Google Analytics: A Complete Guide
You’re under pressure. Stakeholders demand insights, but your reports lack clarity. You're spending hours pulling data that still doesn’t answer the real questions. You know Google Analytics holds answers-but you’re stuck in a maze of settings, metrics, and misconfigured tracking. Meanwhile, others are moving faster. Digital teams in top companies are uncovering growth levers, optimising funnels, and proving ROI with precision. They speak the language of data fluency-and you’re left wondering how to catch up without wasting time on outdated tutorials or fragmented guides. What if you could go from overwhelmed to in control-confidently interpreting user behaviour, identifying revenue opportunities, and delivering insights that get attention at the leadership level? The Google Analytics: A Complete Guide is your blueprint for doing exactly that. By the end of this course, you'll go from uncertain analyst to trusted data strategist-equipped to build a fully implemented, audit-ready analytics framework in under 30 days. You’ll produce documentation, reports, and dashboards that are board-ready, technically sound, and aligned to business KPIs. Sarah L., a marketing operations lead at a SaaS scale-up, used this exact framework to identify a 37% drop-off in their trial sign-up flow. Within two weeks, she presented findings that led to a redesign-boosting conversions by 22% and saving $180K in lost pipeline annually. No fluff. No theory without application. This is the system trusted professionals use to turn data chaos into strategic clarity. Here’s how this course is structured to help you get there.Course Format & Delivery: Learn On Your Terms Designed for high-impact professionals who value precision, speed, and outcomes, Google Analytics: A Complete Guide is fully self-paced, with immediate online access upon enrollment. You control when, where, and how quickly you progress-ideal for analysts, marketers, product managers, and consultants balancing real-world demands. Learn Anytime, Anywhere, on Any Device
Access the course 24/7 from desktop, tablet, or mobile. The content is built for seamless readability and interaction across all devices, ensuring you can learn during commutes, between meetings, or from your home office-without disruption. - Self-paced with no deadlines or cohort schedules
- Immediate online access after enrollment
- Lifetime access-return anytime for refresher insights or updated materials
- Ongoing curriculum updates at no extra cost, reflecting Google’s latest documentation and platform changes
From First Login to First Insight: Fast, Focused, Actionable
Most learners complete the core implementation framework in 12–18 hours and begin applying insights within the first week. Foundational modules can be finished in a single afternoon, giving you the tools to clean up tracking, define conversions, and generate meaningful reports immediately. Build momentum fast. See tangible results before you’ve even finished the course. Real Instructor Guidance, Not Just Content
This is not a passive learning experience. You receive direct, expert-level support throughout your journey. Submit questions through the learning portal and receive timely, detailed responses from certified analytics practitioners with over a decade of implementation experience across e-commerce, enterprise, and B2B environments. Earn a Globally Recognised Certificate of Completion
Upon finishing the course, you’ll receive a Certificate of Completion issued by The Art of Service-a credential trusted by professionals in over 120 countries. This certification verifies your mastery of Google Analytics configuration, analysis, and reporting, and is optimised for inclusion on LinkedIn, CVs, and internal promotion packages. The Art of Service has trained over 45,000 professionals in digital analytics, project governance, and data strategy. Our certifications are recognised by hiring managers at companies like Deloitte, Amazon, Shopify, and Atlassian. Transparent Pricing, No Hidden Fees
The listed price covers everything. No recurring charges, no add-ons, no surprise costs. You pay once and gain complete access to the entire curriculum, support, and certification. Secure checkout accepts major payment methods: Visa, Mastercard, and PayPal. Zero-Risk Enrollment: Satisfied or Refunded
We’re confident this course will exceed your expectations. That’s why we offer a comprehensive satisfaction guarantee. If you complete the first two modules and feel the course isn’t delivering measurable value, request a refund. No forms, no hoops, no hassle. This is your risk reversal. You don’t just get knowledge-you get safety, clarity, and full control. This Works Even If…
- You’ve never configured Google Analytics before
- You’ve used it for years but keep getting inconsistent data
- You’re not technical but need to speak authoritatively with developers
- Your current GA4 setup is incomplete or misaligned with business goals
- You work in a regulated industry with strict data compliance needs
Tiffany R., a non-profit digital director, had no prior analytics experience. After applying Module 3’s step-by-step tagging guide, she corrected tracking across 52 campaign URLs, increased donor conversion tracking accuracy by 94%, and secured additional funding based on data she could finally trust. After enrollment, you’ll receive a confirmation email. Once your course materials are prepared, you’ll receive a separate access notification with login details and onboarding instructions.
