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Fixing $88K in Misattributed Revenue with Server-Side Tracking
Analytics & Attribution

Fixing $88K in Misattributed Revenue with Server-Side Tracking

Implemented server-side tracking to solve critical attribution issues across multiple platforms.

Project Overview

While managing performance marketing for a fast-scaling eCommerce client, we faced critical attribution issues across Shopify, Meta Ads, Google Ads, Pinterest, and GA4. Conversion data was inflated, misaligned, and misleading — causing wasted spend and poor optimization decisions.

I led the architecture and deployment of a server-side tracking framework to fix attribution blind spots and bring data clarity across platforms. The project involved deep collaboration with developers to implement a GTM server container using Stape, pushing clean, deduplicated events to GA4, Meta, and Google Ads.

The implementation required careful event mapping and QA, syncing event schema with Shopify's backend, and validating server hits against browser hits. We also built a multi-platform Tableau dashboard to compare platform data against Shopify actuals, enabling LTV-based optimization and smarter CAC targeting.

Challenges

Double Counting Across Platforms: Meta and Google both over-reported sales vs. Shopify actuals
Broken Attribution Logic: GA4 last-click model clashed with ad platform reporting
Scaling Without Signal Loss: Browser-side limitations (ITP, blockers) led to massive data drop-offs
Zero Confidence in Real CAC, LTV, or Retargeting ROI

Solutions

Led Server-Side Tracking Rollout:

Designed and implemented a GTM server container using Stape, pushing clean, deduplicated events to GA4, Meta, and Google Ads.

Event Mapping & QA:

Synced event schema with Shopify's backend, verified via Tag Assistant and GA Debugger, and validated server hits vs. browser hits.

Attribution Realignment:

Built a multi-platform Tableau dashboard to compare platform data vs. Shopify actuals — enabling LTV-based optimization and smarter CAC targeting.

Team Collaboration:

Worked directly with developers for backend integration and marketing leads to realign budget strategy post-tracking upgrade.

Results

  • Reduced attribution error margin from ~28% to under 5%
  • Improved ROAS accuracy — adjusted from inflated 7.2x to true 4.5x
  • Identified Meta Ads as the strongest-performing channel, leading to reallocation of 18% budget from low-ROI Pinterest campaigns
  • Enabled real CAC, LTV, churn visibility, powering smarter scaling decisions
  • Delivered in 4 weeks from diagnosis to full deployment + reporting

Technologies & Tools Used

ShopifyMeta AdsGoogle AdsGA4Pinterest AdsGoogle Tag Manager (Server-Side)StapeTableauGA DebuggerTag Assistant

Project Gallery

Client-Side vs Server-Side Tracking Architecture

Client-Side vs Server-Side Tracking Architecture

Google Tag Manager Server-Side Implementation Flow

Google Tag Manager Server-Side Implementation Flow

Conversion Tracking Accuracy Before & After Fix

Conversion Tracking Accuracy Before & After Fix

LTV to CAC Ratio Dashboard

LTV to CAC Ratio Dashboard

Customer LTV vs CAC Over Time

Customer LTV vs CAC Over Time

Project Details

Client

Fast-Scaling eCommerce Brand

Timeline

4 weeks (Q1 2023)

Role

Analytics & Attribution Architect

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