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 I
Judah Phillips helps companies create value with analytics and data science by improving business performance. Judah has led analytics and data science teams for Fortune 500 companies and has improved their financial performance through the applied analysis of data, the management of analytical and technical resources, and the alignment and optimization of analytics strategy against short-term roadmaps and long-term strategic visions. Judah strongly believes that cutting-edge technology is critical and necessary but often becomes technical overhead unless strategy is aligned with excellence in organizational development, operational management, and delivery execution that is solidly tied to impacting material financial goals. Judah has worked for or been hired as a consultant by Internet companies, media companies, consumer product companies, financial services firms, and various types of agencies.* He is the sole author of three books on analytics, including Ecommerce Analytics, Building a Digital Analytics Organization, and Digital Analytics Primer. Judah has also authored chapters, edited, or contributed to the development of other books: Measuring the Digital World, Advanced Business Analytics, Sales and Marketing Analytics, Digital Is Changing Everything, The Complete Guide to B2B Marketing, and Multichannel Marketing Metrics.* He served on various boards of or advised established and start-up technology companies, including global leaders in digital analytics, mobile analytics, ecommerce, mobile apps, and advertising technology.* He is an Adjunct Professor at Babson College and has guest lectured on analytics and data science at the business schools for New York University, Boston College, Northeastern University, and others.* He is the former V.I.P. at Harvard Innovation Lab, where he advised Harvard start-ups about analytics and data science.* He has spoken at more than 70 technology and industry conferences since 2006.Judah holds a master of science in finance and a master of business administration from Northeastern University and a B.A. from the University of Massachusetts Amherst.