| name | campaign-analytics |
| description | Analyzes campaign performance with multi-touch attribution, funnel conversion, and ROI calculation for marketing optimization |
| zh_description | 用于活动、分析，支持内容、营销、渠道和数据分析。 |
| version | 1.0.0 |
| author | Alireza Rezvani |
| source | in-house |
| source_url | |
| license | MIT |
| tags | ["analytics", "campaign", "growth", "marketing"] |
| created_at | 2026-03-04 |
| updated_at | 2026-03-20 |
| quality | 5 |
| complexity | intermediate |
| metadata | null |
| 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 |
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.
Table of Contents
Capabilities
- Multi-Touch Attribution: Five attribution models (first-touch, last-touch, linear, time-decay, position-based) with configurable parameters
- Funnel Conversion Analysis: Stage-by-stage conversion rates, drop-off identification, bottleneck detection, and segment comparison
- Campaign ROI Calculation: ROI, ROAS, CPA, CPL, CAC metrics with industry benchmarking and underperformance flagging
- A/B Test Support: Templates for structured A/B test documentation and analysis
- Channel Comparison: Cross-channel performance comparison with normalized metrics
- Executive Reporting: Ready-to-use templates for campaign performance reports
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",
