Ecommerce Analytics: Analyze and Improve the Impact of Your Digital Strategy

Book description

Today's Complete, Focused, Up-to-Date Guide to Analytics for Ecommerce

  • Profit from analytics throughout the entire customer experience and lifecycle

  • Make the most of all the fast-changing data sources now available to you

  • For all ecommerce executives, strategists, entrepreneurs, marketers, analysts, and data scientists

  • Ecommerce Analytics is the only complete single-source guide to analytics for your ecommerce business. It brings together all the knowledge and skills you need to solve your unique problems, and transform your data into better decisions and customer experiences.

    Judah Phillips shows how to use analysis to improve ecommerce marketing and advertising, understand customer behavior, increase conversion rates, strengthen loyalty, optimize merchandising and product mix, streamline transactions, optimize product mix, and accurately attribute sales.

    Drawing on extensive experience leading large-scale analytics programs, he also offers expert guidance on building successful analytical teams; surfacing high-value insights via dashboards and visualization; and managing data governance, security, and privacy.

    Here are the answers you need to make the most of analytics in ecommerce: throughout your organization, across your entire customer lifecycle.

    Table of contents

    1. Title Page
    2. Copyright Page
    3. Dedication
    4. Contents
    5. Acknowledgments [This content is currently in development.]
    6. About the Author [This content is currently in development.]
    7. Chapter 1. Ecommerce Analytics Creates Business Value and Drives Business Growth
    8. Chapter 2. The Ecommerce Analytics Value Chain
      1. Identifying and Prioritizing Demand
      2. Developing an Analytical Plan
      3. Activating the Ecommerce Analytics Environment
      4. Preparing and Wrangling Data
      5. Analyzing, Predicting, Optimizing, and Automating with Data
      6. Socializing Analytics
      7. Communicating Economic Impact of Analytics
    9. Chapter 3. Methods and Techniques for Ecommerce Analysis
      1. Understanding the Calendar for Ecommerce Analysis
      2. Storytelling Is Important for Analysis
      3. Tukey’s Exploratory Data Analysis Is an Important Concept in Digital Analytics
      4. Types of Data: Simplified
      5. Looking at Data: Shapes of Data
    10. Chapter 4. Visualizing, Dashboarding, and Reporting Ecommerce Data and Analysis
      1. Understanding Reporting
      2. Explaining the RASTA Approach to Reporting
      3. Understanding Dashboarding
      4. Explaining the LIVES Approach to Dashboarding
      5. What Data Should I Start with in an Ecommerce Dashboard?
      6. Understanding Data Visualization
    11. Chapter 5. Ecommerce Analytics Data Model and Technology
      1. Understanding the Ecommerce Analytics Data Model: Facts and Dimensions
      2. Explaining a Sample Ecommerce Data Model
      3. Understanding the Inventory Fact
      4. Understanding the Product Fact
      5. Understanding the Order Fact
      6. Understanding the Order Item Fact
      7. Understanding the Users Fact
      8. Understanding the User Order Fact
      9. Reviewing Common Dimensions and Measures in Ecommerce
    12. Chapter 6. Marketing and Advertising Analytics in Ecommerce
      1. Understanding the Shared Goals of Marketing and Advertising Analysis
      2. Reviewing the Marketing Lifecycle
      3. Understanding the Types of Ecommerce Marketing
      4. Analyzing Marketing and Advertising for Ecommerce
      5. What Marketing Data Should You Begin to Analyze?
    13. Chapter 7. Analyzing Behavioral Data
      1. Answering Business Questions with Behavioral Analytics
      2. Understanding Metrics and Key Performance Indicators for Behavioral Analysis
      3. Reviewing Types of Ecommerce Behavioral Analysis
    14. Chapter 8. Optimizing for Ecommerce Conversion and User Experience
      1. The Importance of the Value Proposition in Conversion Optimization 1 page
      2. The Basics of Conversion Optimization: Persuasion, Psychology, Information Architecture to Copywriting
      3. The Conversion Optimization Process: Ideation to Hypothesis to Post Optimization Analysis
      4. The Data for Conversion Optimization: Analytics, Visualization, Research, Usability, Customer, and Network Data
      5. The Science Behind Conversion Optimization
      6. Succeeding with Conversion Optimization 1 page
    15. Chapter 9. Analyzing Ecommerce Customers
      1. What Does a Customer Record look like in Ecommerce?
