Description

Introduction
Adobe Analytics is a powerful tool used by organizations to gather, analyze, and report on digital data. It allows for in-depth analysis of user behaviors, interactions, and business performance across web and mobile applications. This advanced course is designed to deepen your understanding of Adobe Analytics, focusing on advanced reporting techniques, data analysis methods, and actionable insights that drive strategic decision-making. By the end of this course, you’ll be able to leverage Adobe Analytics’ full potential to optimize marketing campaigns, enhance user experiences, and improve business outcomes.

Prerequisites

• Familiarity with the basics of Adobe Analytics
• Experience with web and app analytics, report creation, and data collection
• Knowledge of key analytics concepts such as metrics, dimensions, and variables
• Understanding of HTML, JavaScript, and digital marketing strategies is helpful but not required

Table of Contents

1. Advanced Reporting Techniques in Adobe Analytics
1.1 Customizing and Enhancing Standard Reports
1.2 Using Advanced Segmentation for Deeper Insights
1.3 Building Complex Data Queries with Adobe Analytics
1.4 Utilizing Calculated Metrics and Custom Dimensions

2. Creating and Managing Dashboards
2.1 Advanced Dashboard Design Principles
2.2 Building Interactive Dashboards for Stakeholders
2.3 Using Data Visualizations and Custom Graphs
2.4 Sharing and Scheduling Dashboards for Regular Reporting

3. Analyzing User Behavior with Adobe Analytics
3.1 Behavioral Segmentation: Grouping Users Based on Actions
3.2 Funnel Analysis: Tracking Conversion Paths and Drop-Offs
3.3 Pathing Analysis: Visualizing User Journey Across Channels
3.4 Heatmaps and Clickstream Analysis for Deeper Interaction Insights

4. Advanced Data Analysis Techniques
4.1 Applying Statistical Methods to Analyze Trends
4.2 Predictive Analytics and Forecasting User Behavior
4.3 Cohort Analysis: Grouping Users by Acquisition Date and Behavior
4.4 Anomaly Detection: Identifying and Understanding Outliers

5. Attribution Modeling and Multi-Channel Analytics
5.1 Introduction to Attribution Models in Adobe Analytics
5.2 Multi-Touch Attribution for Multi-Channel Campaigns
5.3 Using the Marketing Channel Processing Rules
5.4 Analyzing Customer Journeys Across Multiple Touchpoints

6. Leveraging Adobe Sensei for Advanced Insights
6.1 Overview of Adobe Sensei’s Machine Learning Capabilities
6.2 Automated Insights: Getting Actionable Recommendations
6.3 Analyzing Predictive Metrics for Future Trends
6.4 Integrating Adobe Sensei with Adobe Analytics Reports

7. Managing and Optimizing Data Quality
7.1 Techniques for Ensuring Data Accuracy and Completeness
7.2 Identifying Data Gaps and Resolving Collection Issues
7.3 Implementing Data Governance Best Practices
7.4 Creating Data Quality Dashboards for Ongoing Monitoring

8. Integrating Adobe Analytics with Other Platforms
8.1 Integration with Adobe Target for Personalization Insights
8.2 Combining Adobe Analytics and Adobe Campaign for Cross-Channel Analysis
8.3 Connecting Adobe Analytics with Third-Party Tools (e.g., Google Analytics)
8.4 Advanced Integration with Data Warehouses and Data Lakes

9. Using APIs for Advanced Data Analysis
9.1 Introduction to Adobe Analytics APIs
9.2 Automating Reports and Data Exports via APIs
9.3 Integrating Adobe Analytics Data with Business Intelligence Tools
9.4 Building Custom Analytics Dashboards Using API Data

10. Advanced Marketing Analytics with Adobe Analytics
10.1 Analyzing Marketing Campaign Performance
10.2 Measuring ROI and Conversion Rates Across Multiple Campaigns
10.3 A/B Testing and Multivariate Testing for Optimization
10.4 Leveraging Adobe Analytics for Real-Time Campaign Adjustments

11. Using Advanced Segments for Deeper Insights
11.1 Building Complex Segments Based on User Attributes
11.2 Combining Multiple Segments to Gain Detailed Insights
11.3 Leveraging Dynamic Segmentation for Real-Time Analytics
11.4 Segmenting Based on Visitor Context (Device, Location, Behavior)

12. Performance Metrics and Optimization
12.1 Analyzing Site Speed and Performance Metrics
12.2 Optimizing Conversion Rates Using Analytics Data
12.3 Identifying Areas for UX/UI Improvement
12.4 Enhancing Mobile and Desktop Performance Through Data Insights

13. Real-World Use Cases and Case Studies
13.1 Case Study: Using Adobe Analytics to Improve E-commerce Performance
13.2 Analyzing Cross-Channel Marketing Campaigns for Improved Results
13.3 Case Study: Reducing Bounce Rates and Improving Retention
13.4 Real-World Examples of Data-Driven Business Decisions

14. Best Practices and Advanced Tips
14.1 Advanced Report Filters and Conditional Logic
14.2 Mastering the Adobe Analytics Workspace and Navigation
14.3 Leveraging Adobe Analytics in a Cross-Departmental Environment
14.4 Staying Up to Date with Adobe Analytics Features and Updates

Conclusion
Mastering Adobe Analytics for advanced reporting and data analysis will allow you to derive deeper insights from your digital data and apply them to enhance your business strategies. This course provides the tools to navigate advanced features, use analytics to predict trends, and integrate data from multiple platforms for comprehensive reporting. By applying these advanced techniques, you will be able to drive more informed decisions, optimize digital marketing efforts, and maximize business impact.