19/ ROAS Forecasting, Google + Meta

What it does

Projects your ROAS for the next 30, 60, and 90 days based on current performance trends, seasonality patterns from your historical data, and planned budget or campaign changes. Gives you a range with confidence intervals, not a single number pretending to be precise.

How it works

Claude takes your trailing performance data, identifies the trend line (improving, declining, or stable), overlays seasonal patterns from the same period in prior years if available, and factors in any known upcoming changes (budget shifts, new campaigns, creative launches). It produces a forecast range showing best case, expected case, and conservative case.

Practical example

Your ecommerce account is averaging 4.2x ROAS in March. Claude's analysis shows ROAS typically dips 15-20% in April based on last year's data (post-spring-sale slowdown), your top creative set is showing early fatigue signals that will reduce efficiency by ~10% over the next 30 days, and you're planning a 20% budget increase which historically reduces marginal ROAS by 8-12%. 30-day forecast: 3.1x (conservative) to 3.6x (expected) to 4.0x (best case, if new creatives outperform).

What you get back

• 30/60/90 day ROAS projections with confidence ranges
• Key assumptions behind each scenario (trend, seasonality, budget impact)
• Risk factors that could push results toward the conservative end
• Upside opportunities that could push toward best case
• Revenue projections at each ROAS level tied to planned spend

When to use it

• Monthly planning and client expectation setting
• Before committing to budget increases with stakeholders
• Quarterly business reviews where leadership wants revenue projections
• When seasonal shifts are approaching and you need to model the impact on efficiency

Data access (Ryze MCP)