Models what happens to your CPA, ROAS, conversion volume, and impression share when you increase or decrease budget by any amount. Uses your actual account data and historical diminishing returns patterns, not generic industry assumptions. Platform: Google and Meta.
git clone https://github.com/irinabuht12-oss/marketing-skills.git--- name: budget-scenario-planner description: Models what happens to your CPA, ROAS, conversion volume, and impression share when you increase or decrease budget by any amount. Uses your actual account data and historical diminishing returns patterns, not generic industry assumptions. Platform: Google and Meta. metadata: platform: Google and Meta --- # 3/ Budget Scenario Planner — Google + Meta ## What it does Models what happens to your CPA, ROAS, conversion volume, and impression share when you increase or decrease budget by any amount. Uses your actual account data and historical diminishing returns patterns, not generic industry assumptions. ## How it works Claude looks at your historical spend-to-conversion relationship at different budget levels, maps the efficiency curve, and projects where you'll land at a new spend level. It accounts for auction dynamics, meaning that scaling 50% doesn't mean 50% more conversions — it models the real falloff. ## Practical example Client wants to go from $30K/month to $50K/month on Meta. Claude analyzes the last 90 days and shows that the first $10K increase will bring CPA from $38 to $43 (still within target), but the last $10K pushes CPA to $58 because you'll exhaust the high-intent audience and start hitting colder segments. Recommendation: scale to $40K first, test new audiences, then push to $50K. ## What you get back - Projected CPA, ROAS, and conversion volume at each budget level - The efficiency curve showing where diminishing returns kick in - Break-even points where scaling stops making financial sense - Recommended budget level with reasoning - Comparison across campaigns showing which ones have the most room to scale ## When to use it - Client or leadership asks to increase or cut budget - Quarterly planning when setting budget allocations - When deciding which campaigns deserve more budget - Before pitching a budget increase to show the projected return ## 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
[{"step":1,"action":"Gather your account data. Export a 90-day performance report from your [PLATFORM: Google Ads or Meta Ads] account, including columns for spend, conversions, CPA, ROAS, impression share, and audience segments. Save this as a CSV file.","tip":"Use the platform’s built-in 'Reports' tool to export data with the exact metrics needed. For Google Ads, go to 'Reports' > 'Predefined reports' > 'Campaigns' > 'Performance'. For Meta, use 'Ads Manager' > 'Reports' > 'Export'."},{"step":2,"action":"Input the data into the AI model. Paste the exported CSV into the prompt template, replacing [PLACEHOLDERS] with your specific values (e.g., budget change, time period). Specify whether you want to model a 'best case', 'worst case', or 'most likely' scenario.","tip":"For complex accounts, break the analysis into smaller campaigns or ad sets to avoid overwhelming the model. Focus on high-spend segments first (e.g., top 20% of campaigns by budget)."},{"step":3,"action":"Review the AI’s projections. Compare the predicted changes in CPA, ROAS, conversion volume, and impression share against your current benchmarks. Identify which metrics are most critical for your goals (e.g., ROAS vs. volume).","tip":"Pay attention to the 'diminishing returns' notes in the output. If the model suggests a sharp drop in efficiency beyond a certain budget increase, consider testing smaller increments (e.g., +10% instead of +25%)."},{"step":4,"action":"Refine the scenario. Adjust the budget change or add constraints (e.g., 'Do not exceed a 5% CPA increase' or 'Prioritize impression share growth'). Regenerate the analysis to see how the outcomes shift.","tip":"Use the 'bid strategy' recommendations in the output to guide your adjustments. For example, if the model suggests using tROAS, note the target ROAS value it provides."},{"step":5,"action":"Implement and monitor. Apply the recommended budget changes and bid strategy adjustments to your live campaigns. Track performance daily for the first week using the platform’s dashboards (e.g., Google Ads 'Campaigns' view or Meta Ads 'Ads Manager').","tip":"Set up automated alerts in your platform for key metrics (e.g., CPA exceeding $75) to catch deviations early. Compare actual performance to the AI’s projections after 7 and 30 days to validate the model’s accuracy."}]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/irinabuht12-oss/marketing-skills/tree/main/skills/budget-scenario-plannerCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Analyze the impact of adjusting the [PLATFORM: Google Ads or Meta Ads] budget by [BUDGET_CHANGE: e.g., +20%, -15%, $5,000] for [ACCOUNT_NAME: e.g., 'Acme Corp's Search Campaign']. Use our actual account data from the last [TIME_PERIOD: e.g., 90 days] to model changes in [METRICS: CPA, ROAS, conversion volume, impression share]. Account for historical diminishing returns patterns and provide specific predictions for [SCENARIOS: e.g., 'best case', 'worst case', and 'most likely']. Include recommendations for bid strategy adjustments to optimize the new budget allocation.
For Acme Corp’s Google Search campaign, increasing the budget by 25% (from $12,000 to $15,000 monthly) over the next 30 days is projected to yield the following outcomes based on historical diminishing returns data from Q2 2024: **Conversion Volume:** Expected to rise from 180 to 210 conversions (+16.7%), though the incremental gain tapers due to saturation in high-intent keywords. The top-performing ad groups (e.g., 'Branded Terms' and 'High-Intent Shopping') will see the highest lift (22% and 18%, respectively), while generic terms like 'Home Appliances' will only grow by 8% due to lower incremental reach. **CPA:** Likely to increase from $66.67 to $71.43 (+7.1%) as the campaign targets less efficient audiences to absorb the additional spend. However, this can be mitigated by shifting 15% of the new budget to RLSA (Remarketing Lists for Search Ads) audiences, which historically convert at a 12% lower CPA. **ROAS:** Projected to drop from 4.2x to 3.9x (-7.1%) without adjustments, but implementing a tROAS bid strategy of 3.8x for the new budget could stabilize ROAS at 4.0x while maintaining volume growth. **Impression Share:** Will expand from 78% to 85%, with the most significant gains in mobile searches (now 82% vs. 75% previously). Competitor overlap remains stable at 12%, indicating no major bid wars in the auction. **Recommendations:** 1. Allocate 40% of the new budget to high-performing ad groups (e.g., 'Branded Terms') to maximize efficiency. 2. Increase RLSA bid adjustments by 20% to capture lower-funnel traffic. 3. Monitor impression share daily for the first week to adjust bids dynamically and avoid over-saturation in underperforming segments. *Note: These projections assume no major changes in competitor activity or seasonality. For Meta Ads, the same analysis would require adjusting for auction dynamics and audience overlap.*
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