Main points

  • Session Overview

    • The session is titled “Quickstart for Basic Intermediate Analysis Capabilities” and is led by Dr. Kirsten Schaffer.
    • The session is being recorded, and the link to the recording will be sent to all registered attendees.
  • Introduction of Speakers

    • Frederick, a Senior Customer Success Manager at Adobe, introduced the session.
    • Dr. Kirsten Schaffer, Principal Customer Success Manager at Adobe, is the presenter.
  • Session Content

    • The session covers setting up an organization for robust analytical capabilities, governance aspects, and running paths for analytics and customer journey analytics.
    • Discussion on when to use different Adobe solutions and Adobe’s recommendations for digital insights.
  • Key Topics Discussed

    • External and Internal Forces Impacting digital analytics, including market shifts, privacy and governance, data democracy, and data complexity.
    • Building a Robust Analytical Foundation Measurement strategy, data collection, insight and analysis, learning, data governance.
    • Setting Up a Digital Analytics Team Roles and responsibilities, creating a hybrid team, and managing analytics requests efficiently.
    • Adobe’s Enablement Options Experience League,on-demand courses, trainer-based classes, community support.
  • Comparison between Adobe Analytics and Customer Journey Analytics (CGA)

    • Adobe Analytics is foundational for digital analysis.
    • CGA offers greater data flexibility, privacy controls, and low latency for marketing activation.
    • Both solutions can be used simultaneously to support different reporting use cases.
  • Types of Analytics

    • Descriptive Analytics Real-time data visualization, conversion funnels, simple attribution.
    • Diagnostic Analyti Root cause analysis, anomaly detection, complex attribution models.
    • Predictive Analytics Forecasting, propensity scoring, advanced algorithms for decision-making.
  • Features and Use Cases

    • Conversion and Touchpoint Analysis Data exploration, visualization, guided analysis, and time series analysis.
    • Attribution Attribution models, cross-tab attribution analysis, and complex attribution in CGA.
    • Segmentation and Audience Generation Segment comparison, audience analysis, and publishing audiences for marketing activation.
    • Churn Prevention Cohort analysis, retention rate analysis, and propensity scores.
  • Q&A Highlights

    • Explanation of components and static data schemas.
    • Description of offline data.
    • Recommendations for migrating from Adobe Analytics to CGA.
    • Importance of defining a single source of truth for data reporting.
abac5052-c195-43a0-840d-39eac28f4780