My Work & Focus Areas

Deep-dive into my core competencies and approach

My work centers around turning digital noise into actionable intelligence. I specialize in six core areas that work together to create comprehensive, privacy-first measurement and optimization systems.

🎯 Matomo Analytics & Tagging

Privacy-first analytics that actually drive decisions

Why Matomo?

While the industry scrambles with privacy regulations and platform changes, Matomo offers stability, control, and respect for user privacy. I've guided dozens of organizations through successful migrations from Universal Analytics and GA4 to Matomo, often improving their data quality and reducing compliance headaches simultaneously.

My Matomo Approach

Clean Event Architecture

I design event taxonomies that are both comprehensive and maintainable. No more "misc_click_button_maybe" events — every interaction is purposefully categorized and documented.

Tag Manager Implementation

Matomo Tag Manager isn't as mature as GTM, but it's powerful enough for most use cases and keeps your data on your servers. I build tag architectures that are easy to maintain and extend.

Custom Dimensions Strategy

Matomo's custom dimensions are incredibly flexible. I help organizations design dimension schemas that capture business-specific context without creating analysis paralysis.

API Integration

Matomo's APIs are robust and well-documented. I build custom dashboards, automated reports, and data exports that integrate seamlessly with existing business systems.

Migration & Data Quality

Moving from GA4 to Matomo isn't just a platform switch — it's an opportunity to clean up years of accumulated tracking debt. I help organizations:

  • Audit existing tracking to identify what's actually being used vs. collected
  • Redesign event structures that align with current business questions
  • Implement data validation to catch tracking issues before they corrupt reports
  • Create historical data bridges to maintain year-over-year comparisons
  • Train teams on new interfaces and capabilities

Consent & Privacy Integration

Matomo's privacy features aren't just compliance checkboxes — they're designed to provide meaningful insights while respecting user choices. I implement consent management that:

  • Gracefully handles users who opt out without breaking analytics
  • Provides valuable insights from first-party data even with limited tracking
  • Balances user privacy with business intelligence needs
  • Meets GDPR, CCPA, and other privacy regulations

🔍 SEO, AEO & GEO

Optimizing for how people actually search today

Beyond Traditional SEO

Search has fundamentally changed. AI overviews, voice search, and answer engines mean that traditional keyword optimization is just the baseline. My approach focuses on three interconnected areas:

🔍 Traditional SEO

The fundamentals still matter: technical optimization, content structure, internal linking, and page speed. But these are table stakes, not differentiators.

💡 Answer Engine Optimization (AEO)

Optimizing for featured snippets, "People Also Ask" boxes, and direct answer formats that search engines increasingly favor.

🤖 Generative Engine Optimization (GEO)

Preparing content for AI-powered search tools like Perplexity, ChatGPT search, and Google's AI overviews.

Structured Data Mastery

Schema.org markup isn't optional anymore — it's how search engines understand your content. I implement comprehensive structured data strategies that include:

  • Entity optimization — helping search engines understand what your business actually does
  • Content relationships — connecting related pieces of content through proper markup
  • Rich results targeting — optimizing for specific SERP features relevant to your industry
  • Knowledge graph integration — building entity authority that helps with broader search visibility

Technical SEO Infrastructure

Modern SEO requires solid technical foundations. I audit and optimize:

Performance Optimization

Core Web Vitals aren't just ranking factors — they impact user experience and conversion rates. I optimize for real-world performance, not just test scores.

Crawl Budget Optimization

Large sites need smart crawl management. I help search engines find and index your most important content efficiently.

International SEO

Proper hreflang implementation, content localization strategies, and technical infrastructure for multi-language sites.

Mobile-First Optimization

Going beyond responsive design to create mobile experiences that search engines and users love.

Content Strategy for AI Search

AI-powered search tools evaluate content differently than traditional search engines. I help organizations adapt their content strategy to perform well in this new landscape:

  • Comprehensive coverage — creating content that answers the full spectrum of user questions
  • Authoritative sourcing — building content that AI tools want to cite and reference
  • Clear information hierarchy — structuring content so AI can extract key information accurately
  • Context building — connecting individual pieces of content into comprehensive topic coverage

🔬 Experimentation & Optimization

Rigorous testing that drives real business impact

The Experimentation Problem

Most A/B testing is broken. Teams run tests without proper statistical foundations, declare victory on insignificant results, and optimize for metrics that don't drive business outcomes. I help build experimentation programs that actually work.

My Testing Philosophy

📊 Statistical Rigor First

Every test starts with proper power analysis, meaningful effect size calculations, and clear success criteria. No "let's see what happens" experiments.

🎯 Business Impact Focus

Optimizing click-through rates is useless if it doesn't improve revenue or user satisfaction. I help teams identify metrics that actually matter to business outcomes.

⚖️ Guardrail Metrics

Every test includes guardrail metrics to ensure improvements in primary metrics don't come at the cost of overall user experience or long-term value.

