campaign-analytics

What This Skill Does

The campaign-analytics skill provides a production-grade toolkit for deterministic marketing performance measurement. By leveraging three specialized Python CLI scripts, it allows users to perform multi-touch attribution, analyze funnel conversion bottlenecks, and calculate critical financial performance indicators like ROI, ROAS, and CPA. This skill is designed for high-integrity data analysis, operating entirely on standard Python libraries without the need for external APIs, ML models, or cloud-based data transmissions. It provides a repeatable, transparent method for evaluating how specific marketing channels influence the customer journey and contribute to final revenue.

Installation

To integrate this skill into your environment, run the following command within your OpenClaw agent interface:

clawhub install openclaw/skills/skills/alirezarezvani/campaign-analytics

Ensure your local environment has Python installed, as the tools operate as local CLI scripts. We recommend validating your input data using python -m json.tool before processing to ensure compatibility with the expected schema.

Use Cases

• Attribution Modeling: Determine which touchpoints (e.g., organic search vs. email) contribute most to conversions using time-decay or linear attribution models.
• Funnel Optimization: Identify specific stages in your acquisition funnel where drop-off rates exceed benchmarks.
• Budget Allocation: Calculate exact ROAS for various channels to identify where to increase or decrease marketing spend.
• Performance Reporting: Generate structured, machine-readable JSON reports for automated dashboards or human-readable tables for executive summaries.

Example Prompts

1. "Analyze my campaign_data.json using the attribution analyzer with a time-decay model to see which channels are driving late-stage conversions."
2. "Check the funnel performance in funnel_data.json. Where is the biggest drop-off between awareness and purchase, and what are the raw conversion rates?"
3. "Calculate the ROI for all campaigns listed in campaign_data.json and provide the output in JSON format so I can import it into my spreadsheet."

Tips & Limitations

• Data Integrity: The scripts are deterministic and rely on strict input schemas. Always verify that your JSON follows the required structure, particularly regarding array lengths for funnel stages.
• Scope: Since this skill uses no external APIs, it does not auto-fetch data from platforms like Google Ads or Facebook. You must export your source data into the required JSON format first.
• Performance: Because it utilizes standard Python libraries, it is extremely fast and secure, making it ideal for processing large local datasets without privacy concerns.