Analyze competitor ads from Meta Ad Library and Google Ads Transparency Center, organize their messages and formats, and compare them with your strategy to find unused angles and ideas for campaign tests.
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Pulls competitor ads from Meta Ad Library and Google Ads Transparency Center, categorizes their messaging angles, formats, CTAs, and creative types, then identifies gaps in their approach you can exploit and patterns worth testing in your own campaigns. Platform: Meta.
安装前可以查看交给 AI 代理的指令内容。
Pulls competitor ads from Meta Ad Library and Google Ads Transparency Center, categorizes their messaging angles, formats, CTAs, and creative types, then identifies gaps in their approach you can exploit and patterns worth testing in your own campaigns.
Claude reviews competitor ad libraries and breaks down what they're running — how many active ads, what formats (video, static, carousel), what messaging themes (pain point, benefit, social proof, urgency), how often they rotate, and what offers they're pushing. It then maps this against your current creative strategy to find differentiation opportunities.
Your three main SaaS competitors are all running 15-25 active ads each on Meta. Claude finds that all three lead with feature-comparison messaging and "book a demo" CTAs. None are using customer testimonials as primary creative, none are running educational content ads, and only one uses video. Claude recommends testing UGC testimonial ads with a free trial CTA — a combination no competitor is using — and flags that Competitor B just launched 8 new ads in the last week, suggesting a campaign refresh or new product push.
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.
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。
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.
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.
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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。