Mastering Adobe Analytics: The Complete Guide to Data-Driven Decision Making
You’re under pressure. Your team needs answers, not data dumps. Stakeholders demand clarity. Executives want proof your digital strategy moves the needle. And you’re stuck in a maze of metrics, reports, and incomplete insights-wasting hours chasing ghosts in your analytics platform. You know Adobe Analytics holds the key, but mastering it feels like deciphering hieroglyphics without a translator. You’ve tried documentation, forums, and fragmented guides. Nothing connects the dots from raw data to boardroom-ready decisions. You’re missing the structured system that turns confusion into confidence. Mastering Adobe Analytics: The Complete Guide to Data-Driven Decision Making is that system. This course transforms you from overwhelmed user to strategic analyst-equipping you to extract, interpret, and act on data with precision, speed, and authority. Imagine building custom reports in under 15 minutes, identifying revenue leaks before they impact performance, and presenting insights so clear that stakeholders approve your next initiative on the spot. That’s the outcome: going from data uncertainty to delivering actionable intelligence with a board-ready decision framework in 30 days. Jamie R., Senior Digital Analyst at a global e-commerce brand, used this methodology to identify a $2.3M annual revenue loss caused by funnel drop-offs. Within three weeks of applying these techniques, her team redesigned the checkout flow and increased conversion by 18%. Now she leads analytics for the entire EU region. This isn’t about learning tools. It’s about owning outcomes. Here’s how this course is structured to help you get there.Course Format & Delivery Details: Learn with Confidence, Clarity, and Zero Risk Self-Paced, On-Demand Access with No Deadlines or Time Pressure This is a fully self-paced learning experience. You begin the moment your access is confirmed, and progress at your own rhythm-no fixed live sessions, no rigid schedules. You decide when and where you learn, fitting it seamlessly around your responsibilities. Most learners complete the core curriculum in 4 to 6 weeks with 60–90 minutes of focused work per week. But many report applying the first framework to real business questions within 72 hours of starting. Results don’t wait for completion. Lifetime Access with Continuous, No-Cost Updates Once enrolled, you have indefinite access to all course materials. Adobe Analytics evolves-and so does this course. You receive every future update automatically, ensuring your knowledge stays current, accurate, and aligned with Adobe’s latest capabilities, at no additional fee. 24/7 Global Access • Mobile-Friendly Learning Anywhere Access the full curriculum from any device-laptop, tablet, or smartphone. Whether you’re at your desk, on a train, or working remotely, the material is optimized for fast loading, responsive navigation, and distraction-free focus, no matter your location or bandwidth. Direct Instructor Guidance and Expert Support You’re not learning in isolation. Throughout the course, you receive structured guidance from industry-certified analytics professionals with over a decade of real-world Adobe Analytics implementation experience. Their insights are embedded directly into the content, and responsive feedback mechanisms ensure your questions are addressed with precision. Receive a Certificate of Completion Issued by The Art of Service Upon finishing, you earn a globally recognised Certificate of Completion issued by The Art of Service, a leader in professional digital training with over 250,000 professionals trained worldwide. This credential validates your expertise and strengthens your credibility in job applications, promotions, and cross-functional leadership. Transparent, One-Time Pricing • No Hidden Fees The price covers everything: full curriculum, all updates, certification, and support. No subscriptions. No surprise charges. No upsells. You see the total cost upfront, and what you pay today is all you will ever pay. Accepted Payment Methods: Visa, Mastercard, PayPal Secure payment processing ensures your transaction is safe and seamless. Payments are handled through encrypted gateways, and your financial information remains private. Enrol Risk-Free with Our 30-Day “Satisfied or Refunded” Guarantee We eliminate all risk. Study the course, apply the frameworks, and test the outcomes. If you’re not completely satisfied within 30 days, simply contact support for a full refund-no forms, no hoops, no questions asked. What Happens After Enrollment? Once you enrol, you’ll receive a confirmation email. Shortly afterward, a separate message delivers your secure access details and login instructions. Your access is fully activated once your learner profile is processed and verified-typically within a few business hours. Will This Work for Me? Absolutely-Especially If You’re New to Adobe Analytics, Overwhelmed by Data, or Need to Prove ROI Faster This course works even if you’ve struggled with other training platforms. It works even if you’ve never built a custom report. It works even if your current data is messy or inconsistently tracked. Why? Because it’s built for real-world conditions. Each module follows a proven implementation path used by enterprise analytics teams-from setting up variables correctly to isolating signal from noise. You’ll follow step-by-step workflows tested across industries, including retail, SaaS, finance, and media. Sarah K., a Marketing Operations Manager at a B2B tech firm, entered the course doubting her technical skills. After completing Module 3, she rebuilt her company’s campaign tracking and discovered under-attributed channels driving 37% of new leads. She was promoted within two months. You’re not just learning analytics. You’re mastering a high-leverage skill that compounds across every role in digital, marketing, product, and strategy. This is your career advantage-delivered with certainty.
