Analytics systems that actually get used.

I help product and marketing teams design, implement, and debug analytics setups so their dashboards tell the truth instead of starting arguments.

  • Adobe Experience Platform, GA4, and server-side tracking implementations that don't crumble under real-world traffic and consent rules.
  • Clean, consistent events and properties across products and platforms.
  • Dashboards and reports people actually open more than once.
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Connected teams
Pharma industry
Diagnostics industry
E-commerce industry
B2B SaaS industry
HealthTech industry
Retail industry

Client names protected for confidentiality. Industries shown represent project experience.

Services

🏗️

Adobe Experience Platform

AEPWeb SDKAppMeasurementLaunch
  • Design unified event schemas across products, markets, and platforms.
  • Implement data collection using Web SDK or AppMeasurement with Adobe Launch.
  • Build pipelines into AEP, Real-Time CDP, and downstream destinations.
See example project
📡

GA4 & Server-side Tracking

GA4GTMServer-side
  • Harden GA4 setups against consent changes, ITP, and ad blockers.
  • Implement server-side tracking with clear ownership and error handling.
  • Debug existing setups without breaking production or losing historical data.
See example project
🗄️

Marketing Data Warehousing

BigQueryGCPETLdbt
  • Build marketing data warehouses on BigQuery for unified cross-channel reporting.
  • Integrate GA4, CRM, ad platforms, and marketing tools into a single source of truth.
  • Design data models that connect customer journeys across touchpoints.
See example project
🔍

Analytics Audits & Rescue

AuditTroubleshooting
  • Audit your current tracking, data flow, and reporting layers.
  • Identify gaps, duplication, and reliability issues.
  • Deliver a prioritized roadmap focused on decisions, not vanity fixes.
See example project
🤖

Agentic AI Workflows

LLMAdobe APIsAutomation
  • Auto-generate tracking documentation from Adobe Analytics and Reactor APIs.
  • Build Knowledge Graph structures for LLM-powered implementation discussions.
  • Reduce documentation maintenance to one-click updates with AI agents.
See example project
🤝

Fractional Analytics Partner

Long-termAdvisory
  • Join your team as a part-time analytics engineer / architect.
  • Support product, marketing, and data teams across planning and execution.
  • Own analytics questions so your team can ship faster with fewer data debates.
See example project

Project Process

01

Discovery

  • Understand your business goals and what decisions need data support.
  • Review your current stack, data flows, and pain points.
  • Identify gaps, risks, and quick wins.
02

Design

  • Define a unified event schema for all required user actions.
  • Design architecture for your stack (AEP, GA4, BigQuery).
  • Create tracking specs and implementation plans your team can follow.
03

Implementation

  • Build dataLayer events, tag configurations, and integrations.
  • Set up ETL pipelines and data destinations.
  • Implement server-side tracking where needed for reliability.
04

Testing

  • Validate event firing and data accuracy across browsers and devices.
  • QA against tracking specs and debug discrepancies.
  • Verify data flows end-to-end from source to reporting.
05

Documentation

  • Deliver tracking documentation and event dictionaries.
  • Record handover videos and knowledge transfer sessions.
  • Provide maintenance guides so your team owns the setup.

Selected Work

Diagnostics & Healthcare, EU

Context

Multiple products and instruments, each with its own tracking logic, no unified view of customer behavior.

What we did

  • Designed a unified event schema across instruments and applications.
  • Implemented tracking changes and data flows into AEP and GA4.
  • Documented key events, properties, and dashboards.

Outcome

Reporting time for critical KPIs dropped from days of manual work to hours, with improved trust in the numbers.

E-commerce Scale-up

Context

Inconsistent GA4 setup across regions, broken funnels, and unstable attribution.

What we did

  • Rebuilt the tracking plan and standardized events across markets.
  • Implemented consent-aware client- and server-side tracking.
  • Set up monitoring to catch future implementation drift.

Outcome

Stable funnels and clear attribution, enabling confident experimentation and campaign decisions.

B2B SaaS Product Team

Context

Product analytics scattered across tools, no single narrative of user journeys.

What we did

  • Consolidated tracking into a coherent schema.
  • Integrated product analytics and marketing tools with a shared event language.
  • Defined a core set of product metrics aligned with the roadmap.

Outcome

Product and marketing teams now speak the same language and base decisions on shared dashboards.

About

👤
  • Digital analytics engineer and solution architect based in Wrocław, Poland.
  • 6+ years implementing analytics for healthcare, diagnostics, and e‑commerce teams.
  • Specialized in Adobe Experience Platform, GA4, server-side tracking, and data integration.
  • Comfortable working directly with product, marketing, and engineering teams.

I like solving messy, real-world analytics problems where tools, consent, and timelines don't always behave nicely. If you care more about reliable decisions than fancy dashboards, we will get along well.

AEP GA4 GTM Server-side BigQuery Python TypeScript

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