Ashiqur Rahman

Selected work

See how tracking problems become decision-ready data.

Examples of measurement architecture, implementation, and diagnosis across the complete path from customer action to analytics and advertising platforms.

Explore the details
01

Measurement design

GA4 and GTM tracking architecture

Context

A reporting setup had inconsistent event names, missing dimensions, and noisy automatic events that made funnels difficult to interpret.

Approach
  • Mapped meaningful user actions to a shared event taxonomy
  • Defined a purpose-built data layer and required parameters
  • Configured and validated GA4 events through GTM
Outcome

A consistent event model with duplicate signals removed and critical funnel steps validated.

  • GA4
  • Google Tag Manager
  • Data Layer
  • JavaScript
02

Cloud infrastructure

First-party server-side tracking

Context

Browser restrictions, blocking, and third-party routing weakened important conversion signals and reduced control over outgoing data.

Approach
  • Configured a server-side GTM container on a first-party endpoint
  • Routed GA4 and advertising events through controlled clients and tags
  • Tested payload transformations, consent, and platform delivery
Outcome

A more resilient collection path with one controlled point for validation and multi-platform routing.

  • Server-Side GTM
  • Meta CAPI
  • Cloud Run
  • Stape
03

Audit and repair

Conversion tracking diagnosis

Context

Ad-platform conversions did not align with backend sales, while transaction totals showed signs of repeated firing.

Approach
  • Reproduced the checkout journey and inspected every request
  • Verified transaction IDs, deduplication, and consent behavior
  • Compared platform configuration with backend outcomes
Outcome

Duplicate transaction triggers were isolated, removed, and retested against the intended attribution path.

  • GTM Preview
  • GA4 DebugView
  • Network Inspection
  • Looker Studio

What is documented

The work stays useful after handoff.

A reliable setup should not depend on one person's memory. Clear evidence helps your team understand what changed, why it changed, how it was verified, and what to watch next.

  • Event and parameter definitions
  • Source and destination ownership
  • Test journeys and expected results
  • Debug and network evidence
  • Known platform differences
  • Maintenance and handoff notes

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