      2. What Customer Data Could I Start to Analyze?
      3. Questioning Customer Data with Analytical Thought
      4. Understanding the Ecommerce Customer Analytics Lifecycle
      5. Defining the Different Types of Customers
      6. Reviewing Types of Customer Analytics
      7. Segmenting Customers
      8. Performing Cohort Analysis
      9. Calculating Customer Lifetime Value
      10. Determining the Cost of Customer Acquisition
      11. Analyzing Customer Churn
      12. Understanding Voice of Customer Analytics
      13. Doing Recency, Frequency, and Monetary Analysis
      14. Determining Share of Wallet
      15. Scoring Customers
      16. Predicting Customer Behavior
      17. Clustering Customers
      18. Predicting Customer Propensities
      19. Personalizing Customer Experiences
    16. Chapter 10. Analyzing Products and Orders in Ecommerce
      1. What are Ecommerce Orders?
      2. What Order Data Should I Begin to Analyze?
      3. What Metrics and Key Performance Indicators are Relevant for Ecommerce Transactions?
      4. Approaches to Analyzing Transactions
      5. Analyzing Products in Ecommerce
      6. Analyzing Merchandising in Ecommerce
      7. What Merchandising Data Should I Start Analyzing First?
    17. Chapter 11. Attribution in Ecommerce Analytics
      1. Attributing Sources of Buyers, Conversion, Revenue, and Profit
      2. Understanding Engagement Mapping and the Different Types of Attribution
      3. The Difference between Top Down and Bottoms Up Approaches to Attribution
      4. A Framework for Assessing Attribution Software
    18. Chapter 12. What is an Ecommerce Platform?
      1. Understanding the Core Data of an Ecommerce Platform to Analyze
      2. Understanding the Business Functions Supported by an Ecommerce Platforms
      3. Determining an Analytical Approach to Analyzing the Ecommerce Platform
    19. Chapter 13. Integrating Data and Analysis to Drive Your Ecommerce Strategy
      1. Defining the Different Types of Data; Single-Channel to Omnichannel
      2. Integrating Data from a Technical Perspective
      3. Integrating Analytics Applications
      4. Integrating Data from a Business Perspective
    20. Chapter 14. Governing Data and Ensuring Privacy and Security
      1. Applying Data Governance in Ecommerce
      2. Applying Data Privacy and Security in Ecommerce
      3. Governance, Privacy, and Security are part of the Analysts Job
    21. Chapter 15. Building Analytics Organizations and Socializing Successful Analytics
      1. Suggesting a Universal Approach for Building Successful Analytics Organizations
      2. Determining and Justifying the Need for and Analytics Team
      3. Gain Support for Hiring or Appointing a Leader for Analytics
      4. Hire the Analytics Leader
      5. Gather Business Requirements
      6. Create the Mission and Vision for the Analytics Team
      7. Create an Organizational Model
      8. Hire staff
      9. Assess the current state capabilities and determine the future state capabilities
      10. Assess the current state technology architecture and determine the future state architecture
      11. Begin building an analytics roadmap
      12. Train staff
      13. Map current processes, interactions, and workflows
      14. Build templates and artifacts to support the analytics process
      15. Create a supply and demand management model
      16. Create an operating model for working with stakeholders
      17. Use, deploy, and/or upgrade existing or new technology
      18. Collect or acquire new data
      19. Develop data catalog, master data management, and data governance
      20. Do analysis and data science and deliver analysis
      21. Meet with stakeholders and participate in business processes; and then socialize analysis on a regular cadence and periodicity
      22. Lead or assist with new work resulting from analytical processes
      23. Document and socialize the financial impact and business outcomes resulting from analysis
      24. Continue to do analysis, socialize, and manage technology emphasize the business impact ad infinitum
      25. Manage change and support stakeholders
    22. Chapter 16. The Future of Ecommerce Analytics
      1. The Future of Data Collection and Preparation
      2. The Future is Data Experiences
      3. Future Analytics and Technology Capabilities

    Product information

    • Title: Ecommerce Analytics: Analyze and Improve the Impact of Your Digital Strategy
    • Author(s): Judah Phillips
    • Release date: April 2016
    • Publisher(s): Pearson
    • ISBN: 9780134177953