Module 1: Foundations of Adobe Analytics and Data-Driven Thinking - Understanding the role of digital analytics in strategic decision making
- Why most organisations fail to extract value from analytics platforms
- Core components of the Adobe Analytics ecosystem
- Key differences between Adobe Analytics and other analytics tools
- Navigating the interface: Workspaces, Reports, and Admin consoles
- How data flows from digital touchpoints into Adobe Analytics
- Setting up your user access and permissions correctly
- Introduction to hit, visit, and visitor-level data structures
- What are dimensions and metrics in Adobe Analytics?
- Best practices for naming conventions and report clarity
- Common pitfalls in data interpretation and how to avoid them
- Principles of clean, repeatable, and auditable analysis
- Defining success: Aligning KPIs to business objectives
- Establishing baseline metrics before building reports
- Understanding data processing and latency windows
Module 2: Core Concepts – Variables, Dimensions, and Metric Types - Overview of eVars, props, and events: Purpose and use cases
- How s.prop variables work and when to use them
- Deploying and configuring eVars for campaign tracking
- Differences between conversion and traffic variables
- First-touch vs. last-touch attribution at the variable level
- Setting expiration rules for persistence
- Custom conversion events vs. standard metrics
- Counters, currencies, and numeric event types
- Calculated metrics: how they extend raw data
- Using processing rules to transform incoming data
- Context data and its role in complex tracking
- Understanding timestamps and time-zone handling
- Link tracking: internal vs. exit link classification
- Page load vs. direct call rule triggers
- Global variables and their strategic application
Module 3: Implementing Accurate Data Capture and Tag Management - Setting up a data layer for consistent variable population
- Integrating Adobe Analytics with Adobe Experience Platform (AEP)
- Using Adobe Experience Platform Launch (Tags) effectively
- Rules, conditions, and actions in tag management
- Triggering analytics calls on page scroll, video play, form start
- Tracking single-page applications (SPAs) with dynamic data
- Validating implementation with browser developer tools
- Testing data capture before pushing to production
- Debugging missing or inflated metrics
- Implementing cross-domain and subdomain tracking
- Cookie handling and visitor identification logic
- Managing referrer data and campaign parameters
- UTM parameter mapping to Adobe variables
- Tracking offline conversions and CRM data sync
- Ensuring GDPR and privacy compliance in tracking setup
Module 4: Building High-Impact Reports and Dashboards - Creating custom reports using Analysis Workspace
- Dragging and dropping panels for multi-metric analysis
- Using flow reports to visualise user journey paths
- Building fallout reports to identify funnel drop-off points
- Designing executive dashboards with strategic KPIs
- Applying segment containers for comparative analysis
- Scheduling and automating report distribution
- Exporting data to PDF, CSV, or PowerPoint formats
- Using annotations to explain data shifts and events
- Leveraging bookmarks for report version control
- Sharing dashboards with stakeholders securely
- Setting up real-time alerting for threshold breaches
- Applying filters to isolate specific audience behaviours
- Using date range comparisons to show performance trends
- Creating reusable report templates for consistency
Module 5: Advanced Segmentation and Audience Targeting - Building complex segments using logical operators
- Defining audiences based on behavioural thresholds
- Creating segments for high-value customer cohorts
- Combining dimensions, metrics, and time conditions
