/Catalogue/Prompt/irinabuht12-oss/irinabuht12-oss-marketing-skills-account-structure-review

Origin: github

account-structure-review

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.

by irinabuht12-oss · updated 1d ago · imported from GitHub

Installs0+0/7d
Security score98/100
Retention 14d0%
GitHub stars2K

Skill logic

Execution graph
User message
Prompt rewrites behaviour
Response

SKILL.md

View on GitHub ↗

17/ Account Structure Review — Google + Meta

What it does

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.

How it works

Claude maps your entire account structure — campaigns, ad sets/ad groups, targeting, budgets, and bid strategies — and evaluates it against best practices for your specific situation. It considers conversion volume per campaign (enough for algorithms to learn), budget distribution (too many campaigns splitting too little budget), targeting overlap, and whether your structure supports clean testing and reporting.

Practical example

Your Google Ads account has 34 search campaigns. Claude finds that 19 of them have fewer than 10 conversions per month — not enough for automated bidding to work. Twelve campaigns have daily budgets under $15, meaning they run out by noon. Three campaigns target nearly identical keyword sets in different geographies but could be consolidated with geo bid adjustments. Recommendation: consolidate down to 14 campaigns, which would give each campaign 25+ monthly conversions and $40+ daily budgets while maintaining clean reporting segments.

What you get back

  • Full account structure map with performance metrics at each level
  • Campaigns flagged for insufficient conversion volume, budget fragmentation, or targeting overlap
  • Specific consolidation recommendations with projected performance impact
  • Recommended structure with campaign/ad group grouping logic explained
  • Migration plan showing how to consolidate without losing historical data or disrupting active campaigns

When to use it

  • When inheriting a new account from a previous team or agency
  • Quarterly account health checks
  • When performance plateaus and structural issues might be holding back algorithms
  • Before scaling, because a messy structure at $20K/month becomes a disaster at $100K/month

Data access (Ryze MCP)

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:

  • claude.ai / Claude Desktop: Settings → Connectors → Add custom connector → https://connector.get-ryze.ai/mcp
  • Claude Code: claude mcp add ryze --transport http https://connector.get-ryze.ai/mcp
  • Cursor: Settings → MCP → add the same URL

Setup guide: https://www.get-ryze.ai/how-to-connect-claude-to-google-meta-ads-mcp

Discussion

No comments yet — start the thread.

Sign in to join the discussion.

/More from irinabuht12-oss/marketing-skills

irinabuht12-oss· 1d agoCommunity
ab-test-analyzer

Prompts · v0.1.0

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.

#ai-visibility#claude-code#claude-desktop

0 2K
irinabuht12-oss· 1d agoCommunity

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.

#ai-visibility#claude-code#claude-desktop

0 2K
irinabuht12-oss· 1d agoCommunity
ad-copy-variant-generator

Prompts · v0.1.0

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.

#ai-visibility#claude-code#claude-desktop

0 2K
irinabuht12-oss· 1d agoCommunity
ad-extension-audit

Prompts · v0.1.0

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.

#ai-visibility#claude-code#claude-desktop

0 2K