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
- Title Page
- Copyright Page
- Dedication
- Contents
- Acknowledgments [This content is currently in development.]
- About the Author [This content is currently in development.]
- Chapter 1. Ecommerce Analytics Creates Business Value and Drives Business Growth
- Chapter 2. The Ecommerce Analytics Value Chain
- Chapter 3. Methods and Techniques for Ecommerce Analysis
- Chapter 4. Visualizing, Dashboarding, and Reporting Ecommerce Data and Analysis
-
Chapter 5. Ecommerce Analytics Data Model and Technology
- Understanding the Ecommerce Analytics Data Model: Facts and Dimensions
- Explaining a Sample Ecommerce Data Model
- Understanding the Inventory Fact
- Understanding the Product Fact
- Understanding the Order Fact
- Understanding the Order Item Fact
- Understanding the Users Fact
- Understanding the User Order Fact
- Reviewing Common Dimensions and Measures in Ecommerce
- Chapter 6. Marketing and Advertising Analytics in Ecommerce
- Chapter 7. Analyzing Behavioral Data
-
Chapter 8. Optimizing for Ecommerce Conversion and User Experience
- The Importance of the Value Proposition in Conversion Optimization 1 page
- The Basics of Conversion Optimization: Persuasion, Psychology, Information Architecture to Copywriting
- The Conversion Optimization Process: Ideation to Hypothesis to Post Optimization Analysis
- The Data for Conversion Optimization: Analytics, Visualization, Research, Usability, Customer, and Network Data
- The Science Behind Conversion Optimization
- Succeeding with Conversion Optimization 1 page
-
Chapter 9. Analyzing Ecommerce Customers
- What Does a Customer Record look like in Ecommerce?
- What Customer Data Could I Start to Analyze?
- Questioning Customer Data with Analytical Thought
- Understanding the Ecommerce Customer Analytics Lifecycle
- Defining the Different Types of Customers
- Reviewing Types of Customer Analytics
- Segmenting Customers
- Performing Cohort Analysis
- Calculating Customer Lifetime Value
- Determining the Cost of Customer Acquisition
- Analyzing Customer Churn
- Understanding Voice of Customer Analytics
- Doing Recency, Frequency, and Monetary Analysis
- Determining Share of Wallet
- Scoring Customers
- Predicting Customer Behavior
- Clustering Customers
- Predicting Customer Propensities
- Personalizing Customer Experiences
-
Chapter 10. Analyzing Products and Orders in Ecommerce
- What are Ecommerce Orders?
- What Order Data Should I Begin to Analyze?
- What Metrics and Key Performance Indicators are Relevant for Ecommerce Transactions?
- Approaches to Analyzing Transactions
- Analyzing Products in Ecommerce
- Analyzing Merchandising in Ecommerce
- What Merchandising Data Should I Start Analyzing First?
- Chapter 11. Attribution in Ecommerce Analytics
- Chapter 12. What is an Ecommerce Platform?
- Chapter 13. Integrating Data and Analysis to Drive Your Ecommerce Strategy
- Chapter 14. Governing Data and Ensuring Privacy and Security
-
Chapter 15. Building Analytics Organizations and Socializing Successful Analytics
- Suggesting a Universal Approach for Building Successful Analytics Organizations
- Determining and Justifying the Need for and Analytics Team
- Gain Support for Hiring or Appointing a Leader for Analytics
- Hire the Analytics Leader
- Gather Business Requirements
- Create the Mission and Vision for the Analytics Team
- Create an Organizational Model
- Hire staff
- Assess the current state capabilities and determine the future state capabilities
- Assess the current state technology architecture and determine the future state architecture
- Begin building an analytics roadmap
- Train staff
- Map current processes, interactions, and workflows
- Build templates and artifacts to support the analytics process
- Create a supply and demand management model
- Create an operating model for working with stakeholders
- Use, deploy, and/or upgrade existing or new technology
- Collect or acquire new data
- Develop data catalog, master data management, and data governance
- Do analysis and data science and deliver analysis
- Meet with stakeholders and participate in business processes; and then socialize analysis on a regular cadence and periodicity
- Lead or assist with new work resulting from analytical processes
- Document and socialize the financial impact and business outcomes resulting from analysis
- Continue to do analysis, socialize, and manage technology emphasize the business impact ad infinitum
- Manage change and support stakeholders
- Chapter 16. The Future of Ecommerce Analytics
Product information
- Title: Ecommerce Analytics: Analyze and Improve the Impact of Your Digital Strategy
- Author(s):
- Release date: April 2016
- Publisher(s): Pearson
- ISBN: 9780134177953
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