- Using segment persistence across multiple reports
- Exporting segment definitions for team collaboration
- Applying segments in A/B testing and personalisation
- Feeding audiences into Adobe Target and Audience Manager
- Setting up lookalike modelling from top converters
- Analysing mobile vs. desktop user behaviour by segment
- Identifying churn risk segments based on drop-off patterns
- Creating time-based loyalty segments (e.g. 90-day inactive)
- Using geo-based segments for regional campaign analysis
- Tagging segments for audit and compliance tracking
- Validating segment accuracy with sample data queries
Module 6: Attribution Modelling and Pathing Analysis - Understanding multi-touch attribution concepts
- Comparing linear, time decay, and position-based models
- Setting up custom attribution models in Analysis Workspace
- Analysing assisted conversions across channels
- Identifying top assist channels in customer journeys
- Using path length analysis to understand decision cycles
- Visualising common entry-to-exit paths
- Detecting looping behaviour and redirects
- Applying pathing to conversion funnel optimisation
- Benchmarking paths by device, region, or campaign
- Calculating contribution scores for each touchpoint
- Using conversion explorer to trace individual paths
- Adjusting for direct traffic influence in models
- Building exposure frequency models for remarketing
- Aligning attribution insights with budget allocation
Module 7: Real-Time Data Monitoring and Alert Systems - Accessing real-time reports in Adobe Analytics
- Monitoring active users across devices and regions
- Setting up threshold-based alerts for anomalies
- Using real-time dashboards during campaign launches
- Identifying bot traffic and filtering it proactively
- Monitoring site health during traffic spikes
- Responding to sudden drop-offs with rapid diagnosis
- Integrating with incident response and DevOps teams
- Customising real-time panel layouts for speed
- Tracking user count by campaign or content piece
- Using real-time data to adjust ad spend dynamically
- Creating alerts for form abandonment surges
- Setting alert delivery via email or Slack integration
- Analysing concurrent user spikes during live events
- Validating data integrity during high-volume periods
Module 8: Data Visualization and Stakeholder Communication - Selecting the right chart type for each data story
- Designing dashboards for executive consumption
- Using colour psychology to highlight insights
- Decluttering charts to remove noise
- Labelling best practices for clarity and consistency
- Adding summaries and insights boxes to reports
- Writing compelling titles that guide interpretation
- Presenting trends versus snapshots effectively
- Using before-and-after comparisons to show impact
- Creating narrative flows in multi-panel dashboards
- Converting analytics findings into spoken insights
- Preparing Q&A backups for stakeholder challenges
- Translating technical data into business language
- Building confidence with consistent reporting rhythm
- Using preview modes to control stakeholder access
Module 9: Campaign Tracking, UTM Strategy, and Acquisition Analysis - Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Understanding the role of digital analytics in strategic decision making
- Why most organisations fail to extract value from analytics platforms
- Core components of the Adobe Analytics ecosystem
- Key differences between Adobe Analytics and other analytics tools
- Navigating the interface: Workspaces, Reports, and Admin consoles
- How data flows from digital touchpoints into Adobe Analytics
- Setting up your user access and permissions correctly
- Introduction to hit, visit, and visitor-level data structures
- What are dimensions and metrics in Adobe Analytics?