🔄 Learning Over Winning

Failed tests that generate clear insights are more valuable than winning tests that don't teach us anything. I design experiments that generate learning regardless of outcome.

Platform Expertise

I'm certified in both Optimizely and VWO, but more importantly, I understand when to use each platform and when to build custom solutions:

Optimizely Ecosystem

  • Web Experiments — Complex multivariate tests and sophisticated targeting
  • Feature Flags — Safe feature rollouts and gradual deployments
  • ODP (Optimizely Data Platform) — Customer data unification and segmentation
  • CMS Integration — Content experiments within Optimizely CMS

VWO & Other Platforms

  • VWO Testing — Cost-effective solution for straightforward A/B tests
  • Server-side Testing — Backend experiments that don't rely on client-side JavaScript
  • Custom Solutions — Building bespoke testing infrastructure when platforms don't fit

Experiment Design & Methodology

Great experiments start with great hypotheses. I help teams move beyond "what if we make this button blue?" to structured hypothesis formation:

1. Problem Identification

Using data to identify real user friction points, not just personal opinions about what needs fixing.

2. Hypothesis Formation

Creating testable hypotheses that include specific, measurable predictions about user behavior changes.

3. Test Design

Designing experiments that isolate variables, minimize external factors, and generate clear insights.

4. Statistical Planning

Calculating required sample sizes, experiment duration, and success criteria before launch.

5. Implementation & QA

Ensuring experiments run correctly across all user segments and device types.

6. Analysis & Learning

Going beyond "winner" or "loser" to extract actionable insights for future optimization.

Building Experimentation Culture

Technology is the easy part — the hard part is building organizational capabilities for continuous experimentation. I help teams:

  • Create experiment backlogs that prioritize high-impact, high-learning opportunities
  • Establish review processes that maintain statistical rigor without slowing down iteration
  • Build internal expertise so teams can run experiments independently
  • Document learnings in ways that inform future experiments and broader strategy

⚙️ Data Ops & Engineering

Reliable data infrastructure that scales with your business

Beyond Analytics Implementation

Great analytics requires great data infrastructure. I build systems that collect, process, and deliver data reliably — because insights are only valuable if you can trust the data behind them.

Data Pipeline Architecture

I design and implement data pipelines that handle the complexity of modern digital ecosystems:

📥 Data Collection

  • Client-side tracking with proper error handling
  • Server-side event collection for critical business metrics
  • API integrations with business systems (CRM, email, e-commerce)
  • Data validation and quality checks at collection time

🔄 Data Processing

  • ETL pipelines that transform raw data into analysis-ready formats
  • Data enrichment with external sources (weather, demographics, market data)
  • Automated data quality monitoring and alerting
  • Historical data backfilling and correction processes

📊 Data Delivery

  • Custom dashboards that answer specific business questions
  • Automated report generation and distribution
  • API endpoints for real-time data access
  • Data exports for machine learning and advanced analytics

Technology Stack

I choose technologies based on reliability, maintainability, and cost-effectiveness, not resume-building:

Data Warehousing

BigQuery for most use cases — it's cost-effective, scales automatically, and integrates well with analytics tools. I also work with PostgreSQL for smaller datasets and Snowflake for enterprise requirements.

Data Processing

Python for most data transformation work, with pandas for data manipulation and Apache Airflow for complex workflow orchestration. Simple pipelines might just use BigQuery SQL.

Visualization

Looker Studio for most business reporting needs, with custom solutions for specialized use cases. I focus on dashboards that drive action, not just display data.

Infrastructure

Docker for consistent deployment environments, with GitHub Actions for CI/CD. I prefer managed services over custom infrastructure when possible.

Monitoring & Reliability

Data systems fail in creative ways. I build monitoring that catches problems before they impact business decisions:

  • Data freshness monitoring — alerting when expected data doesn't arrive on schedule
  • Volume anomaly detection — catching tracking issues that cause dramatic increases or decreases in data volume
  • Data quality validation — automated checks for data completeness, accuracy, and consistency
  • Performance monitoring — ensuring dashboards and reports load quickly and reliably
  • Cost monitoring — preventing surprise cloud bills from runaway queries or inefficient processes

Documentation & Knowledge Transfer

The best data system is useless if your team can't maintain it. I create comprehensive documentation that includes:

  • Data dictionaries that explain what each metric actually measures
  • Architecture diagrams showing how data flows through your systems
  • Runbooks for common maintenance and troubleshooting tasks
  • Training materials for team members who need to extend or modify systems

💻 Web Engineering & Performance

Technical implementations that are fast, reliable, and maintainable

The Engineering Mindset

I'm not a full-stack developer, but I write enough code to be dangerous — and more importantly, to understand the constraints and possibilities of web development. My engineering work focuses on analytics implementation, performance optimization, and automation.

Custom Tracking Solutions

Sometimes standard analytics tools aren't enough. I build custom tracking solutions for complex use cases:

🎯 Event Tracking Libraries

Custom JavaScript libraries that standardize event collection across multiple properties, handle offline scenarios, and provide better error handling than standard implementations.

