roas-forecast-attribution-modeler

# Ads ROAS Forecast

## Purpose
Core mission:
- forecast scenario modeling, attribution sensitivity, budget recommendation

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

## When To Trigger
Use this skill when the user asks for:
- ad execution guidance tied to business outcomes
- growth decisions involving revenue, roas, cpa, or budget efficiency
- platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic
- this specific capability: forecast scenario modeling, attribution sensitivity, budget recommendation

High-signal keywords:
- ads, advertising, campaign, growth, revenue, profit
- roas, cpa, roi, budget, bidding, traffic, conversion, funnel
- meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

## Input Contract
Required:
- forecast_target: roas, cpa, or revenue
- planning_horizon
- base_assumptions

Optional:
- attribution_window_options
- budget_scenarios
- seasonality_factors
- risk_tolerance

## Output Contract
1. Model Inputs
2. Scenario Outputs
3. Sensitivity Analysis
4. Attribution Impact Notes
5. Budget Recommendation

## Workflow
1. Normalize baseline metrics and assumptions.
2. Build base, upside, and downside scenarios.
3. Run sensitivity on conversion rate and CPC assumptions.
4. Compare attribution windows and expected deltas.
5. Recommend budget path with confidence bounds.

## Decision Rules
- If assumptions are uncertain, widen forecast intervals and reduce aggressiveness.
- If scenario spread is large, recommend phased budget release.
- If attribution window drives major variance, present dual-plan decisions.

## Platform Notes
Primary scope:
- Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, Shopify Ads, DSP/programmatic

Platform behavior guidance:
- Keep recommendations channel-aware; do not collapse all channels into one generic plan.
- For Meta and TikTok Ad...