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Analyzes campaign performance with multi-touch attribution, funnel conversion analysis, and ROI calculation for marketing optimization. Use when analyzing marketing campaigns, ad performance, attribution models, conversion rates, or calculating marketing ROI, ROAS, CPA, and campaign metrics across channels.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install alirezarezvani/campaign-analyticsExaminez la source et la compatibilité, puis suivez les étapes d’installation.
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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.
All scripts accept a JSON file as positional input argument. See assets/sample_campaign_data.json for complete examples.
{
"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": "2025-10-08T09:15:00", "interaction": "click"}
],
"converted": true,
"revenue": 500.00
}
]
}
{
"funnel": {
"stages": ["Awareness", "Interest", "Consideration", "Intent", "Purchase"],
"counts": [10000, 5200, 2800, 1400, 420]
}
}
{
"campaigns": [
{
"name": "Spring Email Campaign",
"channel": "email",
"spend": 5000.00,
"revenue": 25000.00,
"impressions": 50000,
"clicks": 2500,
"leads": 300,
"customers": 45
}
]
}
Before running scripts, verify your JSON is valid and matches the expected schema. Common errors:
journeys, funnel.stages, campaigns) → script exits with a descriptive KeyError
stages and counts must be the same length) → raises ValueError
TypeError
Use python -m json.tool your_file.json to validate JSON syntax before passing it to any script.
All scripts support two output formats via the `--forma...
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# 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.
---
## Input Requirements
All scripts accept a JSON file as positional input argument. See `assets/sample_campaign_data.json` for complete examples.
### Attribution Analyzer
```json
{
"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": "2025-10-08T09:15:00", "interaction": "click"}
],
"converted": true,
"revenue": 500.00
}
]
}
```
### Funnel Analyzer
```json
{
"funnel": {
"stages": ["Awareness", "Interest", "Consideration", "Intent", "Purchase"],
"counts": [10000, 5200, 2800, 1400, 420]
}
}
```
### Campaign ROI Calculator
```json
{
"campaigns": [
{
"name": "Spring Email Campaign",
"channel": "email",
"spend": 5000.00,
"revenue": 25000.00,
"impressions": 50000,
"clicks": 2500,
"leads": 300,
"customers": 45
}
]
}
```
### Input Validation
Before running scripts, verify your JSON is valid and matches the expected schema. Common errors:
- **Missing required keys** (e.g., `journeys`, `funnel.stages`, `campaigns`) → script exits with a descriptive `KeyError`
- **Mismatched array lengths** in funnel data (`stages` and `counts` must be the same length) → raises `ValueError`
- **Non-numeric monetary values** in ROI data → raises `TypeError`
Use `python -m json.tool your_file.json` to validate JSON syntax before passing it to any script.
---
## Output Formats
All scripts support two output formats via the `--forma...Search and hire real humans for tasks — photography, delivery, research, and more
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