Module 1: Foundations of Google Analytics Mastery - Understanding the core purpose and business value of Google Analytics
- Differentiating between Universal Analytics and GA4: what changed and why it matters
- Mapping analytics to business objectives: revenue, engagement, retention
- The anatomy of a GA4 property: streams, data layers, and processing levels
- How Google Analytics fits into the modern marketing technology stack
- Privacy-first analytics: legal compliance and ethical data collection
- GDPR, CCPA, and ITP implications for tracking configuration
- Role-based access: setting up user permissions securely
- Creating your first GA4 property from scratch
- Linking Google Analytics to Google Ads, Search Console, and Tag Manager
- Verifying connectivity between platforms using diagnostics tools
- Setting up a development, staging, and production analytics environment
- Understanding data thresholds and sampling limitations in GA4
- The role of events, parameters, and user properties in event-driven architecture
- Default vs custom dimensions and metrics: when to use each
Module 2: Strategic Setup and Configuration - Conducting a stakeholder requirement workshop for analytics scope
- Defining core business conversions: macro and micro goals
- Creating a measurement strategy document for organisational alignment
- Configuring enhanced measurement: what to enable and what to disable
- Setting up event tracking without code: scroll, outbound clicks, downloads
- Custom event creation: naming conventions and best practices
- Configuring conversion events and prioritising value
- Setting up purchase revenue tracking for e-commerce
- Adding transaction parameters for product-level reporting
- Configuring user ID tracking for cross-device journey mapping
- Setting up custom dimensions for campaign, content, and user segmentation
- Implementing content grouping for site section analysis
- Configuring internal search tracking with custom parameters
- Setting up outbound link tracking with parameter persistence
- Configuring video engagement tracking (play, pause, complete)
- Adding form interaction tracking: start, progress, submission
- Setting up error page tracking for user experience optimisation
- Measuring time on page and engagement duration thresholds
- Setting up site speed tracking and performance benchmarks
- Using debug mode to validate configuration accuracy
- Creating a configuration audit checklist for ongoing maintenance
Module 3: Data Layer and Tag Management Integration - Understanding the relationship between GA4 and Google Tag Manager
- Installing Google Tag Manager on your website or app
- Creating a GA4 configuration tag with control parameters
- Building triggers for page views, clicks, form submissions
- Using built-in variables vs custom variables in GTM
- Creating custom event triggers based on CSS selectors
- Setting up scroll depth tracking with percentage thresholds
- Implementing form abandonment tracking with custom triggers
- Passing data layer values to GA4 events dynamically
- Creating data layer variables for product, user, and event context
- Debugging tag firing sequences using GTM preview mode
- Setting up error tracking using JavaScript exceptions in GTM
- Adding consent mode for GDPR-compliant tracking
- Configuring ad personalisation, ad storage, and analytics storage
- Setting up AMP and iOS/Android app tracking via GTM
- Version control and workspace management in GTM
- Testing container changes in staging environments
- Publishing GTM containers with change logs and rollback plans
- Setting up custom HTML tags for third-party integrations
- Validating cross-domain tracking configurations
- Creating lookup tables for campaign parameter mapping
- Using regex filters for dynamic URL tracking
Module 4: Advanced Event and Conversion Modelling - Understanding predictive vs observed conversions in GA4
- Configuring conversion modeling for data gaps and privacy restrictions
- Setting up audience triggers for predictive audiences
- Defining high-value users based on behavioural signals
- Creating custom conversion scoring models
- Excluding bot traffic and internal IP addresses from processing
- Setting up filter sets for segmented data views
- Using exploration techniques to identify conversion drop-off points
- Validating event parameters with raw data export
- Configuring custom funnels with flexible entry and exit steps
- Measuring time to conversion across multiple sessions
- Setting up cross-platform conversion paths
- Building custom channel groupings for accurate attribution
- Understanding data-driven attribution weighting
- Comparing last-click vs position-based vs data-driven models
- Creating custom conversion segments for cohort analysis
- Configuring lifetime value (LTV) predictions for retention strategy
- Setting up churn probability modeling
- Measuring product affinity and category purchase sequences
- Creating dynamic audiences for remarketing
- Validating audience logic with exploration reports
Module 5: Data Quality Assurance and Auditing - Conducting a full GA4 health audit: 12-point checklist
- Validating event firing consistency across devices
- Checking data completeness: missing events, null values, zero revenue
- Using GA4 diagnostic reports for anomaly detection
- Identifying and fixing duplicate event tracking
- Resolving missing page view or session start events
- Validating cross-domain tracking with referral path analysis
- Checking user ID overlap and authentication gaps
- Testing server-side tagging connectivity
- Using BigQuery export to verify raw event streams
- Comparing GA4 data with backend CRM or order system records
- Identifying discrepancies in e-commerce totals
- Validating Google Ads click-to-conversion lag
- Testing UTM parameter persistence in multi-touch journeys
- Checking for referrer spam and ghost traffic
- Implementing bot filtering rules at property level
- Setting up custom alerts for data anomalies
- Creating monthly audit documentation templates
- Establishing internal SLAs for data quality oversight