- Best practices for naming conventions and report clarity
- Common pitfalls in data interpretation and how to avoid them
- Principles of clean, repeatable, and auditable analysis
- Defining success: Aligning KPIs to business objectives
- Establishing baseline metrics before building reports
- Understanding data processing and latency windows
Module 2: Core Concepts – Variables, Dimensions, and Metric Types - Overview of eVars, props, and events: Purpose and use cases
- How s.prop variables work and when to use them
- Deploying and configuring eVars for campaign tracking
- Differences between conversion and traffic variables
- First-touch vs. last-touch attribution at the variable level
- Setting expiration rules for persistence
- Custom conversion events vs. standard metrics
- Counters, currencies, and numeric event types
- Calculated metrics: how they extend raw data
- Using processing rules to transform incoming data
- Context data and its role in complex tracking
- Understanding timestamps and time-zone handling
- Link tracking: internal vs. exit link classification
- Page load vs. direct call rule triggers
- Global variables and their strategic application
Module 3: Implementing Accurate Data Capture and Tag Management - Setting up a data layer for consistent variable population
- Integrating Adobe Analytics with Adobe Experience Platform (AEP)
- Using Adobe Experience Platform Launch (Tags) effectively
- Rules, conditions, and actions in tag management
- Triggering analytics calls on page scroll, video play, form start
- Tracking single-page applications (SPAs) with dynamic data
- Validating implementation with browser developer tools
- Testing data capture before pushing to production
- Debugging missing or inflated metrics
- Implementing cross-domain and subdomain tracking
- Cookie handling and visitor identification logic
- Managing referrer data and campaign parameters
- UTM parameter mapping to Adobe variables
- Tracking offline conversions and CRM data sync
- Ensuring GDPR and privacy compliance in tracking setup
Module 4: Building High-Impact Reports and Dashboards - Creating custom reports using Analysis Workspace
- Dragging and dropping panels for multi-metric analysis
- Using flow reports to visualise user journey paths
- Building fallout reports to identify funnel drop-off points
- Designing executive dashboards with strategic KPIs
- Applying segment containers for comparative analysis
- Scheduling and automating report distribution
- Exporting data to PDF, CSV, or PowerPoint formats
- Using annotations to explain data shifts and events
- Leveraging bookmarks for report version control
- Sharing dashboards with stakeholders securely
- Setting up real-time alerting for threshold breaches
- Applying filters to isolate specific audience behaviours
- Using date range comparisons to show performance trends
- Creating reusable report templates for consistency
Module 5: Advanced Segmentation and Audience Targeting - Building complex segments using logical operators
- Defining audiences based on behavioural thresholds
- Creating segments for high-value customer cohorts
- Combining dimensions, metrics, and time conditions
- Using segment persistence across multiple reports
- Exporting segment definitions for team collaboration
- Applying segments in A/B testing and personalisation
- Feeding audiences into Adobe Target and Audience Manager
- Setting up lookalike modelling from top converters
- Analysing mobile vs. desktop user behaviour by segment
- Identifying churn risk segments based on drop-off patterns
- Creating time-based loyalty segments (e.g. 90-day inactive)
- Using geo-based segments for regional campaign analysis
- Tagging segments for audit and compliance tracking
- Validating segment accuracy with sample data queries
Module 6: Attribution Modelling and Pathing Analysis - Understanding multi-touch attribution concepts
- Comparing linear, time decay, and position-based models
- Setting up custom attribution models in Analysis Workspace
- Analysing assisted conversions across channels
- Identifying top assist channels in customer journeys
- Using path length analysis to understand decision cycles
- Visualising common entry-to-exit paths
- Detecting looping behaviour and redirects
- Applying pathing to conversion funnel optimisation
- Benchmarking paths by device, region, or campaign
- Calculating contribution scores for each touchpoint
- Using conversion explorer to trace individual paths
- Adjusting for direct traffic influence in models
- Building exposure frequency models for remarketing
- Aligning attribution insights with budget allocation
Module 7: Real-Time Data Monitoring and Alert Systems - Accessing real-time reports in Adobe Analytics
- Monitoring active users across devices and regions
- Setting up threshold-based alerts for anomalies
