Analyze cited URLs from AI answers to find where your business could earn mentions. Get ranked sources, citation frequency by source type, feasibility assessments, and draft outreach messages or content briefs.
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Find the exact pages AI assistants cite when answering questions in your category, and identify which ones you can get into. Claude clusters the cited sources, scores each by attainability, and outputs an outreach/content plan. Platform: AI visibility.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
AI answers are built from a surprisingly small set of sources — review sites, comparison posts, Reddit threads, docs, Wikipedia. Claude analyzes which sources get cited for your category's questions and tells you which ones are worth pursuing, so you stop guessing where to earn mentions.
Paste in AI answers (with citations) from Perplexity, ChatGPT search, and Google AI Overviews for your key queries. Claude extracts every cited URL, clusters them by type (review platform, listicle, community, editorial, docs), counts citation frequency, and scores each cluster by attainability — can you get listed, pitch an update, or publish a competing page that fits the citation pattern.
For "best CRM for agencies," 62% of citations across assistants come from 9 URLs. Claude flags that two are listicles updated quarterly (pitchable), one is a G2 category page (fixable via review volume), and three are Reddit threads (community play). It drafts the pitch email for the listicles and the Reddit engagement guidelines.
This skill works best with live account data. Connect the free Ryze MCP once and Claude reads your Google Ads, Meta Ads, GA4 and Search Console directly:
https://connector.get-ryze.ai/mcpclaude mcp add ryze --transport http https://connector.get-ryze.ai/mcpSetup guide: https://www.get-ryze.ai/how-to-connect-claude-to-google-meta-ads-mcp
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Analyze A/B test results to assess whether observed differences are likely due to chance. Check test duration and sample size, compare audience segments, distinguish statistical findings from practical value, and generate hypotheses for follow-up tests.
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Plan and analyze A/B tests for Google and Meta advertising. Estimate required traffic and duration, track results, and assess whether observed differences are statistically significant, meaning unlikely to be explained by chance alone.
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Review Google and Meta campaign structures against goals, budgets, and conversion data. Identify excessive segmentation, overlapping targeting, and fragmented budgets, then get consolidation recommendations, an explained account structure, and a migration plan.
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Analyze successful Google and Meta ads to find useful patterns in headlines, body text, and calls to action. Generate new copy variants that preserve those patterns, with platform formatting, test priorities, and suggested pairings for comparison.
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Review Google Ads extensions, the extra links and details shown with ads, across campaigns. Find missing coverage, weak performance, and outdated information, then get replacement copy based on successful ads and landing pages, plus rollout priorities.
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Analyze spending, revenue, and conversions across advertising channels to recommend budget shifts. Compare overall efficiency with the revenue gained from additional spending, identify saturation, and produce a gradual reallocation plan with monitoring priorities.
中文简介正在准备中。当前显示英语简介。