- Training teams on data hygiene best practices
- Using Simo Ahava’s debugging methodology for complex cases
Module 6: Reporting, Visualisation, and Insight Generation - Navigating the GA4 interface with efficiency and intent
- Understanding the lifecycle reporting model: acquisition, engagement, monetisation, retention
- Interpreting engagement rate vs bounce rate in GA4
- Analysing user acquisition channels with campaign tagging accuracy
- Reading and explaining funnel visualisation reports
- Interpreting pathing reports to identify common user journeys
- Using cohort analysis to measure retention and stickiness
- Analysing monetisation reports: ARPU, purchase rate, average order value
- Understanding e-commerce purchase paths and product performance
- Creating custom reports with specific KPIs and filters
- Applying comparison segments to isolate performance differences
- Using date range comparisons to spot trends
- Exporting reports to PDF, CSV, or Google Sheets
- Building real-time monitoring dashboards
- Creating scheduled report emails for stakeholders
- Sharing exploration reports with annotations
- Using annotation best practices for context
- Building story-driven presentations from analytics data
- Distinguishing correlation from causation in trend analysis
- Identifying leading vs lagging indicators in reports
- Creating executive summary dashboards with KPIs only
Module 7: Deep Dives with Explorations - Accessing and navigating the Explorations section
- Building Free Form explorations with multiple dimensions
- Using funnel exploration to analyse conversion drop-off
- Creating path exploration to map user navigation flows
- Using segment overlap to compare audience behaviours
- Building cohort exploration for retention and LTV analysis
- Setting up predictive exploration for churn and purchase likelihood
- Configuring blank exploration for custom analysis
- Adding dimensions: device, location, campaign, custom parameters
- Adding metrics: sessions, conversions, revenue, engagement time
- Using segments to filter high-intent or at-risk users
- Applying date comparisons to track performance changes
- Using the filter feature to isolate specific data subsets
- Creating calculated metrics for custom KPIs (e.g. revenue per engaged user)
- Visualising data with bar, line, pie, and table charts
- Exporting exploration results to PDF or Google Slides
- Saving exploration templates for recurring analysis
- Sharing explorations with stakeholders via link or email
- Using exploration annotations to guide interpretation
- Building a library of reusable analysis templates
- Training teams to use explorations independently
Module 8: BigQuery Integration and Raw Data Mastery - Enabling BigQuery export for full raw data access
- Understanding the GA4 BigQuery schema structure
- Navigating BigQuery console and dataset organisation
- Writing basic SQL queries to extract event data
- Selecting specific events, parameters, and user properties
- Filtering data by date range, user ID, or campaign
- Aggregating metrics: count, sum, average, distinct users
- Grouping data by dimensions like device, country, source
- Joining GA4 data with CRM or order system tables
- Calculating conversion rates from raw event counts
- Identifying top conversion paths using funnel queries
- Measuring time between key events (e.g. sign-up to purchase)
- Building custom attribution models in SQL
- Exporting query results to Google Sheets for reporting
- Scheduling automated data exports with BigQuery jobs
- Using partitioning and clustering for query efficiency
- Estimating query costs and managing budget
- Caching frequent queries for faster access
- Setting up dashboards in Looker Studio powered by BigQuery
- Validating GA4 interface data against raw exports
- Creating data dictionaries for team-wide clarity
Module 9: Organisation-Wide Analytics Governance - Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)
Module 10: Certification Preparation and Career Advancement - Reviewing key concepts for the Google Analytics certification exam
- Analysing sample exam questions with deep explanations
- Mastering GA4 interface navigation under time pressure
- Understanding data collection methodology differences
- Practicing interpretation of exploration reports
- Learning how to eliminate trick question traps
- Preparing for scenario-based questions on implementation
- Reviewing attribution model comparisons
- Understanding consent mode and data privacy rules
- Practicing budget-friendly analytics strategies for small teams
- Building a portfolio of documentation: measurement plans, audit reports, dashboards
- Creating a LinkedIn-ready case study from your course project
- Using your Certificate of Completion to boost job applications
- Adding your credential to email signatures and CVs
- Preparing for salary negotiation with analytics expertise
- Positioning yourself as the data authority in your organisation
- Leading analytics transformation initiatives
- Transitioning from marketer to analytics manager
- Freelancing or consulting with verified skills
- Becoming a go-to resource for data-driven decision making
- Continuing your journey with advanced data science pathways
- Understanding the core purpose and business value of Google Analytics
- Differentiating between Universal Analytics and GA4: what changed and why it matters
- Mapping analytics to business objectives: revenue, engagement, retention
- The anatomy of a GA4 property: streams, data layers, and processing levels
- How Google Analytics fits into the modern marketing technology stack
- Privacy-first analytics: legal compliance and ethical data collection
- GDPR, CCPA, and ITP implications for tracking configuration
- Role-based access: setting up user permissions securely
- Creating your first GA4 property from scratch
- Linking Google Analytics to Google Ads, Search Console, and Tag Manager
- Verifying connectivity between platforms using diagnostics tools
- Setting up a development, staging, and production analytics environment
