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Index
Chapter 1 Using Digital Analytics to Create Business Value
Big Data and Data Science Requires Digital Analytics Defining Digital Analytics
Chapter 2 Analytics Value Chain and the P’s of Digital Analytics
Explaining the P’s of Digital Analytics The Analytics Value Chain: Process for Tactical and Strategic Success The Analytics Work Request Process
Chapter 3 Building an Analytics Organization
Justifying Investment in the Analytics Team Creating the Analytics Team Business Justification and Investment Consideration Reporting to Executives and Other Teams about Analytics Value Generation Creating Analytics Team Roles and Responsibilities Enhancing Your Career: Methods for Success
Chapter 4 What Are Analytics Tools?
To Build or to Buy? Balancing Management of Analytics Technology: Should “the Business” or IT Run It? Selecting an Analytics Tool Succeeding with Tool Deployment Business Concerns: Maintenance Why Do Digital Analytics Tools and Data Decay?
Chapter 5 Methods and Techniques for Digital Analysis
Storytelling Is Important for Analysis Tukey’s Exploratory Data Analysis Is an Important Concept in Digital Analytics Types of Data: Simplified Looking at Data: Shapes of Data Analyzing Digital Data Using Statistics and Machine Learning
Chapter 6 Defining, Planning, Collecting, and Governing Data in Digital Analytics
Defining Digital Data: How to Do It What Are Business Definitions for Digital Data? What Are Operational Definitions for Digital Data? What Are Technical Definitions for Digital Data? Creating and Maintaining Data Definitions Planning for Digital Data: What Should You Do? Collecting Digital Data: What You Need to Know Governing Digital Data: The Data Governance Function The Data Governance Team: What Do They Do? The Process for Data Governance Across Programs, Projects, and Teams The Difficulty of Testing and Verifying Data
Chapter 7 Reporting Data and Using Key Performance Indicators
What Is Reporting and How Does It Happen? The Five Elements of Excellent Reporting: RASTA The Difference Between Reporting and Dashboarding What Is Dashboarding and How Does It Happen? The Five Elements of Excellent Dashboarding: LIVES Understanding Key Performance Indicators (KPIs) Where Does Reporting and Dashboarding Fit in the Analytics Value Chain? Example KPIs: Averages, Percentages, Rates/Ratios, “Per X”, and Derivatives Real-Time Versus Timely Data: A Practitioner Perspective
Chapter 8 Optimization and Testing with Digital Analytics: Test, Don’t Guess
Reviewing the AB Test: Start Here Expanding to Multivariate Testing Creating a Testing and Optimization Plan The Process of AB and Multivariate Testing Technologies and Methods for Measuring, Analyzing, and Reporting Results of AB and Multivariate Testing Types of Optimization Enabled Through Testing Setting Up a Digital Optimization Program Developing Controlled Experiments and Digital Data Science Tips for Testing and Optimizing Digital Experiences
Chapter 9 Qualitative and Voice of Customer Data and Digital Analytics
Listening to Your Customer Is More Important Today Than Ever Before Tools of the Trade: Market Research and Qualitative Data Collection Methods and Techniques Creating Customer Feedback Systems Such as Call Centers and Online Feedback Forms What Does a Qualitative Data Team Do and How Does It Work with Digital Analytics? Integrating Digital Behavioral Data with Qualitative Data Working Successfully Together and with the Business: Qualitative and Quantitative Data, Research, and Analytics Teams
Chapter 10 Competitive Intelligence and Digital Analytics
Competitive Intelligence Versus Digital Intelligence Types of Digital Competitive Intelligence: Real-World Examples Digital Competitive Intelligence Tools and Methods The Process for Digital Competitive Intelligence Integrating Digital Behavioral Data with Competitive Intelligence
Chapter 11 Targeting and Automation with Digital Analytics
Types of Targeting Where in Digital Does Targeting Occur? What Is Retargeting? Types of Retargeting How Can the Digital Analytics Team Assist the Process of Targeting and Retargeting? Suggestions When Targeting and Retargeting: Lessons Learned
Chapter 12 Converging Omnichannels and Integrating Data for Understanding Customers, Audiences, and Media
Types of Omnichannel Data Omnichannel Data Metrics Defining Customer Analytics: Enabled by Omnichannel Data Integration Questioning Customers Using Their Data and Your Analytics The Unified Customer Life Cycle Work Activities in Customer Analytics via Omnichannel Data Integration Challenges to Customer Analytics What’s Required for the Digital Analytics Team to Do Customer Analytics via Omnichannel Integration?
Chapter 13 Future of Digital Analytics
Predictive Personalization Closed-Loop Behavioral Feedback Systems Real-Time, Addressable, Relevant Content and Advertising Delivered Unified Across Multiscreens Sensing and Responding Interacting and Alerting Geo-Specific Relevance and Intent Targeting Automated Services and Product Delivery Data-Interactive Shopper and Customer Experiences The Future of Analytics Requires Privacy and Ethics Works Cited Index
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