This case study highlights my expertise in designing, implementing, and maintaining a centralized tracking infrastructure using Google Tag Manager (GTM) across multiple ecommerce brands.
I built and managed a clean, scalable tagging system that ensured accurate data collection, reliable attribution, and platform stability across all major marketing and analytics platforms.
Data Sources & Platforms Integrated
All tracking was implemented and managed centrally via Google Tag Manager, including:
Google Analytics 4 (GA4)
Event-based ecommerce tracking for user behavior and funnel analysis
Google Ads Conversion Tracking
Accurate purchase and key funnel event measurement for bidding optimization
Meta Ads Pixel
Standard and custom events for full-funnel optimization and attribution
Google Search Console (GSC)
Organic performance insights aligned with analytics and landing pages
Each integration was structured to ensure data consistency, correct event mapping, and minimal discrepancies across platforms.
My Technical Responsibilities
Data-First GTM Architecture
Designed a clean, centralized GTM structure
Applied clear naming conventions for tags, triggers, and variables
Built a scalable setup that supports future growth without rework
Conversion & Event Mapping
Implemented standard and custom ecommerce events
Ensured proper alignment between GA4, Google Ads, and Meta Ads events
Verified event firing, deduplication, and parameter accuracy
Debugging & Data Validation
Tested all integrations using GTM preview, GA4 debug view, and platform diagnostics
Resolved issues such as:
Missing conversions
Duplicate event firing
Incorrect triggers or parameters
Ensured stable tracking during website updates and campaign scaling
Attribution & Optimization Readiness
Ensured tracking accuracy before scaling budgets
Enabled confident ROAS, CPA, and funnel analysis
Built a reliable data layer that supports performance optimization and SEO insights
Strategic Philosophy
My approach is simple:
No optimization without accurate data.
I prioritize:
Clean data over assumptions
Stability over quick fixes
Long-term scalability over temporary workarounds
This ensures performance decisions are made with confidence and clarity, not guesswork.
Impact & Outcomes
Created a reliable data foundation for performance marketing
Reduced discrepancies between analytics and ad platforms
Improved optimization efficiency through accurate conversion signals
Enabled scalable growth backed by trustworthy data