geo-performance-analysis

--- name: geo-performance-analysis description: Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits. Platform: Google and Meta. metadata: platform: Google and Meta --- # 24/ Geo Performance Analysis — Google + Meta ## What it does Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits. ## How it works Claude analyzes your performance data segmented by location, identifies statistically significant performance differences (not just noise from low-volume areas), and calculates the cost of running campaigns in underperforming regions vs the conversions you'd lose by excluding or reducing them. ## Practical example Your national ecommerce campaigns spend evenly across the US. Claude finds that 8 states produce 65% of your conversions at a $24 CPA, while 12 states spend $8,400/month combined with a $71 CPA and only 118 conversions. Three metro areas — Dallas, Phoenix, and Atlanta — outperform their state averages by 40%+ and could absorb more budget. Recommendation: reduce bids 40% in the 12 underperforming states, increase 25% in the top 8, and create separate campaigns for the 3 outperforming metros to give them dedicated budgets. ## What you get back - Performance breakdown by geo level with CPA, ROAS, CVR, and volume - Tier ranking of geos (top performers, average, underperformers) with clear thresholds - Bid adjustment recommendations by geo with projected impact - Campaign split recommendations for high-volume geos that deserve independent management - Spend reallocation model showing how redistributing from weak to strong geos affects total conversions ## When to use it - When running national or multi-market campaigns and need to optimize allocation - After expanding into new regions to evaluate early performance - Quarterly to catch geo performance shifts as market conditions change - When clients ask "where should we focus" and you need data behind the recommendation ## 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

["Gather campaign data: Export performance metrics (spend, conversions, ROAS, CPA) from [PLATFORM] for the [DATE_RANGE]. Include geographic breakdowns at your target level ([GEO_LEVEL]).","Define criteria: Decide what ‘underperforming’ or ‘high-performing’ means for your goals (e.g., ROAS < 2.0, CPA > $30). Adjust thresholds based on your industry benchmarks.","Run the analysis: Paste the prompt template into your AI tool, replacing [PLACEHOLDERS] with your data. For Google Ads, use the ‘Geo Performance’ report; for Meta, use the ‘Breakdown by Geography’ report.","Implement changes: Apply bid adjustments or campaign splits in your ad platform. Use the AI’s recommendations as a starting point, then A/B test adjustments over 2–4 weeks.","Iterate: Re-run the analysis monthly to account for seasonality, new geo trends, or shifts in performance. Compare results to your initial recommendations to refine future optimizations."]