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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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.
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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.
Claude ingests your ad performance data alongside the actual ad copy and creative specs. It correlates performance metrics (CTR, CVR, CPA) with copy elements — headline structure, primary text length, tone, CTA type, pain point vs benefit framing, social proof usage. Then it generates variants that preserve the winning elements while changing specific variables.
Your best performing Meta ad has a hook that leads with a specific number ("Cut your onboarding time from 3 weeks to 3 days"), uses a customer quote in the middle, and ends with a soft CTA. Claude generates 8 variants: 4 keep the number-led hook pattern but change the metric, 2 test a question-based hook with the same body structure, and 2 flip to benefit-first with the number as proof. Each variant changes one or two elements so you can isolate what's actually driving performance.
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
中文简介正在准备中。当前显示英语简介。
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.
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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.
中文简介正在准备中。当前显示英语简介。