- Understanding data thresholds and sampling limitations in GA4
- The role of events, parameters, and user properties in event-driven architecture
- Default vs custom dimensions and metrics: when to use each
Module 2: Strategic Setup and Configuration - Conducting a stakeholder requirement workshop for analytics scope
- Defining core business conversions: macro and micro goals
- Creating a measurement strategy document for organisational alignment
- Configuring enhanced measurement: what to enable and what to disable
- Setting up event tracking without code: scroll, outbound clicks, downloads
- Custom event creation: naming conventions and best practices
- Configuring conversion events and prioritising value
- Setting up purchase revenue tracking for e-commerce
- Adding transaction parameters for product-level reporting
- Configuring user ID tracking for cross-device journey mapping
- Setting up custom dimensions for campaign, content, and user segmentation
- Implementing content grouping for site section analysis
- Configuring internal search tracking with custom parameters
- Setting up outbound link tracking with parameter persistence
- Configuring video engagement tracking (play, pause, complete)
- Adding form interaction tracking: start, progress, submission
- Setting up error page tracking for user experience optimisation
- Measuring time on page and engagement duration thresholds
- Setting up site speed tracking and performance benchmarks
- Using debug mode to validate configuration accuracy
- Creating a configuration audit checklist for ongoing maintenance
Module 3: Data Layer and Tag Management Integration - Understanding the relationship between GA4 and Google Tag Manager
- Installing Google Tag Manager on your website or app
- Creating a GA4 configuration tag with control parameters
- Building triggers for page views, clicks, form submissions
- Using built-in variables vs custom variables in GTM
- Creating custom event triggers based on CSS selectors
- Setting up scroll depth tracking with percentage thresholds
- Implementing form abandonment tracking with custom triggers
- Passing data layer values to GA4 events dynamically
- Creating data layer variables for product, user, and event context
- Debugging tag firing sequences using GTM preview mode
- Setting up error tracking using JavaScript exceptions in GTM
- Adding consent mode for GDPR-compliant tracking
- Configuring ad personalisation, ad storage, and analytics storage
- Setting up AMP and iOS/Android app tracking via GTM
- Version control and workspace management in GTM
- Testing container changes in staging environments
- Publishing GTM containers with change logs and rollback plans
- Setting up custom HTML tags for third-party integrations
- Validating cross-domain tracking configurations
- Creating lookup tables for campaign parameter mapping
- Using regex filters for dynamic URL tracking
Module 4: Advanced Event and Conversion Modelling - Understanding predictive vs observed conversions in GA4
- Configuring conversion modeling for data gaps and privacy restrictions
- Setting up audience triggers for predictive audiences
- Defining high-value users based on behavioural signals
- Creating custom conversion scoring models
- Excluding bot traffic and internal IP addresses from processing
- Setting up filter sets for segmented data views
- Using exploration techniques to identify conversion drop-off points
- Validating event parameters with raw data export
- Configuring custom funnels with flexible entry and exit steps
- Measuring time to conversion across multiple sessions
- Setting up cross-platform conversion paths
- Building custom channel groupings for accurate attribution
- Understanding data-driven attribution weighting
- Comparing last-click vs position-based vs data-driven models
- Creating custom conversion segments for cohort analysis
- Configuring lifetime value (LTV) predictions for retention strategy
- Setting up churn probability modeling
- Measuring product affinity and category purchase sequences
- Creating dynamic audiences for remarketing
- Validating audience logic with exploration reports
Module 5: Data Quality Assurance and Auditing - Conducting a full GA4 health audit: 12-point checklist
- Validating event firing consistency across devices
- Checking data completeness: missing events, null values, zero revenue
- Using GA4 diagnostic reports for anomaly detection
- Identifying and fixing duplicate event tracking
- Resolving missing page view or session start events
- Validating cross-domain tracking with referral path analysis
- Checking user ID overlap and authentication gaps
- Testing server-side tagging connectivity
- Using BigQuery export to verify raw event streams
- Comparing GA4 data with backend CRM or order system records
- Identifying discrepancies in e-commerce totals
- Validating Google Ads click-to-conversion lag
- Testing UTM parameter persistence in multi-touch journeys
- Checking for referrer spam and ghost traffic
- Implementing bot filtering rules at property level
- Setting up custom alerts for data anomalies
- Creating monthly audit documentation templates
- Establishing internal SLAs for data quality oversight
- Training teams on data hygiene best practices
- Using Simo Ahava’s debugging methodology for complex cases
Module 6: Reporting, Visualisation, and Insight Generation - Navigating the GA4 interface with efficiency and intent
- Understanding the lifecycle reporting model: acquisition, engagement, monetisation, retention
- Interpreting engagement rate vs bounce rate in GA4
- Analysing user acquisition channels with campaign tagging accuracy
- Reading and explaining funnel visualisation reports
- Interpreting pathing reports to identify common user journeys
- Using cohort analysis to measure retention and stickiness
- Analysing monetisation reports: ARPU, purchase rate, average order value
- Understanding e-commerce purchase paths and product performance
- Creating custom reports with specific KPIs and filters
- Applying comparison segments to isolate performance differences