- Using real-time dashboards during campaign launches
- Identifying bot traffic and filtering it proactively
- Monitoring site health during traffic spikes
- Responding to sudden drop-offs with rapid diagnosis
- Integrating with incident response and DevOps teams
- Customising real-time panel layouts for speed
- Tracking user count by campaign or content piece
- Using real-time data to adjust ad spend dynamically
- Creating alerts for form abandonment surges
- Setting alert delivery via email or Slack integration
- Analysing concurrent user spikes during live events
- Validating data integrity during high-volume periods
Module 8: Data Visualization and Stakeholder Communication - Selecting the right chart type for each data story
- Designing dashboards for executive consumption
- Using colour psychology to highlight insights
- Decluttering charts to remove noise
- Labelling best practices for clarity and consistency
- Adding summaries and insights boxes to reports
- Writing compelling titles that guide interpretation
- Presenting trends versus snapshots effectively
- Using before-and-after comparisons to show impact
- Creating narrative flows in multi-panel dashboards
- Converting analytics findings into spoken insights
- Preparing Q&A backups for stakeholder challenges
- Translating technical data into business language
- Building confidence with consistent reporting rhythm
- Using preview modes to control stakeholder access
Module 9: Campaign Tracking, UTM Strategy, and Acquisition Analysis - Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Setting up a data layer for consistent variable population
- Integrating Adobe Analytics with Adobe Experience Platform (AEP)
- Using Adobe Experience Platform Launch (Tags) effectively
- Rules, conditions, and actions in tag management
- Triggering analytics calls on page scroll, video play, form start
- Tracking single-page applications (SPAs) with dynamic data
- Validating implementation with browser developer tools
- Testing data capture before pushing to production
- Debugging missing or inflated metrics
- Implementing cross-domain and subdomain tracking
- Cookie handling and visitor identification logic
- Managing referrer data and campaign parameters
- UTM parameter mapping to Adobe variables
- Tracking offline conversions and CRM data sync
- Ensuring GDPR and privacy compliance in tracking setup
Module 4: Building High-Impact Reports and Dashboards - Creating custom reports using Analysis Workspace
- Dragging and dropping panels for multi-metric analysis
- Using flow reports to visualise user journey paths
- Building fallout reports to identify funnel drop-off points
- Designing executive dashboards with strategic KPIs
- Applying segment containers for comparative analysis
- Scheduling and automating report distribution
- Exporting data to PDF, CSV, or PowerPoint formats
- Using annotations to explain data shifts and events
- Leveraging bookmarks for report version control
- Sharing dashboards with stakeholders securely
- Setting up real-time alerting for threshold breaches
- Applying filters to isolate specific audience behaviours
- Using date range comparisons to show performance trends
- Creating reusable report templates for consistency
Module 5: Advanced Segmentation and Audience Targeting - Building complex segments using logical operators
- Defining audiences based on behavioural thresholds
- Creating segments for high-value customer cohorts
- Combining dimensions, metrics, and time conditions
- Using segment persistence across multiple reports
- Exporting segment definitions for team collaboration
- Applying segments in A/B testing and personalisation
- Feeding audiences into Adobe Target and Audience Manager
- Setting up lookalike modelling from top converters
- Analysing mobile vs. desktop user behaviour by segment
- Identifying churn risk segments based on drop-off patterns
- Creating time-based loyalty segments (e.g. 90-day inactive)
- Using geo-based segments for regional campaign analysis
- Tagging segments for audit and compliance tracking
- Validating segment accuracy with sample data queries
Module 6: Attribution Modelling and Pathing Analysis - Understanding multi-touch attribution concepts
- Comparing linear, time decay, and position-based models
- Setting up custom attribution models in Analysis Workspace
- Analysing assisted conversions across channels
- Identifying top assist channels in customer journeys
- Using path length analysis to understand decision cycles
- Visualising common entry-to-exit paths
- Detecting looping behaviour and redirects
- Applying pathing to conversion funnel optimisation
- Benchmarking paths by device, region, or campaign
- Calculating contribution scores for each touchpoint
- Using conversion explorer to trace individual paths
- Adjusting for direct traffic influence in models
- Building exposure frequency models for remarketing
