Build a question set to check whether AI assistants mention your brand. Analyze the answers you collect, compare visibility against competitors, trace cited sources, and receive a prioritized list of opportunities to address gaps.
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Audit how visible your brand is inside AI answers (ChatGPT, Claude, Gemini, Perplexity, AI Overviews). Claude builds a prompt panel for your category, scores where you show up vs competitors, and turns the gaps into a prioritized fix list. Platform: AI visibility.
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Measures whether AI assistants recommend your brand when buyers ask category questions. Claude designs the question set your buyers actually ask, you run it across the major assistants, and Claude scores the results — mention rate, position, sentiment, and which sources the answers cite.
Give Claude your brand, category, top 3 competitors, and target buyer. It generates a 30–50 prompt panel (category queries, comparison queries, "best X for Y" queries, problem queries). You paste in the AI answers you get back, and Claude builds a visibility scorecard plus a gap analysis: where competitors are cited and you're not, and which cited sources you could realistically get into.
A B2B ads tool runs the panel and finds it's mentioned in 4 of 40 answers while a competitor appears in 26. Claude traces the competitor's mentions to three sources — a G2 category page, one comparison blog post ranking on page 1, and a Reddit thread — and outputs a plan targeting exactly those citation sources.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.