Digital Marketing

1. Analytics and Measurement
   1. Web Analytics Tools
      1. Google Analytics
         1. Setting up Google Analytics
            1. Creating an account
            2. Installing tracking code
            3. Configuring data views
         2. Key Features of Google Analytics
            1. Real-time reporting
            2. Audience reports
            3. Acquisition reports
            4. Behavior reports
            5. Conversion tracking
         3. Advanced Analytics Techniques
            1. Custom dashboards
            2. Goal setting and tracking
            3. Event tracking
            4. Enhanced eCommerce tracking
            5. Funnel visualization
      2. Adobe Analytics
         1. Overview and Capabilities
            1. Cross-channel analytics
            2. Predictive analytics
            3. Segment builder
         2. Implementation and Setup
            1. Data integration
            2. Tag-based tracking
         3. Key Features
            1. Customer journey insights
            2. Pathing analysis
            3. Cohort analysis
         4. Data Visualization and Reporting
            1. Custom reports
            2. Data warehouse functionality
            3. Integration with Adobe Marketing Cloud
   2. Key Performance Indicators (KPIs)
      1. Definition and Importance
         1. Understanding KPIs
         2. Role in performance evaluation
      2. Financial KPIs
         1. ROI/ROAS
            1. Calculation of ROI
            2. Factors impacting ROAS
         2. Customer Acquisition Cost (CAC)
            1. Significance of CAC in budgeting
            2. Methods to reduce CAC
         3. Customer Lifetime Value (CLV)
            1. Modeling CLV
            2. Importance in retention strategy
      3. Marketing and Engagement KPIs
         1. Website Traffic Metrics
            1. Page views
            2. Bounce rate
         2. Engagement Metrics
            1. Time on site
            2. Pages per session
         3. Conversion Metrics
            1. Conversion rate definition
            2. Multichannel conversion paths
   3. A/B Testing and Conversion Rate Optimization (CRO)
      1. A/B Testing Fundamentals
         1. Purpose and process of A/B testing
         2. Identifying elements to test
         3. Implementing A/B tests
         4. Analyzing test results
      2. Multivariate Testing
         1. How multivariate differs from A/B testing
         2. Setting up multivariate tests
         3. Measuring multivariate test outcomes
      3. Conversion Rate Optimization Techniques
         1. Website usability improvements
         2. Persuasive copywriting
         3. Simplifying conversion paths
         4. Reducing friction in the sales funnel
      4. Tools for A/B Testing and CRO
         1. Popular tools overview (e.g., Optimizely, VWO)
         2. Integrating with analytics platforms
   4. Data Collection and Management
      1. Data Sources in Marketing
         1. First-party data collection
         2. Third-party data usage
      2. Data Quality and Integrity
         1. Ensuring accurate data
         2. Common data errors and solutions
      3. Data Management Platforms (DMPs)
         1. Role of DMPs in analytics
         2. Integrating cross-channel data
         3. Leveraging DMPs for audience insights
   5. Reporting and Dashboard Creation
      1. Importance of Data Visualization
         1. Making data-driven decisions
         2. Storytelling with data
      2. Creating Effective Dashboards
         1. Selecting key metrics
         2. Designing user-friendly interfaces
         3. Customization for stakeholders
      3. Reporting Frameworks
         1. Monthly and quarterly reports
         2. Real-time analytics dashboards
         3. Comparative reports and benchmarking
   6. Data Privacy Considerations in Analytics
      1. Compliance with GDPR and CCPA
         1. Key provisions affecting analytics
         2. Ensuring data practices are compliant
      2. Ethical Considerations
         1. Balancing data collection and privacy
         2. Transparency and user consent
      3. Anonymization and Pseudonymization of Data
         1. Techniques for protecting user identity
         2. Impact on analytics accuracy