- Aligning attribution insights with budget allocation
Module 7: Real-Time Data Monitoring and Alert Systems - Accessing real-time reports in Adobe Analytics
- Monitoring active users across devices and regions
- Setting up threshold-based alerts for anomalies
- Using real-time dashboards during campaign launches
- Identifying bot traffic and filtering it proactively
- Monitoring site health during traffic spikes
- Responding to sudden drop-offs with rapid diagnosis
- Integrating with incident response and DevOps teams
- Customising real-time panel layouts for speed
- Tracking user count by campaign or content piece
- Using real-time data to adjust ad spend dynamically
- Creating alerts for form abandonment surges
- Setting alert delivery via email or Slack integration
- Analysing concurrent user spikes during live events
- Validating data integrity during high-volume periods
Module 8: Data Visualization and Stakeholder Communication - Selecting the right chart type for each data story
- Designing dashboards for executive consumption
- Using colour psychology to highlight insights
- Decluttering charts to remove noise
- Labelling best practices for clarity and consistency
- Adding summaries and insights boxes to reports
- Writing compelling titles that guide interpretation
- Presenting trends versus snapshots effectively
- Using before-and-after comparisons to show impact
- Creating narrative flows in multi-panel dashboards
- Converting analytics findings into spoken insights
- Preparing Q&A backups for stakeholder challenges
- Translating technical data into business language
- Building confidence with consistent reporting rhythm
- Using preview modes to control stakeholder access
Module 9: Campaign Tracking, UTM Strategy, and Acquisition Analysis - Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Building complex segments using logical operators
- Defining audiences based on behavioural thresholds
- Creating segments for high-value customer cohorts
- Combining dimensions, metrics, and time conditions
- Using segment persistence across multiple reports
- Exporting segment definitions for team collaboration
- Applying segments in A/B testing and personalisation
- Feeding audiences into Adobe Target and Audience Manager
- Setting up lookalike modelling from top converters
- Analysing mobile vs. desktop user behaviour by segment
- Identifying churn risk segments based on drop-off patterns
- Creating time-based loyalty segments (e.g. 90-day inactive)
- Using geo-based segments for regional campaign analysis
- Tagging segments for audit and compliance tracking
- Validating segment accuracy with sample data queries
Module 6: Attribution Modelling and Pathing Analysis - Understanding multi-touch attribution concepts
- Comparing linear, time decay, and position-based models
- Setting up custom attribution models in Analysis Workspace
- Analysing assisted conversions across channels
- Identifying top assist channels in customer journeys
- Using path length analysis to understand decision cycles
- Visualising common entry-to-exit paths
- Detecting looping behaviour and redirects
- Applying pathing to conversion funnel optimisation
- Benchmarking paths by device, region, or campaign
- Calculating contribution scores for each touchpoint
- Using conversion explorer to trace individual paths
- Adjusting for direct traffic influence in models
- Building exposure frequency models for remarketing
- Aligning attribution insights with budget allocation
Module 7: Real-Time Data Monitoring and Alert Systems - Accessing real-time reports in Adobe Analytics
- Monitoring active users across devices and regions
- Setting up threshold-based alerts for anomalies
- Using real-time dashboards during campaign launches
- Identifying bot traffic and filtering it proactively
- Monitoring site health during traffic spikes
- Responding to sudden drop-offs with rapid diagnosis
- Integrating with incident response and DevOps teams
- Customising real-time panel layouts for speed
- Tracking user count by campaign or content piece
- Using real-time data to adjust ad spend dynamically
- Creating alerts for form abandonment surges
- Setting alert delivery via email or Slack integration
- Analysing concurrent user spikes during live events
- Validating data integrity during high-volume periods
Module 8: Data Visualization and Stakeholder Communication - Selecting the right chart type for each data story
- Designing dashboards for executive consumption
- Using colour psychology to highlight insights
- Decluttering charts to remove noise
- Labelling best practices for clarity and consistency
- Adding summaries and insights boxes to reports
- Writing compelling titles that guide interpretation
- Presenting trends versus snapshots effectively
- Using before-and-after comparisons to show impact
