campaign-analytics

name	campaign-analytics
description	Manage — Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad p
license	MIT
metadata	{"version":"1.0.0","author":"Alireza Rezvani","category":"marketing","domain":"campaign-analytics","updated":"2026-02-06T00:00:00.000Z","python-tools":"attribution_analyzer.py, funnel_analyzer.py, campaign_roi_calculator.py","tech-stack":"marketing-analytics, attribution-modeling"}
executor	HYBRID
skill_id	business.marketing-skill.campaign-analytics
status	ADOPTED
security	{"level":"standard","pii":false,"approval_required":false}
anchors	["business","marketing","data_science","performance"]
tier	2
input_schema	[{"name":"code_or_task","type":"string","description":"Code snippet, script, or task description to process","required":true}]
output_schema	[{"name":"report","type":"string","description":"Analysis report or summary from campaign analytics"}]

Campaign Analytics

Production-grade campaign performance analysis with multi-touch attribution modeling, funnel conversion analysis, and ROI calculation. Three Python CLI tools provide deterministic, repeatable analytics using standard library only -- no external dependencies, no API calls, no ML models.

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Input Requirements

All scripts accept a JSON file as positional input argument. See assets/sample_campaign_data.json for complete examples.

Attribution Analyzer

{
  "journeys": [
    {
      "journey_id": "j1",
      "touchpoints": [
        {"channel": "organic_search", "timestamp": "2025-10-01T10:00:00", "interaction": "click"},
        {"channel": "email", "timestamp": "2025-10-05T14:30:00", "interaction": "open"},
        {"channel": "paid_search", "timestamp":