorGap auditManual prompts show whether there is a problem.
The audit shows which models, markets, citations, and competitor answers caused the problem.
The remediation workflow turns weak answers into public pages, proof updates, schema improvements, and source fixes.
The generator gives agencies a strong manual test plan. The 5-credit audit runs the same market-specific angle across providers, competitors, source evidence, missions, retests, and white-label report exports.
Runs the prompt set across the 7-provider panel: ChatGPT, Claude, Gemini, Perplexity, Grok, Mistral, and DeepSeek.
Compares provider answer differences instead of relying on one manual screenshot.
Identifies source, citation, competitor preference, and market-language gaps behind the answer.
Turns the strongest gap into remediation missions, retest targets, and a white-label action plan.
It is a market-specific question designed to test how an AI assistant describes, recommends, compares, and cites a brand for a buyer in a specific country, city, language, and category.
No. The generator creates a useful manual test plan. A VectorGap localized audit runs prompts across AI providers, captures outputs and citations, benchmarks competitors, scores gaps, and turns findings into remediation work.
AI answers can change by market, language, and buyer intent. A brand may look visible in English but disappear in French, German, Dutch, or city-level recommendation prompts.
Yes. It produces a client-ready test plan without exposing proprietary audit mechanics. Use it to show why localized AI visibility requires repeatable evidence instead of one-off ChatGPT screenshots.