What platforms does this skill support?

The skill supports major advertising platforms (Google Ads, Meta, LinkedIn), analytics (GA4, Mixpanel, Amplitude), email services (Mailchimp, HubSpot), and social networks (Instagram, Twitter).

How does it handle data quality and anomalies?

It performs automated checks for completeness, cross-platform consistency (e.g., GA4 vs Ads variance), and uses z-score thresholds to flag unusual spikes in spend or drops in conversions.

Where are the reports and data stored?

By default, the skill outputs raw and transformed data to the .aiwg/marketing/data/ directory and generates readable reports in the .aiwg/marketing/reports/ folder.

Can I customize the attribution models?

Yes, the skill includes pre-configured models like last-click, first-click, linear, time-decay, and position-based attribution, which can be toggled in the pipeline configuration.

Marketing Data Pipeline

Name: Marketing Data Pipeline
Author: jmagly

byjmagly

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102

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Marketing Automation

Orchestrates automated marketing data collection, cross-channel transformation, and performance reporting within your development workflow.

The Marketing Data Pipeline skill streamlines the complex process of managing multi-channel marketing data by automating collection from platforms like Google Ads, Meta, and GA4. It goes beyond simple data pulling by applying sophisticated transformation rules, calculating derived metrics like ROAS and CPA, and implementing various attribution models. Designed for growth engineers and marketing analysts, it includes built-in data quality checks, anomaly detection, and automated reporting, ensuring your marketing stack remains synchronized and your insights are always based on fresh, validated data.

Key Features

01Built-in attribution modeling supporting Last-click, Linear, and Position-based logic

02Rigorous data quality validation with automated anomaly detection alerts

03102 GitHub stars

04Advanced metric transformation including ROAS, CPA, and custom KPI calculations

05Automated multi-platform data collection from Ads, Analytics, Email, and Social sources

06Standardized performance reporting with cross-channel aggregation and CSV/JSON output

Use Cases

01Automating daily performance reports across fragmented advertising and social channels

02Identifying and resolving data discrepancies between analytics platforms and ad managers

03Monitoring campaign spend anomalies and conversion drops using automated quality checks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jmagly/aiwg data-pipeline

For use in Claude.ai and ChatGPT