How does the skill handle data quality?

The pipeline includes automated quality checks for completeness, consistency (cross-platform variance), data freshness, and statistical anomalies using z-score thresholds.

Which platforms does the Data Pipeline skill support?

It supports a wide range of platforms including Google Ads, Meta Ads, LinkedIn Ads, GA4, Mixpanel, Mailchimp, HubSpot, and major social media networks.

How do I schedule data refreshes?

The skill includes a pipeline configuration that allows you to set cron-based schedules for full refreshes or specific daily reports.

What attribution models are available?

It supports multiple models including Last Click, First Click, Linear, Time Decay, Position-Based (40-20-40), and custom Data-Driven models.

Can it calculate custom marketing metrics?

Yes, the skill automatically calculates derived metrics like CTR, CPA, CPC, and ROAS using standardized formulas applied to your raw platform data.

Marketing Data Pipeline

Name: Marketing Data Pipeline
Author: jmagly

byjmagly

•

Marketing Automation

Orchestrates end-to-end marketing data collection, transformation, and multi-channel reporting workflows.

About

The Marketing Data Pipeline skill transforms Claude into an automated data engineer capable of managing complex marketing analytics workflows. It streamlines the process of extracting metrics from diverse platforms—including Google Ads, Meta, GA4, and HubSpot—while automating transformations such as metric normalization and attribution modeling. By handling technical hurdles like API pagination, rate limits, and anomaly detection, this skill provides a reliable, automated source of truth for cross-channel performance, enabling teams to spend less time on manual data cleaning and more time on strategic optimization.

Key Features

Configurable attribution modeling including linear and data-driven methods
Automated metric calculation for ROI, ROAS, CPA, and CTR
Automated reporting in JSON, CSV, and Markdown formats
Multi-platform data extraction (Ads, Analytics, Email, and Social)
Built-in data quality validation and anomaly detection
67 GitHub stars

Use Cases

Consolidating cross-channel ad spend and conversion data into a unified dashboard
Automating the generation of weekly executive performance and attribution reports
Monitoring marketing campaigns for performance anomalies and budget spikes

About

Key Features

Configurable attribution modeling including linear and data-driven methods
Automated metric calculation for ROI, ROAS, CPA, and CTR
Automated reporting in JSON, CSV, and Markdown formats
Multi-platform data extraction (Ads, Analytics, Email, and Social)
Built-in data quality validation and anomaly detection
67 GitHub stars

Use Cases

Consolidating cross-channel ad spend and conversion data into a unified dashboard
Automating the generation of weekly executive performance and attribution reports
Monitoring marketing campaigns for performance anomalies and budget spikes