- Using date range comparisons to spot trends
- Exporting reports to PDF, CSV, or Google Sheets
- Building real-time monitoring dashboards
- Creating scheduled report emails for stakeholders
- Sharing exploration reports with annotations
- Using annotation best practices for context
- Building story-driven presentations from analytics data
- Distinguishing correlation from causation in trend analysis
- Identifying leading vs lagging indicators in reports
- Creating executive summary dashboards with KPIs only
Module 7: Deep Dives with Explorations - Accessing and navigating the Explorations section
- Building Free Form explorations with multiple dimensions
- Using funnel exploration to analyse conversion drop-off
- Creating path exploration to map user navigation flows
- Using segment overlap to compare audience behaviours
- Building cohort exploration for retention and LTV analysis
- Setting up predictive exploration for churn and purchase likelihood
- Configuring blank exploration for custom analysis
- Adding dimensions: device, location, campaign, custom parameters
- Adding metrics: sessions, conversions, revenue, engagement time
- Using segments to filter high-intent or at-risk users
- Applying date comparisons to track performance changes
- Using the filter feature to isolate specific data subsets
- Creating calculated metrics for custom KPIs (e.g. revenue per engaged user)
- Visualising data with bar, line, pie, and table charts
- Exporting exploration results to PDF or Google Slides
- Saving exploration templates for recurring analysis
- Sharing explorations with stakeholders via link or email
- Using exploration annotations to guide interpretation
- Building a library of reusable analysis templates
- Training teams to use explorations independently
Module 8: BigQuery Integration and Raw Data Mastery - Enabling BigQuery export for full raw data access
- Understanding the GA4 BigQuery schema structure
- Navigating BigQuery console and dataset organisation
- Writing basic SQL queries to extract event data
- Selecting specific events, parameters, and user properties
- Filtering data by date range, user ID, or campaign
- Aggregating metrics: count, sum, average, distinct users
- Grouping data by dimensions like device, country, source
- Joining GA4 data with CRM or order system tables
- Calculating conversion rates from raw event counts
- Identifying top conversion paths using funnel queries
- Measuring time between key events (e.g. sign-up to purchase)
- Building custom attribution models in SQL
- Exporting query results to Google Sheets for reporting
- Scheduling automated data exports with BigQuery jobs
- Using partitioning and clustering for query efficiency
- Estimating query costs and managing budget
- Caching frequent queries for faster access
- Setting up dashboards in Looker Studio powered by BigQuery
- Validating GA4 interface data against raw exports
- Creating data dictionaries for team-wide clarity
Module 9: Organisation-Wide Analytics Governance - Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)
Module 10: Certification Preparation and Career Advancement - Reviewing key concepts for the Google Analytics certification exam
- Analysing sample exam questions with deep explanations
- Mastering GA4 interface navigation under time pressure
- Understanding data collection methodology differences
- Practicing interpretation of exploration reports
- Learning how to eliminate trick question traps
- Preparing for scenario-based questions on implementation
- Reviewing attribution model comparisons
- Understanding consent mode and data privacy rules
- Practicing budget-friendly analytics strategies for small teams
- Building a portfolio of documentation: measurement plans, audit reports, dashboards
- Creating a LinkedIn-ready case study from your course project
- Using your Certificate of Completion to boost job applications
- Adding your credential to email signatures and CVs
- Preparing for salary negotiation with analytics expertise
- Positioning yourself as the data authority in your organisation
- Leading analytics transformation initiatives
- Transitioning from marketer to analytics manager
- Freelancing or consulting with verified skills
- Becoming a go-to resource for data-driven decision making
- Continuing your journey with advanced data science pathways
- Understanding the relationship between GA4 and Google Tag Manager
- Installing Google Tag Manager on your website or app
- Creating a GA4 configuration tag with control parameters
- Building triggers for page views, clicks, form submissions
- Using built-in variables vs custom variables in GTM
- Creating custom event triggers based on CSS selectors
- Setting up scroll depth tracking with percentage thresholds
- Implementing form abandonment tracking with custom triggers
- Passing data layer values to GA4 events dynamically
- Creating data layer variables for product, user, and event context
- Debugging tag firing sequences using GTM preview mode
- Setting up error tracking using JavaScript exceptions in GTM
- Adding consent mode for GDPR-compliant tracking
- Configuring ad personalisation, ad storage, and analytics storage
- Setting up AMP and iOS/Android app tracking via GTM
- Version control and workspace management in GTM
- Testing container changes in staging environments
- Publishing GTM containers with change logs and rollback plans
- Setting up custom HTML tags for third-party integrations
- Validating cross-domain tracking configurations
- Creating lookup tables for campaign parameter mapping
- Using regex filters for dynamic URL tracking
Module 4: Advanced Event and Conversion Modelling - Understanding predictive vs observed conversions in GA4
- Configuring conversion modeling for data gaps and privacy restrictions
- Setting up audience triggers for predictive audiences
- Defining high-value users based on behavioural signals
- Creating custom conversion scoring models
- Excluding bot traffic and internal IP addresses from processing
- Setting up filter sets for segmented data views
