Compares your key metrics against industry benchmarks for your specific vertical, campaign type, and platform. Tells you where you're ahead, where you're behind, and where there's room to improve — adjusted for your account size and spend level, because a $10K/month account and a $500K/month account have different benchmark realities. Platform: Google and Meta.
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Compares your key metrics against industry benchmarks for your specific vertical, campaign type, and platform. Tells you where you're ahead, where you're behind, and where there's room to improve — adjusted for your account size and spend level, because a $10K/month account and a $500K/month account have different benchmark realities.
Claude takes your core metrics (CPC, CTR, CVR, CPA, ROAS, CPM) and compares them against available benchmark data for your industry and campaign type. It adjusts for factors that affect comparison — account maturity, geo, budget level, and funnel stage — so you're not comparing your prospecting CPA against someone else's retargeting CPA.
Your SaaS client's Google Search campaigns show a 3.2% CTR and $52 CPA. Claude benchmarks this against B2B SaaS averages: CTR is 18% above benchmark (strong ad relevance), but CPA is 30% above benchmark, with the gap primarily in CVR (2.1% vs benchmark 3.4%). This points to a landing page issue rather than an ad issue — your ads attract clicks at a good rate, but the landing page isn't converting them. For Meta, your CPM of $18 is right at benchmark, but your hook rate on video ads (22%) is well below the 35% benchmark, suggesting the first 3 seconds of your videos need work.
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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概要と使いどころ
Statistical significance calculator for A/B test results with sample size requirements, segment breakdowns, and hypothesis generation. Use when feeding test results, checking statistical significance, calculating sample sizes, analyzing experiment outcomes, or generating next test ideas based on results. Platform: Google and Meta.
日本語の概要は準備中です。原文の説明を表示しています。
Designs statistically valid split tests for ads, audiences, landing pages, or bid strategies. Calculates required sample sizes before you start, monitors results during the test, and calls winners when statistical significance is actually reached — not when you feel like one is winning. Platform: Google and Meta.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates your campaign and ad set structure against your actual goals and budget. Flags over-segmentation that fragments your data, under-segmentation that hides performance differences, budget allocation issues, and consolidation opportunities that would improve algorithmic delivery and your ability to optimize. Platform: Google and Meta.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes your top performing ads, identifies what's working in the hooks, CTAs, messaging angles, and formats, then generates new variants that follow the same winning patterns while introducing enough variation to test meaningfully. Platform: Google and Meta.
日本語の概要は準備中です。原文の説明を表示しています。
Reviews all your Google Ads extensions — sitelinks, callouts, structured snippets, call extensions, image extensions, price extensions — across every campaign. Flags what's missing, what's underperforming, what's outdated, and writes replacements based on your best performing ads and landing pages. Platform: Google.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-channel budget optimization using MER, marginal ROAS, and diminishing returns analysis. Use when pasting multi-channel spend and results data, requesting reallocation recommendations, analyzing budget shift priorities, or optimizing marketing efficiency across Google, Meta, TikTok, and other channels. Platform: Google and Meta.
日本語の概要は準備中です。原文の説明を表示しています。