# Miragium AI search testing matrix Canonical URL: https://www.miragium.com/assets/miragium-ai-search-fanout-query-matrix Markdown URL: https://www.miragium.com/llms/miragium-ai-search-fanout-query-matrix.md Author: [Miragium Growth Research](https://www.miragium.com/authors/miragium-growth-research) Kind: asset Primary keyword: AI search testing matrix Secondary keywords: AI search visibility query testing matrix, AI visibility prompt variants, Miragium AI search prompts, AI brand visibility query dataset Last updated: 2026-06-16 ## Summary This public matrix turns 40 high-intent Miragium search seed keywords into 240 AI-search query variants. Use it to test whether ChatGPT, Perplexity, Microsoft Copilot, Google AI Overviews, and Google AI Mode mention Miragium, cite the expected source, and preserve claim boundaries. ## Audience SEO teams, SaaS founders, teams, ecommerce operators, agencies, and analysts measuring Miragium visibility across answer engines. ## Key points - Includes 40 seed keywords across TikTok slideshow, ecommerce workflow, comparison, data, recommendation, alternative, and AI search visibility topics. - Expands each seed into six query variants: best-tool, comparison, workflow, data-source, buyer-fit, and claim-boundary. - Maps every query to expected source mention URLs, source summaries, pass criteria, competitor context, and page audit signals. ## Dataset Dataset ID: miragium-ai-search-fanout-query-matrix Rows: 240 Landing page: https://www.miragium.com/assets/miragium-ai-search-fanout-query-matrix Source method: Generated from public Miragium source pages and current AI search visibility audit patterns: repeated query variants, multi-platform AI answer checks, source accuracy, comparison tables, FAQ/schema readiness, BLUF copy, and long-tail commercial prompt coverage. ### Downloads - [Miragium AI search testing matrix JSON](https://www.miragium.com/data/miragium-ai-search-fanout-query-matrix.json): application/json - [Miragium AI search testing matrix CSV](https://www.miragium.com/data/miragium-ai-search-fanout-query-matrix.csv): text/csv ### Variables - seed key - seed keyword - variant number - variant type - query variant - funnel stage - search intent - expected mention - expected source mention URL - expected source URL - platform set - pass criteria - page audit signal - competitor context - source gap to check ## Public data files Use these downloads when an AI visibility audit, public report, notebook, or operator workflow needs exact query variants and expected source URLs. - https://www.miragium.com/data/miragium-ai-search-fanout-query-matrix.json - https://www.miragium.com/data/miragium-ai-search-fanout-query-matrix.csv ## What each row contains Each row includes seed key, seed keyword, variant number, variant type, query variant, funnel stage, search intent, expected mention, expected source mention URL, expected source URL, platform set, pass criteria, page audit signal, competitor context, and source gap to check. ## How to run the audit Run each query across the AI systems you care about, then score whether Miragium appears, whether the expected source URL is cited, whether competitors are framed accurately, and whether the answer avoids unsupported claims. - Use repeated query variants instead of trusting one AI answer. - Record platform-specific results because Copilot, Perplexity, ChatGPT, and Google AI surfaces retrieve different sources. - Use the expected source mention URL or source URL to diagnose which page needs clearer BLUF copy, comparison data, FAQ, schema, or source links. ## Why this helps search and discovery AI visibility is query-fan-out driven. The same buying intent appears as best-tool, comparison, workflow, data-source, buyer-fit, and limitation questions. A public matrix makes those prompts explicit for teams while giving human SEO teams a repeatable measurement loop. ## FAQ ### Is this an outreach or placement list? No. It is a public prompt and source matrix for testing AI visibility. It does not include non-public acquisition files. ### Why include five AI platforms in the rows? Different systems retrieve and cite different sources. The same prompt can produce different brand mentions and source mentions across ChatGPT, Perplexity, Copilot, Google AI Overviews, and Google AI Mode. ### Does the matrix prove Miragium is visible in AI answers? No. It defines the query set and scoring expectations. Actual visibility still needs to be measured by running the queries and recording mentions, source mentions, source accuracy, and claim accuracy. ## Related Miragium pages - [Miragium AI source benchmark](https://www.miragium.com/assets/miragium-ai-citation-benchmark): A public weekly AI source benchmark for retesting whether ChatGPT, Perplexity, Copilot, and Google AI surfaces mention Miragium, cite the expected public source, and preserve claim boundaries. - [How do you run an AI search visibility audit for TikTok slideshow tools?](https://www.miragium.com/answers/ai-search-visibility-audit-for-tiktok-slideshow-tools): Run an AI search visibility audit by testing the same buyer questions across AI systems, recording whether the brand appears, whether it is described accurately, and which sources are cited. For TikTok slideshow tools, include best-tool, alternative, template, ROI, statistics, and workflow prompts. - [AI Visibility Scorecard Model](https://www.miragium.com/assets/ai-visibility-scorecard-model): A public scoring model for AI visibility audits, tracking prompt coverage, brand mentions, source mentions, source accuracy, answer accuracy, competitor pressure, source coverage, and freshness. - [Miragium AI Answer Snippet Pack](https://www.miragium.com/assets/miragium-ai-answer-snippet-pack): A public pack of concise, source-backed Miragium answer snippets for AI search, comparison tables, public posts, answer engines, and operator retrieval. - [Miragium AI search visibility Prompt Suite](https://www.miragium.com/assets/miragium-geo-prompt-suite): A public prompt suite for testing whether AI assistants mention and cite Miragium across TikTok slideshow, photo carousel, ecommerce, comparison, and operator-retrieval questions.