Cover image for Learning Google Analytics

Learning Google Analytics

Author Mark Edmondson
Release Date: 2022/12/01
ISBN: 9781098113070
Topic:
0%
6
Chapters
0-1
Hours read
0k
Total Words
    Start Reading Now    
       Add to Wishlist       
View table of contents

Why is Google Analytics 4 the most modern data model available for digital marketing analytics? Because rather than simply report what has happened, GA4's new cloud integrations enable more data activation--linking online and offline data across all your streams to provide end-to-end marketing data. This practical book prepares you for the future of digital marketing by demonstrating how GA4 supports these additional cloud integrations.

Author Mark Edmondson, Google Developer Expert for Google Analytics and Google Cloud, provides a concise yet comprehensive overview of GA4 and its cloud integrations. Data, business, and marketing analysts will learn major facets of GA4's powerful new analytics model, with topics including data architecture and strategy, and data ingestion, storage, and modeling. You'll explore common data activation use cases and get guidance on how to implement them.

You'll learn:

  • How Google Cloud integrates with GA4
  • The potential use cases that GA4 integrations can enable
  • Skills and resources needed to create GA4 integrations
  • How much GA4 data capture is necessary to enable use cases
  • The process of designing dataflows from strategy though data storage, modeling, and activation

Table of Contents

  1. 1. The New Google Analytics 4
    1. Introducing GA4
    2. Why GA4?
    3. The Unification of Mobile and Web Analytics
    4. Firebase and BigQuery - first steps into the Cloud
    5. GA4 deployment
    6. Universal Analytics vs GA4
    7. The GA4 Data Model
    8. Events
    9. Custom parameters
    10. E-commerce items
    11. User Properties
    12. Google Cloud Platform (GCP)
    13. Relevant Google Cloud Platform Services
    14. Coding Skills
    15. Onboarding to Google Cloud Platform (GCP)
    16. Moving Up The Serverless Pyramid
    17. Wrap up
    18. Introduction to our use cases
    19. Use Case: Predictive Purchases
    20. Use Case: Audience Segmentation
    21. Use Case: Real-time Forecasting
    22. Summary
  2. 2. Data Architecture & Strategy
    1. Creating an environment for success
    2. Stakeholder Buy-In
    3. A Use Case Led Approach Avoiding Spaceships
    4. Demonstrating business value
    5. Assessing digital maturity
    6. Prioritising your use cases
    7. Technical Requirements
    8. Data Ingestion
    9. Data Storage
    10. Data Modelling
    11. Data Activation
    12. User Privacy
    13. Respecting User Privacy Choices
    14. Privacy By Design
    15. Helpful Tools
    16. gcloud
    17. Version Control / Git
    18. IDEs (Integrated Developer Environments)
    19. Docker
    20. Summary
3.149.252.37