campaign-analytics
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.
Profile →npx skills add alirezarezvani/claude-skills --skill campaign-analytics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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":
- Input Requirements
- Attribution Analyzer
- Funnel Analyzer
- Campaign ROI Calculator
- Input Validation
- Output Formats
- Typical Analysis Workflow
- How to Use
- Attribution Analysis
- Funnel Analysis
- Campaign ROI Calculation
- Scripts
- 1. attributionanalyzer.py
- 2. funnelanalyzer.py
Step 1 — Attribution: understand which channels drive conversions python scripts/attribution_analyzer.py campaign_data.json --model time-decay Step 2 — Funnel: identify where prospects drop off on the path to conversion python scripts/funnel_analyzer.py funnel_data.json Step 3 — ROI: calculate profitability and benchmark against industry standards python scripts/campaign_roi_calculator.py campaign_data.json Run all 5 attribution models python scripts/attribution_analyzer.py campaign_data.json Run a specific model JSON output for pipeline integration
What does the campaign-analytics skill do?
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.
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill campaign-analytics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.