- Creating narrative flows in multi-panel dashboards
- Converting analytics findings into spoken insights
- Preparing Q&A backups for stakeholder challenges
- Translating technical data into business language
- Building confidence with consistent reporting rhythm
- Using preview modes to control stakeholder access
Module 9: Campaign Tracking, UTM Strategy, and Acquisition Analysis - Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Accessing real-time reports in Adobe Analytics
- Monitoring active users across devices and regions
- Setting up threshold-based alerts for anomalies
- Using real-time dashboards during campaign launches
- Identifying bot traffic and filtering it proactively
- Monitoring site health during traffic spikes
- Responding to sudden drop-offs with rapid diagnosis
- Integrating with incident response and DevOps teams
- Customising real-time panel layouts for speed
- Tracking user count by campaign or content piece
- Using real-time data to adjust ad spend dynamically
- Creating alerts for form abandonment surges
- Setting alert delivery via email or Slack integration
- Analysing concurrent user spikes during live events
- Validating data integrity during high-volume periods
Module 8: Data Visualization and Stakeholder Communication - Selecting the right chart type for each data story
- Designing dashboards for executive consumption
- Using colour psychology to highlight insights
- Decluttering charts to remove noise
- Labelling best practices for clarity and consistency
- Adding summaries and insights boxes to reports
- Writing compelling titles that guide interpretation
- Presenting trends versus snapshots effectively
- Using before-and-after comparisons to show impact
- Creating narrative flows in multi-panel dashboards
- Converting analytics findings into spoken insights
- Preparing Q&A backups for stakeholder challenges
- Translating technical data into business language
- Building confidence with consistent reporting rhythm
- Using preview modes to control stakeholder access
Module 9: Campaign Tracking, UTM Strategy, and Acquisition Analysis - Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Designing a standardised UTM parameter framework
- Mapping UTMs to eVars and campaign variables
- Tracking paid, organic, social, and email campaigns
- Identifying top-performing campaigns by conversion rate
- Analysing cost-per-acquisition by channel source
- Measuring assisted campaigns and indirect influence
- Setting up campaign expiry rules for accurate attribution
- Using campaign variables in segmentation and filtering
- Validating campaign tracking with URL testing tools
- Tracking offline campaigns using promo codes
- Analysing seasonality in acquisition performance
- Building campaign benchmarking reports
- Using campaign data to inform future spend decisions
- Identifying zombie campaigns with no ROI
- Automating campaign performance summaries
Module 10: Conversion Funnel Analysis and Optimization - Defining conversion events with precision
- Mapping the customer journey into funnel stages
- Building funnel reports to identify drop-off points
- Analysing funnel efficiency by segment and device
- Using fallout reports to pinpoint friction areas
- Validating funnel logic with sample session data
- Setting up micro-conversions to measure progress
- Measuring time-to-convert across user paths
- Identifying high-exit pages and entry barriers
- Testing funnel improvements with before-and-after data
- Linking funnel insights to UX and copy changes
- Calculating potential revenue recovery from drop-offs
- Building reusable funnel report templates
- Comparing funnel performance across regions
- Using funnel data to prioritise product fixes
Module 11: Product Performance and Merchandising Reports - Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Configuring product syntax and category hierarchy
- Tracking product views, adds to cart, and purchases
- Measuring product affinity and cross-sell potential
- Analysing out-of-stock impact on revenue
- Building best-seller and worst-performer reports
- Using merchandising eVars for category attribution
- Tracking internal promotions and onsite banners
- Measuring promo code effectiveness
- Analysing cart abandonment by product type
- Linking product views to conversion rates
- Calculating contribution margin per product line
- Using heatmaps in conjunction with product data
- Building seasonal product performance trends
- Forecasting inventory needs from behavioural data
- Sharing product reports with merchandising teams
Module 12: Mobile App and Cross-Device Analytics - Setting up Adobe Analytics for mobile apps
- Differences between web and app data structures
- Tracking app installs, launches, and sessions
- Measuring screen views and in-app events
- Analysing push notification effectiveness
- Tracking in-app purchases and subscription behaviour
