Analyze Google Ads Quality Score, a keyword-level quality rating, across expected click-through rate, ad relevance, and landing page experience. Identify weak components and their causes, then prioritize fixes by potential click-cost savings and conversion impact.
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Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact. Platform: Google.
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Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact.
Claude pulls your keyword-level Quality Score data along with historical QS trends, CTR benchmarks, ad copy relevance signals, and landing page metrics. It identifies which of the three components is below average for each keyword and cross-references with your actual ad copy and landing pages to pinpoint the exact issue.
You have 340 active keywords. Claude identifies 47 with Quality Score 5 or below. Of those, 28 have below-average landing page experience (mostly because 3 landing pages have slow mobile load times), 14 have below-average ad relevance (the ad groups contain too many unrelated keywords diluting relevance), and 5 have below-average expected CTR (they're in ad groups where CTR is dragged down by poor-performing ad copy variants). Fixing the 3 landing pages alone would impact 28 keywords and potentially reduce CPC by 15-25%.
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.