🔄 Server-Side Tracking

Backend implementations that capture critical business events without relying on client-side JavaScript, essential for accurate conversion tracking in privacy-focused environments.

📱 Cross-Platform Analytics

Solutions that provide consistent event tracking across web, mobile apps, and backend systems, enabling true cross-platform user journey analysis.

Performance Optimization

Analytics and performance often conflict — tracking scripts can slow down websites significantly. I implement solutions that prioritize user experience:

  • Async loading strategies that ensure analytics never block page rendering
  • Script optimization that minimizes the performance impact of tracking code
  • Local storage management that reduces redundant API calls and improves responsiveness
  • CDN optimization for serving analytics assets quickly across global audiences
  • Bundle analysis to identify and eliminate unnecessary tracking dependencies

Automation & Tooling

I build tools that eliminate repetitive tasks and reduce the chance of human error:

🤖 Report Generation

Python scripts that automatically generate and distribute regular reports, pulling data from multiple sources and formatting it for specific stakeholder needs.

✅ Quality Assurance

Automated testing tools that verify tracking implementations work correctly across different browsers, devices, and user scenarios.

📋 Data Validation

Scripts that continuously monitor data quality, alert when anomalies occur, and provide suggested fixes for common issues.

🚀 Deployment Tools

CI/CD pipelines that safely deploy analytics changes, with rollback capabilities and automated testing.

Modern Development Practices

I apply software engineering best practices to analytics implementations:

  • Version control for all analytics configurations and custom code
  • Code review processes that catch errors before they reach production
  • Testing environments for validating changes before deployment
  • Documentation as code that stays up-to-date with implementation changes
  • Error handling that gracefully handles edge cases and network issues

AI-Augmented Development

I leverage AI tools to accelerate development and improve code quality:

  • Claude Code for complex problem-solving and code architecture decisions
  • GitHub Copilot for faster implementation of standard patterns
  • ChatGPT for debugging assistance and documentation generation
  • OpenAI Codex for automated code generation from natural language specifications

🔒 Privacy & Compliance

Ethical data practices that build trust and drive results

Privacy as a Competitive Advantage

Most organizations view privacy compliance as a cost center or legal requirement. I help them understand that privacy-first approaches can actually improve data quality and user trust, leading to better business outcomes.

Comprehensive Privacy Strategy

Effective privacy compliance goes far beyond cookie banners and privacy policies:

🎯 Data Minimization

Collecting only the data you actually need for specific business purposes. This reduces compliance burden, improves performance, and often leads to cleaner insights.

✅ Consent Management

Implementing consent systems that respect user choices while maintaining analytics effectiveness. This includes graceful degradation when users opt out.

🔄 First-Party Data Strategy

Building systems that rely on directly collected data rather than third-party tracking, improving both privacy and data quality.

🛡️ Security by Design

Implementing data handling practices that protect user information throughout collection, processing, and storage.

Regulation Compliance

I help organizations navigate the complex landscape of privacy regulations:

GDPR (General Data Protection Regulation)

  • Lawful basis identification for all data processing
  • Data subject rights implementation (access, portability, deletion)
  • Privacy by design and by default principles
  • Data Protection Impact Assessments (DPIAs)

CCPA/CPRA (California Consumer Privacy Act)

  • Consumer disclosure requirements
  • Opt-out mechanisms for data sale and sharing
  • Sensitive personal information handling
  • Third-party data sharing agreements

ePrivacy Directive

  • Cookie consent management
  • Electronic communications privacy
  • Direct marketing consent requirements
  • Website visitor information requirements

Cookieless Analytics Solutions

The death of third-party cookies isn't a crisis — it's an opportunity to build better measurement systems:

  • Server-side tracking that doesn't rely on client-side cookies
  • First-party identifier strategies that respect user privacy while enabling attribution
  • Cohort-based analytics that provide insights without individual user tracking
  • Privacy-preserving attribution models that work within platform limitations
  • Contextual targeting strategies that don't require behavioral profiling

Building Trust Through Transparency

Privacy compliance isn't just about meeting legal minimums — it's about building user trust that drives long-term business value:

Clear Communication

Privacy policies and cookie banners that actually explain what data you collect and why, written in plain language that users can understand.

Granular Controls

Consent interfaces that let users make informed choices about different types of data collection, rather than all-or-nothing approaches.

Data Value Exchange

Clearly articulating the value users receive in exchange for their data, whether that's personalized experiences, better products, or other benefits.

Ongoing Transparency

Regular communication about how data is being used, what insights are being generated, and how this benefits users.

Implementation Best Practices

Privacy-compliant analytics requires careful technical implementation:

  • Data governance frameworks that define roles, responsibilities, and approval processes
  • Automated compliance monitoring that detects potential privacy violations
  • Regular privacy audits of data collection and processing practices
  • Incident response procedures for handling data breaches or compliance issues
  • Staff training programs that ensure everyone understands privacy requirements

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