- Using exploration techniques to identify conversion drop-off points
- Validating event parameters with raw data export
- Configuring custom funnels with flexible entry and exit steps
- Measuring time to conversion across multiple sessions
- Setting up cross-platform conversion paths
- Building custom channel groupings for accurate attribution
- Understanding data-driven attribution weighting
- Comparing last-click vs position-based vs data-driven models
- Creating custom conversion segments for cohort analysis
- Configuring lifetime value (LTV) predictions for retention strategy
- Setting up churn probability modeling
- Measuring product affinity and category purchase sequences
- Creating dynamic audiences for remarketing
- Validating audience logic with exploration reports
Module 5: Data Quality Assurance and Auditing - Conducting a full GA4 health audit: 12-point checklist
- Validating event firing consistency across devices
- Checking data completeness: missing events, null values, zero revenue
- Using GA4 diagnostic reports for anomaly detection
- Identifying and fixing duplicate event tracking
- Resolving missing page view or session start events
- Validating cross-domain tracking with referral path analysis
- Checking user ID overlap and authentication gaps
- Testing server-side tagging connectivity
- Using BigQuery export to verify raw event streams
- Comparing GA4 data with backend CRM or order system records
- Identifying discrepancies in e-commerce totals
- Validating Google Ads click-to-conversion lag
- Testing UTM parameter persistence in multi-touch journeys
- Checking for referrer spam and ghost traffic
- Implementing bot filtering rules at property level
- Setting up custom alerts for data anomalies
- Creating monthly audit documentation templates
- Establishing internal SLAs for data quality oversight
- Training teams on data hygiene best practices
- Using Simo Ahava’s debugging methodology for complex cases
Module 6: Reporting, Visualisation, and Insight Generation - Navigating the GA4 interface with efficiency and intent
- Understanding the lifecycle reporting model: acquisition, engagement, monetisation, retention
- Interpreting engagement rate vs bounce rate in GA4
- Analysing user acquisition channels with campaign tagging accuracy
- Reading and explaining funnel visualisation reports
- Interpreting pathing reports to identify common user journeys
- Using cohort analysis to measure retention and stickiness
- Analysing monetisation reports: ARPU, purchase rate, average order value
- Understanding e-commerce purchase paths and product performance
- Creating custom reports with specific KPIs and filters
- Applying comparison segments to isolate performance differences
- Using date range comparisons to spot trends
- Exporting reports to PDF, CSV, or Google Sheets
- Building real-time monitoring dashboards
- Creating scheduled report emails for stakeholders
- Sharing exploration reports with annotations
- Using annotation best practices for context
- Building story-driven presentations from analytics data
- Distinguishing correlation from causation in trend analysis
- Identifying leading vs lagging indicators in reports
- Creating executive summary dashboards with KPIs only
Module 7: Deep Dives with Explorations - Accessing and navigating the Explorations section
- Building Free Form explorations with multiple dimensions
- Using funnel exploration to analyse conversion drop-off
- Creating path exploration to map user navigation flows
- Using segment overlap to compare audience behaviours
- Building cohort exploration for retention and LTV analysis
- Setting up predictive exploration for churn and purchase likelihood
- Configuring blank exploration for custom analysis
- Adding dimensions: device, location, campaign, custom parameters
- Adding metrics: sessions, conversions, revenue, engagement time
- Using segments to filter high-intent or at-risk users
- Applying date comparisons to track performance changes
- Using the filter feature to isolate specific data subsets
- Creating calculated metrics for custom KPIs (e.g. revenue per engaged user)
- Visualising data with bar, line, pie, and table charts
- Exporting exploration results to PDF or Google Slides
- Saving exploration templates for recurring analysis
- Sharing explorations with stakeholders via link or email
- Using exploration annotations to guide interpretation
- Building a library of reusable analysis templates
- Training teams to use explorations independently
Module 8: BigQuery Integration and Raw Data Mastery - Enabling BigQuery export for full raw data access
- Understanding the GA4 BigQuery schema structure
- Navigating BigQuery console and dataset organisation
- Writing basic SQL queries to extract event data
- Selecting specific events, parameters, and user properties
- Filtering data by date range, user ID, or campaign
- Aggregating metrics: count, sum, average, distinct users
- Grouping data by dimensions like device, country, source
- Joining GA4 data with CRM or order system tables
- Calculating conversion rates from raw event counts
- Identifying top conversion paths using funnel queries
- Measuring time between key events (e.g. sign-up to purchase)
- Building custom attribution models in SQL
- Exporting query results to Google Sheets for reporting
- Scheduling automated data exports with BigQuery jobs
- Using partitioning and clustering for query efficiency
- Estimating query costs and managing budget
- Caching frequent queries for faster access
- Setting up dashboards in Looker Studio powered by BigQuery
- Validating GA4 interface data against raw exports
- Creating data dictionaries for team-wide clarity
Module 9: Organisation-Wide Analytics Governance - Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)
Module 10: Certification Preparation and Career Advancement - Reviewing key concepts for the Google Analytics certification exam
- Analysing sample exam questions with deep explanations
- Mastering GA4 interface navigation under time pressure
