Analyze Google and Meta campaign results by weekday and hour to recommend advertising schedules. Estimate spending reductions, conversions lost, and the impact of moving budget to better periods, while accounting for limited data.
中文简介正在准备中。当前显示英语简介。
Analyzes performance by day of week and hour of day across your campaigns. Identifies when your ads perform best and worst, recommends ad schedule adjustments with estimated savings, and tells you exactly what you'd give up by restricting hours. Platform: Google and Meta.
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Analyzes performance by day of week and hour of day across your campaigns. Identifies when your ads perform best and worst, recommends ad schedule adjustments with estimated savings, and tells you exactly what you'd give up by restricting hours.
Claude segments your performance data by day and hour, looking at CPA, CVR, CTR, and spend distribution. It identifies statistically meaningful patterns (not just noise from low-volume hours) and calculates the cost of running ads during underperforming windows vs the conversions you'd lose by turning them off.
Your B2B SaaS campaigns show CPA of $31 during weekday business hours (8am-6pm) but $67 on weekends and $54 after 9pm. Weekend spend accounts for $4,200/month producing 63 leads at $67 each. Claude calculates that cutting weekends and nights saves $6,100/month in spend while losing only 89 conversions — but reallocating that budget to peak hours would generate an estimated 142 conversions at the lower CPA. Net gain: 53 additional conversions.
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。
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.
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.
中文简介正在准备中。当前显示英语简介。