Overview
Designed and developed an interactive Looker Studio website analytics report for the Public Information Office (PIO) using Google Analytics 4 data.
The report was tailored to PIO’s reporting needs, transforming website analytics into clear, accessible visualizations that stakeholders could explore without working directly in GA4.
The project was also designed as a proof of concept for a broader self-service reporting model. The proposed next phase would have adapted the reporting approach for individual website sections, giving subject matter experts easier access to analytics about the content they manage and providing data to help inform content updates and website improvements.
The Challenge
Google Analytics provides extensive information about website performance, but the volume and complexity of the data can make it difficult for stakeholders to quickly find and interpret the information most relevant to them.
The goal was to determine what PIO wanted to know about the website and create a report that made those insights easier to access, understand, and use.
Key challenges included:
- Identifying website metrics most relevant to PIO
- Translating complex analytics data into clear visual reporting
- Making analytics accessible without requiring stakeholders to navigate GA4
- Organizing information so trends and patterns could be identified quickly
- Creating a scalable way to analyze performance by website section rather than manually grouping individual page URLs
- Exploring how analytics could support ongoing website content decisions
Approach
1. Stakeholder-Focused Reporting
Developed the Looker Studio report around PIO’s specific reporting needs, rather than simply reproducing all of the information available in Google Analytics.
Selected and organized relevant metrics, dimensions, filters, and visualizations to provide an at-a-glance view of website performance while allowing stakeholders to explore the data in greater detail.
The goal was to make analytics understandable and useful to stakeholders who did not need to work directly within GA4.
2. Interactive Data Visualization
Organized GA4 data into an interactive Looker Studio report that allowed users to explore website performance through visualizations and filtering rather than relying on static analytics summaries.
The report provided a centralized view of website data, making it easier to identify patterns, compare performance, and understand how visitors were interacting with website content.
3. Designing for Self-Service Analytics
Developed the report with a larger self-service analytics model in mind.
The proposed next phase was to adapt the reporting approach for individual sections of the website. Subject matter experts could then access analytics relevant to the content they manage whenever they wanted to review it, rather than relying solely on periodic or one-time analytics requests.
The intent was to give content owners additional information they could use to identify content that may need to be updated, pages that may not be performing as expected, and areas where content or usability improvements might be beneficial.
The broader section-level reporting model was proposed but was not ultimately implemented.
4. Creating Section-Level Analytics with Google Tag Manager
To support section-specific reporting, I created a custom content-grouping system in Google Tag Manager based on the website’s URL structure.
Using Page Path as the input, I built a RegEx Table variable that mapped URL patterns to major website sections, including Workers, Employers, Providers, Insurers, Representatives, Self-Insureds, TPA, and Forms.
This allowed pages to be automatically categorized by content area rather than requiring individual URLs to be identified and grouped manually.
Custom GTM RegEx Table using Page Path to categorize URLs into website content groups.
5. Connecting Content Groups to GA4
The content-group value created in GTM was passed into Google Analytics 4, where it could be used to analyze website activity by content area.
This made it possible to compare metrics across major sections of the website and established the analytics foundation needed for more targeted reporting.
Content groups collected in GA4 allow website performance to be analyzed by major content area.
The reporting flow connected the website’s URL structure to stakeholder-facing analytics:
Page Path → GTM RegEx Table → Content Group → GA4 → Looker Studio
This structure could then support filters or section-specific reports in Looker Studio, allowing analytics to be organized around the areas of the website most relevant to individual stakeholders.
Results
Completed an interactive PIO-focused Looker Studio report that transformed GA4 website data into more accessible, stakeholder-focused reporting.
The project:
- Centralized relevant website performance information in an interactive report
- Made analytics easier for non-technical stakeholders to access and understand
- Tailored reporting to PIO’s specific information needs
- Provided an interactive way to explore website trends and performance
- Created a custom content-grouping system for analyzing major website sections
- Successfully passed content-group classifications from GTM into GA4
- Established the technical foundation for section-specific analytics
- Demonstrated a potential model for broader self-service reporting
The broader rollout to individual website sections was not implemented, but the completed PIO report and content-grouping implementation demonstrated how stakeholder-specific analytics could support a more data-informed approach to website content management.
My Role
Lead contributor for the design, development, and implementation of the Looker Studio report and supporting analytics configuration.
Key responsibilities included:
- Identifying and translating stakeholder reporting needs
- Designing and building the PIO Looker Studio report
- Selecting and organizing relevant GA4 metrics and dimensions
- Creating interactive data visualizations and filters
- Analyzing website traffic and performance data
- Developing the concept for section-specific stakeholder reporting
- Creating a GTM RegEx Table variable to categorize pages based on URL patterns
- Passing custom content-group values into GA4
- Validating content-group data within GA4
- Incorporating content groups into the reporting approach for section-specific analysis
Tools & Technologies
- Looker Studio
- Google Analytics 4 (GA4)
- Google Tag Manager (GTM)
- RegEx / URL pattern matching
Key Takeaways
- Effective analytics reporting begins with understanding what stakeholders need to know, rather than simply presenting all available data.
- Interactive visualization can make complex website analytics more accessible to non-technical audiences.
- Analytics can provide content owners with useful information for evaluating and maintaining website content.
- Custom content grouping can transform page-level analytics into more meaningful section-level reporting.
- Connecting data collection, analysis, and visualization creates a stronger foundation for using website analytics to inform content decisions.