- Understanding data collection methodology differences
- Practicing interpretation of exploration reports
- Learning how to eliminate trick question traps
- Preparing for scenario-based questions on implementation
- Reviewing attribution model comparisons
- Understanding consent mode and data privacy rules
- Practicing budget-friendly analytics strategies for small teams
- Building a portfolio of documentation: measurement plans, audit reports, dashboards
- Creating a LinkedIn-ready case study from your course project
- Using your Certificate of Completion to boost job applications
- Adding your credential to email signatures and CVs
- Preparing for salary negotiation with analytics expertise
- Positioning yourself as the data authority in your organisation
- Leading analytics transformation initiatives
- Transitioning from marketer to analytics manager
- Freelancing or consulting with verified skills
- Becoming a go-to resource for data-driven decision making
- Continuing your journey with advanced data science pathways
- Conducting a full GA4 health audit: 12-point checklist
- Validating event firing consistency across devices
- Checking data completeness: missing events, null values, zero revenue
- Using GA4 diagnostic reports for anomaly detection
- Identifying and fixing duplicate event tracking
- Resolving missing page view or session start events
- Validating cross-domain tracking with referral path analysis
- Checking user ID overlap and authentication gaps
- Testing server-side tagging connectivity
- Using BigQuery export to verify raw event streams
- Comparing GA4 data with backend CRM or order system records
- Identifying discrepancies in e-commerce totals
- Validating Google Ads click-to-conversion lag
- Testing UTM parameter persistence in multi-touch journeys
- Checking for referrer spam and ghost traffic
- Implementing bot filtering rules at property level
- Setting up custom alerts for data anomalies
- Creating monthly audit documentation templates
- Establishing internal SLAs for data quality oversight
- Training teams on data hygiene best practices
- Using Simo Ahava’s debugging methodology for complex cases
Module 6: Reporting, Visualisation, and Insight Generation - Navigating the GA4 interface with efficiency and intent
- Understanding the lifecycle reporting model: acquisition, engagement, monetisation, retention
- Interpreting engagement rate vs bounce rate in GA4
- Analysing user acquisition channels with campaign tagging accuracy
- Reading and explaining funnel visualisation reports
- Interpreting pathing reports to identify common user journeys
- Using cohort analysis to measure retention and stickiness
- Analysing monetisation reports: ARPU, purchase rate, average order value
- Understanding e-commerce purchase paths and product performance
- Creating custom reports with specific KPIs and filters
- Applying comparison segments to isolate performance differences
- Using date range comparisons to spot trends
- Exporting reports to PDF, CSV, or Google Sheets
- Building real-time monitoring dashboards
- Creating scheduled report emails for stakeholders
- Sharing exploration reports with annotations
- Using annotation best practices for context
- Building story-driven presentations from analytics data
- Distinguishing correlation from causation in trend analysis
- Identifying leading vs lagging indicators in reports
- Creating executive summary dashboards with KPIs only
Module 7: Deep Dives with Explorations - Accessing and navigating the Explorations section
- Building Free Form explorations with multiple dimensions
- Using funnel exploration to analyse conversion drop-off
- Creating path exploration to map user navigation flows
- Using segment overlap to compare audience behaviours
- Building cohort exploration for retention and LTV analysis
- Setting up predictive exploration for churn and purchase likelihood
- Configuring blank exploration for custom analysis
- Adding dimensions: device, location, campaign, custom parameters
- Adding metrics: sessions, conversions, revenue, engagement time
- Using segments to filter high-intent or at-risk users
- Applying date comparisons to track performance changes
- Using the filter feature to isolate specific data subsets
- Creating calculated metrics for custom KPIs (e.g. revenue per engaged user)
- Visualising data with bar, line, pie, and table charts
- Exporting exploration results to PDF or Google Slides
- Saving exploration templates for recurring analysis
- Sharing explorations with stakeholders via link or email
- Using exploration annotations to guide interpretation
- Building a library of reusable analysis templates
- Training teams to use explorations independently
Module 8: BigQuery Integration and Raw Data Mastery - Enabling BigQuery export for full raw data access
- Understanding the GA4 BigQuery schema structure
- Navigating BigQuery console and dataset organisation
- Writing basic SQL queries to extract event data
- Selecting specific events, parameters, and user properties
- Filtering data by date range, user ID, or campaign
- Aggregating metrics: count, sum, average, distinct users
- Grouping data by dimensions like device, country, source
- Joining GA4 data with CRM or order system tables
- Calculating conversion rates from raw event counts
- Identifying top conversion paths using funnel queries
- Measuring time between key events (e.g. sign-up to purchase)
- Building custom attribution models in SQL
- Exporting query results to Google Sheets for reporting
- Scheduling automated data exports with BigQuery jobs
- Using partitioning and clustering for query efficiency
- Estimating query costs and managing budget
- Caching frequent queries for faster access
- Setting up dashboards in Looker Studio powered by BigQuery
- Validating GA4 interface data against raw exports
- Creating data dictionaries for team-wide clarity
Module 9: Organisation-Wide Analytics Governance - Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)
Module 10: Certification Preparation and Career Advancement - Reviewing key concepts for the Google Analytics certification exam
