/evaluate-attribution-models

name: evaluate-attribution-models
description: Compares attribution models, highlights trade-offs, and recommends rollout plans.
usage: /marketing-analytics:evaluate-attribution-models --campaigns launch_q1,evergreen_abm --models first,last,position,data-driven --audience finance

Command: evaluate-attribution-models

Inputs

• **campaigns** – list of campaigns/programs to analyze.
• **models** – attribution models to compare (first, last, linear, position, time-decay, data-driven).
• **audience** – finance | marketing-lead | ops | exec.
• **metrics** – choose KPIs (pipeline, revenue, CAC, payback, LTV, ROAS).
• **confidence** – optional minimum data confidence threshold to highlight gaps.

Workflow

1. **Data Preparation** – pull campaign performance, cost, and pipeline/revenue outcomes. 2. **Model Execution** – run requested models, normalize windows, and apply weighting rules. 3. **Sensitivity Analysis** – compare outcomes vs benchmarks, highlight variance drivers. 4. **Narrative Assembly** – contextualize trade-offs, governance considerations, and risks. 5. **Recommendation Engine** – propose primary model, fallback, and rollout/QA checklist.

Outputs

• Attribution comparison deck/table with KPI deltas per model.
• Recommendation memo with decision, rationale, and risk mitigations.
• Rollout plan including QA steps, owner assignments, and monitoring hooks.

Agent/Skill Invocations

• `attribution-architect` – leads methodology comparison.
• `marketing-intelligence-lead` – ensures narrative + stakeholder alignment.
• `attribution-playbook` skill – documents rules + templates.
• `exec-dashboard-blueprint` skill – packages executive summary.

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