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analytics-tracking

Audit and improve analytics tracking implementations for GA4 and Google Tag Manager.

Updated Feb 21, 2026
Search Tags:#analytics#utm#gtm#event-tracking#ga4#data-layer#tracking-plan
One-click install
npx skills add https://github.com/lofty-thoughts/botdaddy --skill analytics-tracking-lofty-thoughts
Or copy as Structured Prompt for Agentâ–¼
Please help me install this Agent Skill.
Skill: analytics-tracking
Source: https://github.com/lofty-thoughts/botdaddy/tree/main/seed/skills/analytics-tracking
Command: npx skills add https://github.com/lofty-thoughts/botdaddy --skill analytics-tracking-lofty-thoughts

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Helps teams set up, audit, and improve analytics tracking so product and marketing decisions are based on reliable events and conversions rather than guesswork or inconsistent metrics.

Core Features & Use Cases

  • Initial assessment: Evaluate business goals, existing tracking, and technical constraints to design a measurement approach.
  • Tracking plan & naming: Create event libraries, consistent object-action naming conventions, and property schemas to avoid ambiguity.
  • Implementations & tools: Guidance for GA4, Google Tag Manager, dataLayer patterns, UTM strategy, and custom event instrumentation.
  • Validation & privacy: Debugging checklists, DebugView/GTM preview steps, and privacy/compliance recommendations (consent mode, IP anonymization).
  • Use case: Build a tracking plan that captures signup conversions, CTA engagement, and campaign attribution for a marketing site and validate it in GA4/GTM before marking conversions.

Quick Start

Create a GA4 + GTM tracking plan for my marketing site that captures signup_completed, cta_clicked, key pageviews, and UTM sources and includes a validation checklist.

Frequently Asked Questions about analytics-tracking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a GA4 tracking plan with consistent event naming and dataLayer patterns?â–¼

A GA4 tracking plan defines consistent object-action event naming conventions and dataLayer schemas to capture key pageviews, conversions, and campaign attribution without ambiguity. It aligns business goals with property schemas for reliable product and marketing analytics.

What is the best way to validate event tracking in Google Tag Manager before marking conversions?â–¼

Validating event tracking in Google Tag Manager involves using GTM preview mode and GA4 DebugView to run debugging checklists. This ensures your dataLayer pushes and conversion configurations fire correctly before you mark events as conversions for decision-making.

How do I set up UTM strategy and conversion tracking for a marketing site?â–¼

Setting up UTM strategy and conversion tracking requires defining a measurement approach that captures signup conversions, CTA engagement, and campaign attribution. You configure custom event instrumentation and UTM parameters to produce consistent conversion data for marketing decisions.

Can I use this analytics tracking approach with Mixpanel and Amplitude instead of GA4?â–¼

Yes, this analytics tracking approach applies to Mixpanel, Amplitude, and similar tooling. It guides event library creation, consistent naming conventions, and custom event instrumentation across web and mobile properties to ensure consistent event and conversion data.

Does Google Tag Manager support privacy-compliant data collection with consent mode?â–¼

Yes, Google Tag Manager supports privacy-compliant data collection through consent mode and IP anonymization configurations. These features are integrated into tracking implementations to ensure your event and conversion data collection meets privacy and compliance regulations.

Why does my GA4 event tracking show inconsistent data and missed conversions?â–¼

Inconsistent GA4 event tracking and missed conversions usually stem from a lack of a standardized tracking plan, ambiguous event naming, or incorrect dataLayer design. Auditing your implementation against a consistent object-action naming convention resolves these data discrepancies.

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