- Analysing sample exam questions with deep explanations
- Mastering GA4 interface navigation under time pressure
- Understanding data collection methodology differences
- Practicing interpretation of exploration reports
- Learning how to eliminate trick question traps
- Preparing for scenario-based questions on implementation
- Reviewing attribution model comparisons
- Understanding consent mode and data privacy rules
- Practicing budget-friendly analytics strategies for small teams
- Building a portfolio of documentation: measurement plans, audit reports, dashboards
- Creating a LinkedIn-ready case study from your course project
- Using your Certificate of Completion to boost job applications
- Adding your credential to email signatures and CVs
- Preparing for salary negotiation with analytics expertise
- Positioning yourself as the data authority in your organisation
- Leading analytics transformation initiatives
- Transitioning from marketer to analytics manager
- Freelancing or consulting with verified skills
- Becoming a go-to resource for data-driven decision making
- Continuing your journey with advanced data science pathways
- Accessing and navigating the Explorations section
- Building Free Form explorations with multiple dimensions
- Using funnel exploration to analyse conversion drop-off
- Creating path exploration to map user navigation flows
- Using segment overlap to compare audience behaviours
- Building cohort exploration for retention and LTV analysis
- Setting up predictive exploration for churn and purchase likelihood
- Configuring blank exploration for custom analysis
- Adding dimensions: device, location, campaign, custom parameters
- Adding metrics: sessions, conversions, revenue, engagement time
- Using segments to filter high-intent or at-risk users
- Applying date comparisons to track performance changes
- Using the filter feature to isolate specific data subsets
- Creating calculated metrics for custom KPIs (e.g. revenue per engaged user)
- Visualising data with bar, line, pie, and table charts
- Exporting exploration results to PDF or Google Slides
- Saving exploration templates for recurring analysis
- Sharing explorations with stakeholders via link or email
- Using exploration annotations to guide interpretation
- Building a library of reusable analysis templates
- Training teams to use explorations independently
Module 8: BigQuery Integration and Raw Data Mastery - Enabling BigQuery export for full raw data access
- Understanding the GA4 BigQuery schema structure
- Navigating BigQuery console and dataset organisation
- Writing basic SQL queries to extract event data
- Selecting specific events, parameters, and user properties
- Filtering data by date range, user ID, or campaign
- Aggregating metrics: count, sum, average, distinct users
- Grouping data by dimensions like device, country, source
- Joining GA4 data with CRM or order system tables
- Calculating conversion rates from raw event counts
- Identifying top conversion paths using funnel queries
- Measuring time between key events (e.g. sign-up to purchase)
- Building custom attribution models in SQL
- Exporting query results to Google Sheets for reporting
- Scheduling automated data exports with BigQuery jobs
- Using partitioning and clustering for query efficiency
- Estimating query costs and managing budget
- Caching frequent queries for faster access
- Setting up dashboards in Looker Studio powered by BigQuery
- Validating GA4 interface data against raw exports
- Creating data dictionaries for team-wide clarity
Module 9: Organisation-Wide Analytics Governance - Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)
Module 10: Certification Preparation and Career Advancement - Reviewing key concepts for the Google Analytics certification exam
- Analysing sample exam questions with deep explanations
- Mastering GA4 interface navigation under time pressure
- Understanding data collection methodology differences
- Practicing interpretation of exploration reports
- Learning how to eliminate trick question traps
- Preparing for scenario-based questions on implementation
- Reviewing attribution model comparisons
- Understanding consent mode and data privacy rules
- Practicing budget-friendly analytics strategies for small teams
- Building a portfolio of documentation: measurement plans, audit reports, dashboards
- Creating a LinkedIn-ready case study from your course project
- Using your Certificate of Completion to boost job applications
- Adding your credential to email signatures and CVs
- Preparing for salary negotiation with analytics expertise
- Positioning yourself as the data authority in your organisation
- Leading analytics transformation initiatives
- Transitioning from marketer to analytics manager
- Freelancing or consulting with verified skills
- Becoming a go-to resource for data-driven decision making
- Continuing your journey with advanced data science pathways
- Establishing an analytics governance framework
- Defining roles: analyst, admin, reviewer, stakeholder
- Creating a central tag audit log and change history
- Implementing naming conventions for tags, triggers, variables
- Setting up documentation standards for tracking plans
- Building a measurement plan repository in Google Drive or Notion
- Conducting quarterly analytics health reviews
- Training marketing and development teams on tagging discipline
- Creating a launch checklist for new campaigns or features
- Ensuring tracking parity across web, app, and AMP
- Managing access rights with least-privilege principles
- Archiving unused tags and containers
- Monitoring container load performance impact
- Integrating analytics QA into development sprints
- Using version control and approval workflows in GTM
- Creating stakeholder reporting calendars
- Standardising KPI definitions across departments
- Aligning analytics with OKRs and business objectives
- Conducting annual compliance audits for data privacy
- Preparing for future platform changes (e.g. deprecation notices)