Ecommerce analytics : analyze and improve the impact of your digital strategy

Chapter 1  Ecommerce Analytics Creates Business Value and Drives Business Growth   1Chapter 2  The Ecommerce Analytics Value Chain   9   Identifying and Prioritizing Demand   11   Developing an Analytical Plan   14   Activating the Ecommerce Analytics Environment   16   Preparing and Wrangling Data   20   Analyzing, Predicting, Optimizing, and Automating with Data   22   Socializing Analytics   23   Communicating the Economic Impact of Analytics   24Chapter 3  Methods and Techniques for Ecommerce Analysis   27   Understanding the Calendar for Ecommerce Analysis   28   Storytelling Is Important for Ecommerce Analysis   29   Tukey\'s Exploratory Data Analysis Is an Important Concept in Ecommerce Analytics   31   Types of Data: Simplified   34   Looking at Data: Shapes of Data   36   Analyzing Ecommerce Data Using Statistics and Machine Learning   47   Using Key Performance Indicators for Ecommerce   58Chapter 4  Visualizing, Dashboarding, and Reporting Ecommerce Data and Analysis   71   Understanding Reporting   75   Explaining the RASTA Approach to Reporting   77   Understanding Dashboarding   77   Explaining the LIVEN Approach to Dashboarding   80   What Data Should I Start With in an Ecommerce Dashboard?   81   Understanding Data Visualization   81Chapter 5  Ecommerce Analytics Data Model and Technology   91   Understanding the Ecommerce Analytics Data Model: Facts and Dimensions   93   Explaining a Sample Ecommerce Data Model   96   Understanding the Inventory Fact   97   Understanding the Product Fact   98   Understanding the Order Fact   98   Understanding the Order Item Fact   99   Understanding the Customers Fact   99   Understanding the Customer Order Fact   100   Reviewing Common Dimensions and Measures in Ecommerce   100Chapter 6  Marketing and Advertising Analytics in Ecommerce   103   Understanding the Shared Goals of Marketing and Advertising Analysis   105   Reviewing the Marketing Lifecycle   108   Understanding Types of Ecommerce Marketing   111   Analyzing Marketing and Advertising for Ecommerce   112   What Marketing Data Could You Begin to Analyze?   116Chapter 7  Analyzing Behavioral Data   119   Answering Business Questions with Behavioral Analytics   123   Understanding Metrics and Key Performance Indicators for Behavioral Analysis   124   Reviewing Types of Ecommerce Behavioral Analysis   126Chapter 8  Optimizing for Ecommerce Conversion and User Experience   133   The Importance of the Value Proposition in Conversion Optimization   137   The Basics of Conversion Optimization: Persuasion, Psychology, Information Architecture, and Copywriting   138   The Conversion Optimization Process: Ideation to Hypothesis to Post-Optimization Analysis   141   The Data for Conversion Optimization: Analytics, Visualization, Research, Usability, Customer, and Technical Data   145   The Science Behind Conversion Optimization   147   Succeeding with Conversion Optimization   151Chapter 9  Analyzing Ecommerce Customers   155   What Does a Customer Record Look Like in Ecommerce?   156   What Customer Data Could I Start to Analyze?   157   Questioning Customer Data with Analytical Thought   158   Understanding the Ecommerce Customer Analytics Lifecycle   159   Defining the Types of Customers   161   Reviewing Types of Customer Analytics   162   Segmenting Customers   163   Performing Cohort Analysis   165   Calculating Customer Lifetime Value   166   Determining the Cost of Customer Acquisition   168   Analyzing Customer Churn   169   Understanding Voice-of-the-Customer Analytics   170   Doing Recency, Frequency, and Monetary Analysis   171   Determining Share of Wallet   172   Scoring Customers   173   Predicting Customer Behavior   174   Clustering Customers   175   Predicting Customer Propensities   176   Personalizing Customer Experiences   178Chapter 10  Analyzing Products and Orders in Ecommerce   179   What Are Ecommerce Orders?   181   What Order Data Should I Begin to Analyze?   183   What Metrics and Key Performance Indicators Are Relevant for Ecommerce Orders?   184   Approaches to Analyzing Orders and Products   186   Analyzing Products in Ecommerce   193   Analyzing Merchandising in Ecommerce   198   What Merchandising Data Should I Start Analyzing First?   210Chapter 11  Attribution in Ecommerce Analytics   213   Attributing Sources of Buyers, Conversion, Revenue, and Profit   217   Understanding Engagement Mapping and the Types of Attribution   220   The Difference between Top-Down and Bottom-Up Approaches to Attribution   224   A Framework for Assessing Attribution Software   225Chapter 12  What Is an Ecommerce Platform?   229   Understanding the Core Components of an Ecommerce Platform   232   Understanding the Business Functions Supported by an Ecommerce Platform   235   Determining an Analytical Approach to Analyzing the Ecommerce Platform   239Chapter 13  Integrating Data and Analysis to Drive Your Ecommerce Strategy   241   Defining the Types of Data, Single-Channel to Omnichannel   243   Integrating Data from a Technical Perspective   246   Integrating Analytics Applications   259   Integrating Data from a Business Perspective   261Chapter 14  Governing Data and Ensuring Privacy and Security   263   Applying Data Governance in Ecommerce   268   Applying Data Privacy and Security in Ecommerce   272   Governance, Privacy, and Security Are Part of the Analyst\'s Job   276Chapter 15  Building Analytics Organizations and Socializing Successful Analytics   279   Suggesting a Universal Approach for Building Successful Analytics Organizations   280   Determine and Justify the Need for an Analytics Team   283   Gain Support for Hiring or Appointing a Leader for Analytics   285   Hire the Analytics Leader   287   Gather Business Requirements   288   Create the Mission and Vision for the Analytics Team   289   Create an Organizational Model   289   Hire Staff   291   Assess the Current State Capabilities and Determine the Future State Capabilities   291   Assess the Current State Technology Architecture and Determine the Future State Architecture   292   Begin Building an Analytics Road Map   294   Train Staff   294   Map Current Processes, Interactions, and Workflows   295   Build Templates and Artifacts to Support the Analytics Process   296   Create a Supply-and-Demand Management Model   296   Create an Operating Model for Working with Stakeholders   297   Use, Deploy, or Upgrade Existing or New Technology   298   Collect or Acquire New Data   298   Implement a Data Catalog, Master Data Management, and Data Governance   299   Meet with Stakeholders and Participate in Business Processes, and Then Socialize Analysis on a Regular Cadence and Periodicity   300   Do Analysis and Data Science and Deliver It   300   Lead or Assist with New Work Resulting from Analytical Processes   302   Document and Socialize the Financial Impact and Business Outcomes Resulting from Analysis   303   Continue to Do Analysis, Socialize It, and Manage Technology While Emphasizing the Business Impact Ad Infinitum   303   Manage Change and Support Stakeholders   304Chapter 16  The Future of Ecommerce Analytics   307   The Future of Data Collection and Preparation   311   The Future Is Data Experiences   313   Future Analytics and Technology Capabilities   314Bibliography   319Index   329