- Using app lifecycle metrics for engagement scoring
- Connecting mobile web and app data with User IDs
- Building cross-device journey reports
- Analysing starting point differences by device
- Measuring retention and churn in mobile users
- Setting up custom app swizzling for advanced tracking
- Using deep linking to attribute app conversions
- Integrating app data with marketing automation
- Reporting on app store campaign performance
Module 13: Integrating Adobe Analytics with Other Tools - Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Connecting Adobe Analytics to Google Ads and Microsoft Ads
- Syncing data with Salesforce Marketing Cloud
- Feeding analytics segments into CRM platforms
- Using Adobe Experience Platform for data unification
- Integrating with Tableau and Power BI for visualisation
- Exporting raw data via Data Feed for SQL analysis
- Setting up API access for automation and custom apps
- Using Data Connectors for cloud warehouse sync
- Building custom alerts with Zapier integrations
- Linking analytics to Jira and Asana for task tracking
- Automating KPI reporting to Slack channels
- Exporting dashboards to PDF with scheduled triggers
- Using FTP delivery for offline data distribution
- Integrating with email marketing platforms like Mailchimp
- Synchronising with product analytics tools like Amplitude
Module 14: Data Governance, Compliance, and Quality Assurance - Establishing data taxonomy and naming standards
- Creating a data dictionary for team alignment
- Setting up variable approval workflows
- Tracking changes to implementation over time
- Validating data accuracy with sampling and reconciliation
- Using anomaly detection to flag data issues
- Handling consent management and opt-out flags
- Configuring data retention and deletion policies
- Monitoring data quality with scorecards
- Auditing tracking implementation quarterly
- Documenting technical decisions for future teams
- Using version control for report templates
- Training new analysts with standard operating procedures
- Managing user roles and permissions securely
- Complying with CCPA, GDPR, and other privacy laws
Module 15: Advanced Analysis Techniques and Custom Calculations - Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Building calculated metrics with formulas
- Creating ratios: conversion rate, bounce rate, engagement
- Using if-then logic in data calculations
- Deriving customer lifetime value (CLV) estimates
- Calculating average order value by segment
- Building cohort retention curves
- Measuring engagement depth with time-on-page averages
- Using outlier detection to clean data samples
- Applying statistical significance to test results
- Using percentile analysis for performance bands
- Creating custom funnels with dynamic entry points
- Building weighted attribution scores
- Analysing rate of change in key metrics
- Forecasting trends with linear progression models
- Applying seasonality adjustments to raw data
Module 16: Real-World Projects and Implementation Workflows - Project 1: Build a board-ready digital performance dashboard
- Project 2: Diagnose and fix a broken campaign tracking setup
- Project 3: Reconstruct a funnel with missing stages
- Project 4: Identify and quantify a revenue leakage opportunity
- Project 5: Create a cross-channel attribution report for CMO review
- Project 6: Design a mobile app engagement scorecard
- Project 7: Build a real-time campaign monitoring dashboard
- Project 8: Audit an existing implementation for data quality
- Project 9: Develop a standard UTM strategy for your organisation
- Project 10: Transform raw data into a spoken executive summary
- Using project checklists to ensure completeness
- Applying QA processes before stakeholder delivery
- Documenting decisions and assumptions in each project
- Receiving feedback templates for continuous improvement
- Exporting projects for portfolio and career advancement
Module 17: Certification Preparation and Career Advancement - Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights
- Overview of The Art of Service Certificate of Completion
- Requirements to earn your certification
- How to prepare for the final assessment
- Sample certification questions and model answers
- Time management during the final evaluation
- Submitting your capstone project for review
- How certification strengthens your LinkedIn and resume
- Leveraging your credential in job interviews
- Using certification to justify promotions and raises
- Joining The Art of Service alumni network
- Accessing advanced resources post-certification
- Continuing education pathways in data science
- Building a personal brand as a data-driven decision maker
- Contributing to internal analytics centres of excellence
- Transitioning into roles like Analytics Manager, Data Strategist, or Director of Insights