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