Analytics Tracking Setup

Accurate analytics tracking is the backbone of data-driven decisions, but bad setups lead to missing, duplicate, or misleading data. With this skill, your AI can build, audit, or debug your analytics implementation—covering GA4, Google Tag Manager, event naming, conversion tracking, and data quality. It’s perfect for growth leads, product managers, marketers, and engineers who want reliable event data without the usual headaches.

What you can do

• Generate a complete tracking plan with event taxonomy and parameter definitions for your funnel.
• Audit your existing GA4 or GTM setup for gaps, errors, or broken events.
• Debug issues like missing conversions, events firing in GTM but not showing in GA4, or UTM tracking problems.
• Design a consistent event naming convention and parameter schema for new features or campaigns.
• Build a checklist for cross-domain tracking, server-side tagging, or GDPR compliance.

How it works

Your AI starts by gathering context: your stack, current analytics, goals, and business priorities. For new setups, it generates a tracking plan using a Python script, defining every event and parameter you’ll need. For audits, it reviews your current implementation, identifies gaps, and recommends fixes. For debugging, it walks through a structured workflow to pinpoint where data is breaking down—from GTM triggers to GA4 event logs. Outputs include human-readable plans, audit reports, and JSON for pipeline use.

Good to know

• You’ll need access to your GA4 and GTM accounts for a full audit or implementation.
• Python 3 is required to run the tracking plan generator script locally.
• This skill focuses on tracking setup and troubleshooting—not on campaign analytics or BI dashboards.